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Bag A, Ghosh G, Sultan MJ, Chouhdry HH, Hong SJ, Trung TQ, Kang GY, Lee NE. Bio-Inspired Sensory Receptors for Artificial-Intelligence Perception. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024:e2403150. [PMID: 38699932 DOI: 10.1002/adma.202403150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Revised: 04/16/2024] [Indexed: 05/05/2024]
Abstract
In the era of artificial intelligence (AI), there is a growing interest in replicating human sensory perception. Selective and sensitive bio-inspired sensory receptors with synaptic plasticity have recently gained significant attention in developing energy-efficient AI perception. Various bio-inspired sensory receptors and their applications in AI perception are reviewed here. The critical challenges for the future development of bio-inspired sensory receptors are outlined, emphasizing the need for innovative solutions to overcome hurdles in sensor design, integration, and scalability. AI perception can revolutionize various fields, including human-machine interaction, autonomous systems, medical diagnostics, environmental monitoring, industrial optimization, and assistive technologies. As advancements in bio-inspired sensing continue to accelerate, the promise of creating more intelligent and adaptive AI systems becomes increasingly attainable, marking a significant step forward in the evolution of human-like sensory perception.
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Affiliation(s)
- Atanu Bag
- School of Advanced Materials Science & Engineering, Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea
- Research Centre for Advanced Materials Technology, Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea
| | - Gargi Ghosh
- School of Advanced Materials Science & Engineering, Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea
| | - M Junaid Sultan
- School of Advanced Materials Science & Engineering, Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea
| | - Hamna Haq Chouhdry
- SKKU Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea
| | - Seok Ju Hong
- School of Advanced Materials Science & Engineering, Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea
| | - Tran Quang Trung
- School of Advanced Materials Science & Engineering, Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea
| | - Geun-Young Kang
- School of Advanced Materials Science & Engineering, Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea
| | - Nae-Eung Lee
- School of Advanced Materials Science & Engineering, Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea
- Research Centre for Advanced Materials Technology, Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea
- SKKU Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea
- Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Institute of Quantum Biophysics (IQB) and Biomedical Institute for Convergence at SKKU (BICS), Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea
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2
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Li Y, Cai W, Tao R, Shuai W, Rao J, Chang C, Lu X, Ning H. Flexible and Energy-Efficient Synaptic Transistor with Quasi-Linear Weight Update Protocol by Inkjet Printing of Orientated Polar-Electret/High- k Oxide Composite Dielectric. ACS APPLIED MATERIALS & INTERFACES 2024; 16:19271-19282. [PMID: 38591357 DOI: 10.1021/acsami.4c02880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/10/2024]
Abstract
Inkjet printing artificial synapse is cost-effective but challenging in emulating synaptic dynamics with a sufficient number of effective weight states under ultralow voltage spiking operation. A synaptic transistor gated by inkjet-printed composite dielectric of polar-electret polyvinylpyrrolidone (PVP) and high-k zirconia oxide (ZrOx) is proposed and thus synthesized to solve this issue. Quasi-linear weight update with a large variation margin is obtained through the coupling effect and the facilitation of dipole orientation, which can be attributed to the orderly arranged molecule chains induced by the carefully designed microfluidic flows. Crucial features of biological synapses including long-term plasticity, spike-timing-dependence-plasticity (STDP), "Learning-Experience" behavior, and ultralow energy consumption (<10 fJ/pulse) are successfully implemented on the device. Simulation results exhibit an excellent image recognition accuracy (97.1%) after 15 training epochs, which is the highest for printed synaptic transistors. Moreover, the device sustained excellent endurance against bending tests with radius down to 8 mm. This work presents a very viable solution for constructing the futuristic flexible and low-cost neural systems.
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Affiliation(s)
- Yushan Li
- Institute for Advanced Materials, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, China
- Guangdong Provincial Key Laboratory of Optical Information Materials, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, China
| | - Wei Cai
- Jihua Laboratory, Foshan, Guangzhou 528000, China
| | - Ruiqiang Tao
- Institute for Advanced Materials, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, China
- Guangdong Provincial Key Laboratory of Optical Information Materials, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, China
| | - Wentao Shuai
- Institute for Advanced Materials, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, China
- Guangdong Provincial Key Laboratory of Optical Information Materials, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, China
| | - Jingjing Rao
- Institute for Advanced Materials, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, China
- Guangdong Provincial Key Laboratory of Optical Information Materials, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, China
| | - Cheng Chang
- Institute for Advanced Materials, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, China
- Guangdong Provincial Key Laboratory of Optical Information Materials, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, China
| | - Xubing Lu
- Institute for Advanced Materials, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, China
- Guangdong Provincial Key Laboratory of Optical Information Materials, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, China
| | - Honglong Ning
- Institute of Polymer Optoelectronic Materials and Devices, State Key Laboratory of Luminescent Materials and Devices, South China University of Technology, Guangzhou 510640, China
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3
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Shen W, Wang P, Wei G, Yuan S, Chen M, Su Y, Xu B, Li G. SiC@NiO Core-Shell Nanowire Networks-Based Optoelectronic Synapses for Neuromorphic Computing and Visual Systems at High Temperature. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2024:e2400458. [PMID: 38607289 DOI: 10.1002/smll.202400458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Revised: 03/18/2024] [Indexed: 04/13/2024]
Abstract
1D nanowire networks, sharing similarities of structure, information transfer, and computation with biological neural networks, have emerged as a promising platform for neuromorphic systems. Based on brain-like structures of 1D nanowire networks, neuromorphic synaptic devices can overcome the von Neumann bottleneck, achieving intelligent high-efficient sensing and computing function with high information processing rates and low power consumption. Here, high-temperature neuromorphic synaptic devices based on SiC@NiO core-shell nanowire networks optoelectronic memristors (NNOMs) are developed. Experimental results demonstrate that NNOMs attain synaptic short/long-term plasticity and modulation plasticity under both electrical and optical stimulation, and exhibit advanced functions such as short/long-term memory and "learning-forgetting-relearning" under optical stimulation at both room temperature and 200 °C. Based on the advanced functions under light stimulus, the constructed 5 × 3 optoelectronic synaptic array devices exhibit a stable visual memory function up to 200 °C, which can be utilized to develop artificial visual systems. Additionally, when exposed to multiple electronic or optical stimuli, the NNOMs effectively replicate the principles of Pavlovian classical conditioning, achieving visual heterologous synaptic functionality and refining neural networks. Overall, with abundant synaptic characteristics and high-temperature thermal stability, these neuromorphic synaptic devices offer a promising route for advancing neuromorphic computing and visual systems.
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Affiliation(s)
- Weikang Shen
- Xi'an Key Laboratory of Compound Semiconductor Materials and Devices, School of Physics & Information Science, Shaanxi University of Science and Technology, Xi'an, Shaanxi, 710021, P. R. China
| | - Pan Wang
- Xi'an Key Laboratory of Compound Semiconductor Materials and Devices, School of Physics & Information Science, Shaanxi University of Science and Technology, Xi'an, Shaanxi, 710021, P. R. China
| | - Guodong Wei
- Xi'an Key Laboratory of Compound Semiconductor Materials and Devices, School of Physics & Information Science, Shaanxi University of Science and Technology, Xi'an, Shaanxi, 710021, P. R. China
- Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering, Taiyuan, Shanxi, 030024, P. R. China
| | - Shuai Yuan
- Xi'an Key Laboratory of Compound Semiconductor Materials and Devices, School of Physics & Information Science, Shaanxi University of Science and Technology, Xi'an, Shaanxi, 710021, P. R. China
| | - Mi Chen
- Xi'an Key Laboratory of Compound Semiconductor Materials and Devices, School of Physics & Information Science, Shaanxi University of Science and Technology, Xi'an, Shaanxi, 710021, P. R. China
| | - Ying Su
- Xi'an Key Laboratory of Compound Semiconductor Materials and Devices, School of Physics & Information Science, Shaanxi University of Science and Technology, Xi'an, Shaanxi, 710021, P. R. China
| | - Bingshe Xu
- Xi'an Key Laboratory of Compound Semiconductor Materials and Devices, School of Physics & Information Science, Shaanxi University of Science and Technology, Xi'an, Shaanxi, 710021, P. R. China
- Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering, Taiyuan, Shanxi, 030024, P. R. China
| | - Guoqiang Li
- Xi'an Key Laboratory of Compound Semiconductor Materials and Devices, School of Physics & Information Science, Shaanxi University of Science and Technology, Xi'an, Shaanxi, 710021, P. R. China
- The School of Integrated Circuits, State Key Laboratory of Luminescent Materials and Devices, South China University of Technology, Guangzhou, 510641, P. R. China
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4
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Fan ZY, Tang Z, Fang JL, Jiang YP, Liu QX, Tang XG, Zhou YC, Gao J. Neuromorphic Computing of Optoelectronic Artificial BFCO/AZO Heterostructure Memristors Synapses. NANOMATERIALS (BASEL, SWITZERLAND) 2024; 14:583. [PMID: 38607116 PMCID: PMC11013421 DOI: 10.3390/nano14070583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Revised: 03/19/2024] [Accepted: 03/25/2024] [Indexed: 04/13/2024]
Abstract
Compared with purely electrical neuromorphic devices, those stimulated by optical signals have gained increasing attention due to their realistic sensory simulation. In this work, an optoelectronic neuromorphic device based on a photoelectric memristor with a Bi2FeCrO6/Al-doped ZnO (BFCO/AZO) heterostructure is fabricated that can respond to both electrical and optical signals and successfully simulate a variety of synaptic behaviors, such as STP, LTP, and PPF. In addition, the photomemory mechanism was identified by analyzing the energy band structures of AZO and BFCO. A convolutional neural network (CNN) architecture for pattern classification at the Mixed National Institute of Standards and Technology (MNIST) was used and improved the recognition accuracy of the MNIST and Fashion-MNIST datasets to 95.21% and 74.19%, respectively, by implementing an improved stochastic adaptive algorithm. These results provide a feasible approach for future implementation of optoelectronic synapses.
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Affiliation(s)
- Zhao-Yuan Fan
- School of Physics and Optoelectric Engineering, Guangdong University of Technology, Guangzhou Higher Education Mega Center, Guangzhou 510006, China; (Z.-Y.F.)
| | - Zhenhua Tang
- School of Physics and Optoelectric Engineering, Guangdong University of Technology, Guangzhou Higher Education Mega Center, Guangzhou 510006, China; (Z.-Y.F.)
| | - Jun-Lin Fang
- School of Physics and Optoelectric Engineering, Guangdong University of Technology, Guangzhou Higher Education Mega Center, Guangzhou 510006, China; (Z.-Y.F.)
| | - Yan-Ping Jiang
- School of Physics and Optoelectric Engineering, Guangdong University of Technology, Guangzhou Higher Education Mega Center, Guangzhou 510006, China; (Z.-Y.F.)
| | - Qiu-Xiang Liu
- School of Physics and Optoelectric Engineering, Guangdong University of Technology, Guangzhou Higher Education Mega Center, Guangzhou 510006, China; (Z.-Y.F.)
| | - Xin-Gui Tang
- School of Physics and Optoelectric Engineering, Guangdong University of Technology, Guangzhou Higher Education Mega Center, Guangzhou 510006, China; (Z.-Y.F.)
| | - Yi-Chun Zhou
- School of Advanced Materials and Nanotechnology, Xidian University, Xi’an 710126, China
| | - Ju Gao
- Department of Physics, The University of Hong Kong, Hong Kong 999077, China
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5
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Nath SK, Das SK, Nandi SK, Xi C, Marquez CV, Rúa A, Uenuma M, Wang Z, Zhang S, Zhu RJ, Eshraghian J, Sun X, Lu T, Bian Y, Syed N, Pan W, Wang H, Lei W, Fu L, Faraone L, Liu Y, Elliman RG. Optically Tunable Electrical Oscillations in Oxide-Based Memristors for Neuromorphic Computing. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024:e2400904. [PMID: 38516720 DOI: 10.1002/adma.202400904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 03/18/2024] [Indexed: 03/23/2024]
Abstract
The application of hardware-based neural networks can be enhanced by integrating sensory neurons and synapses that enable direct input from external stimuli. This work reports direct optical control of an oscillatory neuron based on volatile threshold switching in V3O5. The devices exhibit electroforming-free operation with switching parameters that can be tuned by optical illumination. Using temperature-dependent electrical measurements, conductive atomic force microscopy (C-AFM), in situ thermal imaging, and lumped element modelling, it is shown that the changes in switching parameters, including threshold and hold voltages, arise from overall conductivity increase of the oxide film due to the contribution of both photoconductive and bolometric characteristics of V3O5, which eventually affects the oscillation dynamics. Furthermore, V3O5 is identified as a new bolometric material with a temperature coefficient of resistance (TCR) as high as -4.6% K-1 at 423 K. The utility of these devices is illustrated by demonstrating in-sensor reservoir computing with reduced computational effort and an optical encoding layer for spiking neural network (SNN), respectively, using a simulated array of devices.
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Affiliation(s)
- Shimul Kanti Nath
- Department of Electrical, Electronic and Computer Engineering, The University of Western Australia, 35 Stirling Highway, Perth, WA, 6009, Australia
- Department of Electronic Materials Engineering, Research School of Physics, The Australian National University, Canberra, ACT, 2601, Australia
- School of Photovoltaic and Renewable Energy Engineering, University of New South Wales (UNSW Sydney), Kensington, NSW, 2052, Australia
| | - Sujan Kumar Das
- Department of Electronic Materials Engineering, Research School of Physics, The Australian National University, Canberra, ACT, 2601, Australia
- Department of Physics, Jahangirnagar Univeristy, Savar, Dhaka, 1342, Bangladesh
| | - Sanjoy Kumar Nandi
- Department of Electronic Materials Engineering, Research School of Physics, The Australian National University, Canberra, ACT, 2601, Australia
| | - Chen Xi
- Department of Electrical and Electronic Engineering, the University of Hong Kong, Pok Fu Lam Rd, Hong Kong Island, Hong Kong
| | | | - Armando Rúa
- Department of Physics, University of Puerto Rico, Mayaguez, PR, 00681, USA
| | - Mutsunori Uenuma
- Information Device Science Laboratory, Nara Institute of Science and Technology (NAIST), Nara, 630-0192, Japan
| | - Zhongrui Wang
- Department of Electrical and Electronic Engineering, the University of Hong Kong, Pok Fu Lam Rd, Hong Kong Island, Hong Kong
| | - Songqing Zhang
- Department of Electrical, Electronic and Computer Engineering, The University of Western Australia, 35 Stirling Highway, Perth, WA, 6009, Australia
| | - Rui-Jie Zhu
- Department of Electrical and Computer Engineering, University of California, Santa Cruz, CA, 95064, USA
| | - Jason Eshraghian
- Department of Electrical and Computer Engineering, University of California, Santa Cruz, CA, 95064, USA
| | - Xiao Sun
- John de Laeter Centre, Curtin University, Perth, WA, 6102, Australia
| | - Teng Lu
- Research School of Chemistry, The Australian National University, Canberra, ACT, 2601, Australia
| | - Yue Bian
- Department of Electronic Materials Engineering, Research School of Physics, The Australian National University, Canberra, ACT, 2601, Australia
- Australian Research Council Centre of Excellence for Transformative Meta-Optical Systems, Canberra, ACT, 2601, Australia
| | - Nitu Syed
- Australian Research Council Centre of Excellence for Transformative Meta-Optical Systems, School of Physics, University of Melbourne, Melbourne, Victoria, 3010, Australia
| | - Wenwu Pan
- Department of Electrical, Electronic and Computer Engineering, The University of Western Australia, 35 Stirling Highway, Perth, WA, 6009, Australia
- Australian Research Council Centre of Excellence for Transformative Meta-Optical Systems, Perth, WA, 6009, Australia
| | - Han Wang
- Department of Electrical, Electronic and Computer Engineering, The University of Western Australia, 35 Stirling Highway, Perth, WA, 6009, Australia
| | - Wen Lei
- Department of Electrical, Electronic and Computer Engineering, The University of Western Australia, 35 Stirling Highway, Perth, WA, 6009, Australia
| | - Lan Fu
- Department of Electronic Materials Engineering, Research School of Physics, The Australian National University, Canberra, ACT, 2601, Australia
- Australian Research Council Centre of Excellence for Transformative Meta-Optical Systems, Canberra, ACT, 2601, Australia
| | - Lorenzo Faraone
- Department of Electrical, Electronic and Computer Engineering, The University of Western Australia, 35 Stirling Highway, Perth, WA, 6009, Australia
- Australian Research Council Centre of Excellence for Transformative Meta-Optical Systems, Perth, WA, 6009, Australia
| | - Yun Liu
- Research School of Chemistry, The Australian National University, Canberra, ACT, 2601, Australia
| | - Robert G Elliman
- Department of Electronic Materials Engineering, Research School of Physics, The Australian National University, Canberra, ACT, 2601, Australia
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6
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Wang J, Ilyas N, Ren Y, Ji Y, Li S, Li C, Liu F, Gu D, Ang KW. Technology and Integration Roadmap for Optoelectronic Memristor. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2307393. [PMID: 37739413 DOI: 10.1002/adma.202307393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 09/10/2023] [Indexed: 09/24/2023]
Abstract
Optoelectronic memristors (OMs) have emerged as a promising optoelectronic Neuromorphic computing paradigm, opening up new opportunities for neurosynaptic devices and optoelectronic systems. These OMs possess a range of desirable features including minimal crosstalk, high bandwidth, low power consumption, zero latency, and the ability to replicate crucial neurological functions such as vision and optical memory. By incorporating large-scale parallel synaptic structures, OMs are anticipated to greatly enhance high-performance and low-power in-memory computing, effectively overcoming the limitations of the von Neumann bottleneck. However, progress in this field necessitates a comprehensive understanding of suitable structures and techniques for integrating low-dimensional materials into optoelectronic integrated circuit platforms. This review aims to offer a comprehensive overview of the fundamental performance, mechanisms, design of structures, applications, and integration roadmap of optoelectronic synaptic memristors. By establishing connections between materials, multilayer optoelectronic memristor units, and monolithic optoelectronic integrated circuits, this review seeks to provide insights into emerging technologies and future prospects that are expected to drive innovation and widespread adoption in the near future.
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Affiliation(s)
- Jinyong Wang
- School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 117576, Singapore
| | - Nasir Ilyas
- School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China
| | - Yujing Ren
- Department of Chemical and Biomolecular Engineering, National University of Singapore, Singapore, 117585, Singapore
| | - Yun Ji
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 117576, Singapore
| | - Sifan Li
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 117576, Singapore
| | - Changcun Li
- School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China
| | - Fucai Liu
- School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China
| | - Deen Gu
- School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China
- State Key Laboratory of Electronic Thin Films and Integrated Devices, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China
| | - Kah-Wee Ang
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 117576, Singapore
- Institute of Materials Research and Engineering, A*STAR, Singapore, 138634, Singapore
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7
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Hasina D, Saini M, Kumar M, Mandal A, Basu N, Maiti P, Srivastava SK, Som T. Site-Specific Emulation of Neuronal Synaptic Behavior in Au Nanoparticle-Decorated Self-Organized TiO x Surface. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2024; 20:e2305605. [PMID: 37803918 DOI: 10.1002/smll.202305605] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 09/18/2023] [Indexed: 10/08/2023]
Abstract
Neuromorphic computing is a potential approach for imitating massive parallel processing capabilities of a bio-synapse. To date, memristors have emerged as the most appropriate device for designing artificial synapses for this purpose due to their excellent analog switching capacities with high endurance and retention. However, to build an operational neuromorphic platform capable of processing high-density information, memristive synapses with nanoscale footprint are important, albeit with device size scaled down, retaining analog plasticity and low power requirement often become a challenge. This paper demonstrates site-selective self-assembly of Au nanoparticles on a patterned TiOx layer formed as a result of ion-induced self-organization, resulting in site-specific resistive switching and emulation of bio-synaptic behavior (e.g., potentiation, depression, spike rate-dependent and spike timing-dependent plasticity, paired pulse facilitation, and post tetanic potentiation) at nanoscale. The use of local probe-based methods enables nanoscale probing on the anisotropic films. With the help of various microscopic and spectroscopic analytical tools, the observed results are attributed to defect migration and self-assembly of implanted Au atoms on self-organized TiOx surfaces. By leveraging the site-selective evolution of gold-nanostructures, the functionalized TiOx surface holds significant potential in a multitude of fields for developing cutting-edge neuromorphic computing platforms and Au-based biosensors with high-density integration.
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Affiliation(s)
- Dilruba Hasina
- SUNAG Laboratory, Institute of Physics, Sachivalaya Marg, Bhubaneswar, 751005, India
- Homi Bhabha National Institute, Training School Complex, Anushakti Nagar, Mumbai, 400085, India
| | - Mahesh Saini
- SUNAG Laboratory, Institute of Physics, Sachivalaya Marg, Bhubaneswar, 751005, India
| | - Mohit Kumar
- Department of Materials Science and Engineering, Ajou University, Suwon, 16499, Republic of Korea
| | - Aparajita Mandal
- SUNAG Laboratory, Institute of Physics, Sachivalaya Marg, Bhubaneswar, 751005, India
| | - Nilanjan Basu
- School of Physics, University of Hyderabad, Hyderabad, 500046, India
| | - Paramita Maiti
- TEM Laboratory, Institute of Physics, 751005, Sachivalaya Marg, Bhubaneswar, India
| | | | - Tapobrata Som
- SUNAG Laboratory, Institute of Physics, Sachivalaya Marg, Bhubaneswar, 751005, India
- Homi Bhabha National Institute, Training School Complex, Anushakti Nagar, Mumbai, 400085, India
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8
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Kumar M, Park J, Kim J, Seo H. Room-Temperature Quantum Diodes with Dynamic Memory for Neural Logic Operations. ACS APPLIED MATERIALS & INTERFACES 2023; 15:56003-56013. [PMID: 37992323 DOI: 10.1021/acsami.3c13031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/24/2023]
Abstract
The pursuit of high-performance, next-generation nanoelectronics is fundamentally reliant on exploiting quantum phenomena such as tunneling at room temperature. However, quantum tunneling and memory dynamics are governed by two conflicting parameters: the presence or absence of defects. Therefore, the integration of both attributes within a single device presents substantial challenges. Nevertheless, successful integration has the potential to prompt crucial breakthroughs by emulating biobrain-like dynamics, in turn enabling sophisticated in-material neural logic operations. In this work, we demonstrate that a conformal nanolaminate HfO2/ZrO2 structure on silicon enables high-performing (>106 s) Fowler-Nordheim tunneling at room temperature. In addition, the device exhibits unipolar dynamic hysteresis loop opening (on/off ratio >102) with high endurance (>104 cycles) along with negative differential resistance, which is attributed to the collective ferroelectric and capacitive effects and is utilized to emulate synaptic functions. Further, proof-of-concept logic gates based on voltage-dependent plasticity and time-domain were developed using a single device, offering in-material neural-like data processing. These findings pave the way for the realization of high-performing and scalability tunneling devices in advanced nanoelectronics, which mark a promising route toward the development of next-generation, fundamental neural logic computing systems.
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Affiliation(s)
- Mohit Kumar
- Department of Energy Systems Research, Ajou University, Suwon 16499, Republic of Korea
- Department of Materials Science and Engineering, Ajou University, Suwon 16499, Republic of Korea
| | - Jiyeong Park
- Department of Energy Systems Research, Ajou University, Suwon 16499, Republic of Korea
| | - Junmo Kim
- Department of Energy Systems Research, Ajou University, Suwon 16499, Republic of Korea
| | - Hyungtak Seo
- Department of Energy Systems Research, Ajou University, Suwon 16499, Republic of Korea
- Department of Materials Science and Engineering, Ajou University, Suwon 16499, Republic of Korea
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9
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Kim HS, Park H, Cho WJ. Light-Stimulated IGZO Transistors with Tunable Synaptic Plasticity Based on Casein Electrolyte Electric Double Layer for Neuromorphic Systems. Biomimetics (Basel) 2023; 8:532. [PMID: 37999173 PMCID: PMC10669183 DOI: 10.3390/biomimetics8070532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 11/05/2023] [Accepted: 11/07/2023] [Indexed: 11/25/2023] Open
Abstract
In this study, optoelectronic synaptic transistors based on indium-gallium-zinc oxide (IGZO) with a casein electrolyte-based electric double layer (EDL) were examined. The casein electrolyte played a crucial role in modulating synaptic plasticity through an internal proton-induced EDL effect. Thus, important synaptic behaviors, such as excitatory post-synaptic current, paired-pulse facilitation, and spike rate-dependent and spike number-dependent plasticity, were successfully implemented by utilizing the persistent photoconductivity effect of the IGZO channel stimulated by light. The synergy between the light stimulation and the EDL effect allowed the effective modulation of synaptic plasticity, enabling the control of memory levels, including the conversion of short-term memory to long-term memory. Furthermore, a Modified National Institute of Standards and Technology digit recognition simulation was performed using a three-layer artificial neural network model, achieving a high recognition rate of 90.5%. These results demonstrated a high application potential of the proposed optoelectronic synaptic transistors in neuromorphic visual systems.
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Affiliation(s)
- Hwi-Su Kim
- Department of Electronic Materials Engineering, Kwangwoon University, Gwangun-ro 20, Nowon-gu, Seoul 01897, Republic of Korea;
| | - Hamin Park
- Department of Electronic Engineering, Kwangwoon University, Gwangun-ro 20, Nowon-gu, Seoul 01897, Republic of Korea;
| | - Won-Ju Cho
- Department of Electronic Materials Engineering, Kwangwoon University, Gwangun-ro 20, Nowon-gu, Seoul 01897, Republic of Korea;
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10
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Huang PY, Jiang BY, Chen HJ, Xu JY, Wang K, Zhu CY, Hu XY, Li D, Zhen L, Zhou FC, Qin JK, Xu CY. Neuro-inspired optical sensor array for high-accuracy static image recognition and dynamic trace extraction. Nat Commun 2023; 14:6736. [PMID: 37872169 PMCID: PMC10593955 DOI: 10.1038/s41467-023-42488-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 10/12/2023] [Indexed: 10/25/2023] Open
Abstract
Neuro-inspired vision systems hold great promise to address the growing demands of mass data processing for edge computing, a distributed framework that brings computation and data storage closer to the sources of data. In addition to the capability of static image sensing and processing, the hardware implementation of a neuro-inspired vision system also requires the fulfilment of detecting and recognizing moving targets. Here, we demonstrated a neuro-inspired optical sensor based on two-dimensional NbS2/MoS2 hybrid films, which featured remarkable photo-induced conductance plasticity and low electrical energy consumption. A neuro-inspired optical sensor array with 10 × 10 NbS2/MoS2 phototransistors enabled highly integrated functions of sensing, memory, and contrast enhancement capabilities for static images, which benefits convolutional neural network (CNN) with a high image recognition accuracy. More importantly, in-sensor trajectory registration of moving light spots was experimentally implemented such that the post-processing could yield a high restoration accuracy. Our neuro-inspired optical sensor array could provide a fascinating platform for the implementation of high-performance artificial vision systems.
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Affiliation(s)
- Pei-Yu Huang
- Sauvage Laboratory for Smart Materials, School of Materials Science and Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen, 518055, China
| | - Bi-Yi Jiang
- School of Microelectronics, Southern University of Science and Technology, Shenzhen, 518055, China
- Department of Applied Physics, The Hong Kong Polytechnic University, Hong Kong, 999077, China
| | - Hong-Ji Chen
- Sauvage Laboratory for Smart Materials, School of Materials Science and Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen, 518055, China
| | - Jia-Yi Xu
- School of Microelectronics, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Kang Wang
- Key Laboratory of MEMS of the Ministry of Education, Southeast University, Nanjing, 210096, China
| | - Cheng-Yi Zhu
- Sauvage Laboratory for Smart Materials, School of Materials Science and Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen, 518055, China
| | - Xin-Yan Hu
- School of Microelectronics, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Dong Li
- Sauvage Laboratory for Smart Materials, School of Materials Science and Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen, 518055, China
| | - Liang Zhen
- MOE Key Laboratory of Micro-Systems and Micro-Structures Manufacturing, Harbin Institute of Technology, Harbin, 150080, China
| | - Fei-Chi Zhou
- School of Microelectronics, Southern University of Science and Technology, Shenzhen, 518055, China.
| | - Jing-Kai Qin
- Sauvage Laboratory for Smart Materials, School of Materials Science and Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen, 518055, China.
| | - Cheng-Yan Xu
- Sauvage Laboratory for Smart Materials, School of Materials Science and Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen, 518055, China.
- MOE Key Laboratory of Micro-Systems and Micro-Structures Manufacturing, Harbin Institute of Technology, Harbin, 150080, China.
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11
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Lee H, Hwang JH, Song SH, Han H, Han S, Suh BL, Hur K, Kyhm J, Ahn J, Cho JH, Hwang DK, Lee E, Choi C, Lim JA. Chiroptical Synaptic Heterojunction Phototransistors Based on Self-Assembled Nanohelix of π-Conjugated Molecules for Direct Noise-Reduced Detection of Circularly Polarized Light. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2304039. [PMID: 37501319 PMCID: PMC10520648 DOI: 10.1002/advs.202304039] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/16/2023] [Indexed: 07/29/2023]
Abstract
High-performance chiroptical synaptic phototransistors are successfully demonstrated using heterojunctions composed of a self-assembled nanohelix of a π-conjugated molecule and a metal oxide semiconductor. To impart strong chiroptical activity to the device, a diketopyrrolopyrrole-based π-conjugated molecule decorated with chiral glutamic acid is newly synthesized; this molecule is capable of supramolecular self-assembly through noncovalent intermolecular interactions. In particular, nanohelix formed by intertwinded fibers with strong and stable chiroptical activity in a solid-film state are obtained through hydrogen-bonding-driven, gelation-assisted self-assembly. Phototransistors based on interfacial charge transfer at the heterojunction from the chiroptical nanohelix to the metal oxide semiconductor show excellent chiroptical detection with a high photocurrent dissymmetry factor of 1.97 and a high photoresponsivity of 218 A W-1 . The chiroptical phototransistor demonstrates photonic synapse-like, time-dependent photocurrent generation, along with persistent photoconductivity, which is attributed to the interfacial charge trapping. Through the advantage of synaptic functionality, a trained convolutional neural network successfully recognizes noise-reduced circularly polarized images of handwritten alphabetic characters with better than 89.7% accuracy.
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Affiliation(s)
- Hanna Lee
- Center for Opto‐Electronic Materials and DevicesKorea Institute of Science and TechnologySeoul02792Republic of Korea
- Department of Chemical and Biomolecular EngineeringYonsei UniversitySeoul03722Republic of Korea
| | - Jun Ho Hwang
- School of Materials Science and EngineeringGwangju Institute of Science and TechnologyGwangju61005Republic of Korea
| | - Seung Ho Song
- Center for Opto‐Electronic Materials and DevicesKorea Institute of Science and TechnologySeoul02792Republic of Korea
| | - Hyemi Han
- Center for Opto‐Electronic Materials and DevicesKorea Institute of Science and TechnologySeoul02792Republic of Korea
| | - Seo‐Jung Han
- Chemical and Biological Integrative Research CenterKorea Institute of Science and TechnologySeoul02792Republic of Korea
- Division of Bio‐Medical Science and TechnologyKIST SchoolUniversity of Science and Technology of KoreaSeoul02792Republic of Korea
| | - Bong Lim Suh
- Extreme Materials Research CenterKorea Institute of Science and TechnologySeoul02792Republic of Korea
| | - Kahyun Hur
- Extreme Materials Research CenterKorea Institute of Science and TechnologySeoul02792Republic of Korea
| | - Jihoon Kyhm
- Technology Support CenterKorea Institute of Science and TechnologySeoul02792Republic of Korea
| | - Jongtae Ahn
- Center for Opto‐Electronic Materials and DevicesKorea Institute of Science and TechnologySeoul02792Republic of Korea
| | - Jeong Ho Cho
- Department of Chemical and Biomolecular EngineeringYonsei UniversitySeoul03722Republic of Korea
| | - Do Kyung Hwang
- Center for Opto‐Electronic Materials and DevicesKorea Institute of Science and TechnologySeoul02792Republic of Korea
- KU‐KIST Graduate School of Converging Science and TechnologyKorea UniversitySeoul02841Republic of Korea
- Division of Nano and Information TechnologyKIST SchoolUniversity of Science and TechnologySeoul02792Republic of Korea
| | - Eunji Lee
- School of Materials Science and EngineeringGwangju Institute of Science and TechnologyGwangju61005Republic of Korea
| | - Changsoon Choi
- Center for Opto‐Electronic Materials and DevicesKorea Institute of Science and TechnologySeoul02792Republic of Korea
| | - Jung Ah Lim
- Center for Opto‐Electronic Materials and DevicesKorea Institute of Science and TechnologySeoul02792Republic of Korea
- Division of Nano and Information TechnologyKIST SchoolUniversity of Science and TechnologySeoul02792Republic of Korea
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12
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Wang H, Zhang Y, Zhou C, Wang X, Ma H, Yin J, Shi H, An Z, Huang W. Photoactivated organic phosphorescence by stereo-hindrance engineering for mimicking synaptic plasticity. LIGHT, SCIENCE & APPLICATIONS 2023; 12:90. [PMID: 37037811 PMCID: PMC10086021 DOI: 10.1038/s41377-023-01132-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 03/12/2023] [Accepted: 03/13/2023] [Indexed: 06/19/2023]
Abstract
Purely organic phosphorescent materials with dynamically tunable optical properties and persistent luminescent characteristics enable more novel applications in intelligent optoelectronics. Herein, we reported a concise and universal strategy to achieve photoactivated ultralong phosphorescence at room temperature through stereo-hindrance engineering. Such dynamically photoactivated phosphorescence behavior was ascribed to the suppression of non-radiative transitions and improvement of spin-orbit coupling (SOC) as the variation of the distorted molecular conformation by the synergistic effect of electrostatic repulsion and steric hindrance. This "trainable" phosphorescent behavior was first proposed to mimic biological synaptic plasticity, especially for unique experience-dependent plasticity, by the manipulation of pulse intensity and numbers. This study not only outlines a principle to design newly dynamic phosphorescent materials, but also broadens their utility in intelligent sensors and robotics.
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Affiliation(s)
- He Wang
- Key Laboratory of Flexible Electronics (KLoFE) & Institute of Advanced Materials (IAM), Nanjing Tech University, Nanjing, 211800, China
| | - Yuan Zhang
- Key Laboratory of Flexible Electronics (KLoFE) & Institute of Advanced Materials (IAM), Nanjing Tech University, Nanjing, 211800, China
| | - Chifeng Zhou
- Key Laboratory of Flexible Electronics (KLoFE) & Institute of Advanced Materials (IAM), Nanjing Tech University, Nanjing, 211800, China
| | - Xiao Wang
- The Institute of Flexible Electronics (IFE, Future Technologies), Xiamen University, Xiamen, 361005, China
| | - Huili Ma
- Key Laboratory of Flexible Electronics (KLoFE) & Institute of Advanced Materials (IAM), Nanjing Tech University, Nanjing, 211800, China
| | - Jun Yin
- Department of Applied Physics, The Hong Kong Polytechnic University, Kowloon, 999077, Hong Kong, China
| | - Huifang Shi
- Key Laboratory of Flexible Electronics (KLoFE) & Institute of Advanced Materials (IAM), Nanjing Tech University, Nanjing, 211800, China.
- State Key Laboratory of Organic Electronics and Information Displays & Institute of Advanced Materials (IAM), Nanjing University of Posts & Telecommunications, 9 Wenyuan Road, Nanjing, 210023, China.
| | - Zhongfu An
- Key Laboratory of Flexible Electronics (KLoFE) & Institute of Advanced Materials (IAM), Nanjing Tech University, Nanjing, 211800, China.
- The Institute of Flexible Electronics (IFE, Future Technologies), Xiamen University, Xiamen, 361005, China.
| | - Wei Huang
- Key Laboratory of Flexible Electronics (KLoFE) & Institute of Advanced Materials (IAM), Nanjing Tech University, Nanjing, 211800, China.
- The Institute of Flexible Electronics (IFE, Future Technologies), Xiamen University, Xiamen, 361005, China.
- State Key Laboratory of Organic Electronics and Information Displays & Institute of Advanced Materials (IAM), Nanjing University of Posts & Telecommunications, 9 Wenyuan Road, Nanjing, 210023, China.
- Frontiers Science Center for Flexible Electronics (FSCFE), MIIT Key Laboratory of Flexible Electronics (KLoFE), Northwestern Polytechnical University, Xi'an, 710072, China.
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13
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All oxide based flexible multi-folded invisible synapse as vision photo-receptor. Sci Rep 2023; 13:1454. [PMID: 36702838 PMCID: PMC9880003 DOI: 10.1038/s41598-023-28505-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 01/19/2023] [Indexed: 01/27/2023] Open
Abstract
All oxide-based transparent flexible memristor is prioritized for the potential application in artificially simulated biological optoelectronic synaptic devices. SnOx memristor with HfOx layer is found to enable a significant effect on synaptic properties. The memristor exhibits good reliability with long retention, 104 s, and high endurance, 104 cycles. The optimized 6 nm thick HfOx layer in SnOx-based memristor possesses the excellent synaptic properties of stable 350 epochs training, multi-level conductance (MLC) behaviour, and the nonlinearity of 1.53 and 1.46 for long-term potentiation and depression, respectively, and faster image recognition accuracy of 100% after 23 iterations. The maximum weight changes of -73.12 and 79.91% for the potentiation and depression of the synaptic device, respectively, are observed from the spike-timing-dependent plasticity (STDP) characteristics making it suitable for biological applications. The flexibility of the device on the PEN substrate is confirmed by the acceptable change of nonlinearities up to 4 mm bending. Such a synaptic device is expected to be used as a vision photo-receptor.
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14
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Zhang L, Zhang Y, Liu F, Chen Q, Lian Y, Ma Q. On-Chip Photonic Synapses with All-Optical Memory and Neural Network Computation. MICROMACHINES 2022; 14:74. [PMID: 36677135 PMCID: PMC9862829 DOI: 10.3390/mi14010074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 12/22/2022] [Accepted: 12/22/2022] [Indexed: 06/17/2023]
Abstract
Inspired by the human brain, neural network computing was expected to break the bottleneck of traditional computing, but the integrated design still faces great challenges. Here, a readily integrated membrane-system photonic synapse was demonstrated. By pre-pulse training at 1064 nm (cutoff wavelength), the photonic synapse can be regulated both excitatory and inhibitory at tunable wavelengths (1200-2000 nm). Furthermore, more weights and memory functions were shown through the photonic synapse integrated network. Additionally, the digital recognition function of the single-layer perceptron neural network constructed by photonic synapses has been successfully demonstrated. Most of the biological synaptic functions were realized by the photonic synaptic network, and it had the advantages of compact structure, scalable, adjustable wavelength, and so on, which opens up a new idea for the study of the neural synaptic network.
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Affiliation(s)
- Lulu Zhang
- MOE Key Laboratory of Trans-Scale Laser Manufacturing Technology, Beijing University of Technology, Beijing 100124, China
- Beijing Engineering Research Center of Laser Technology, Beijing University of Technology, Beijing 100124, China
- Institute of Laser Engineering, Faculty of Materials and Manufacturing, Beijing University of Technology, Beijing 100124, China
| | - Yongzhi Zhang
- MOE Key Laboratory of Trans-Scale Laser Manufacturing Technology, Beijing University of Technology, Beijing 100124, China
- Beijing Engineering Research Center of Laser Technology, Beijing University of Technology, Beijing 100124, China
- Institute of Laser Engineering, Faculty of Materials and Manufacturing, Beijing University of Technology, Beijing 100124, China
| | - Furong Liu
- MOE Key Laboratory of Trans-Scale Laser Manufacturing Technology, Beijing University of Technology, Beijing 100124, China
- Beijing Engineering Research Center of Laser Technology, Beijing University of Technology, Beijing 100124, China
- Institute of Laser Engineering, Faculty of Materials and Manufacturing, Beijing University of Technology, Beijing 100124, China
| | - Qingyuan Chen
- MOE Key Laboratory of Trans-Scale Laser Manufacturing Technology, Beijing University of Technology, Beijing 100124, China
- Beijing Engineering Research Center of Laser Technology, Beijing University of Technology, Beijing 100124, China
- Institute of Laser Engineering, Faculty of Materials and Manufacturing, Beijing University of Technology, Beijing 100124, China
| | - Yangbo Lian
- MOE Key Laboratory of Trans-Scale Laser Manufacturing Technology, Beijing University of Technology, Beijing 100124, China
- Beijing Engineering Research Center of Laser Technology, Beijing University of Technology, Beijing 100124, China
- Institute of Laser Engineering, Faculty of Materials and Manufacturing, Beijing University of Technology, Beijing 100124, China
| | - Quanlong Ma
- MOE Key Laboratory of Trans-Scale Laser Manufacturing Technology, Beijing University of Technology, Beijing 100124, China
- Beijing Engineering Research Center of Laser Technology, Beijing University of Technology, Beijing 100124, China
- Institute of Laser Engineering, Faculty of Materials and Manufacturing, Beijing University of Technology, Beijing 100124, China
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15
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Kim JH, Stolte M, Würthner F. Wavelength and Polarization Sensitive Synaptic Phototransistor Based on Organic n-type Semiconductor/Supramolecular J-Aggregate Heterostructure. ACS NANO 2022; 16:19523-19532. [PMID: 36356301 DOI: 10.1021/acsnano.2c09747] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Human retina- and brain-inspired optoelectronic synapses, which integrate light detection and signal memory functions for data processing, have significant interest because of their potential applications for artificial vision technology. In nature, many animals such as mantis shrimp use polarized light information as well as scalar information including wavelength and intensity; however, a spectropolarimetric organic optoelectronic synapse has been seldom investigated. Herein, we report an organic synaptic phototransistor, consisting of a charge trapping liquid-crystalline perylene bisimide J-aggregate and a charge transporting crystalline dichlorinated naphthalene diimide, that can detect both wavelength and polarization information. The device shows persistent positive and negative photocurrents under low and high voltage conditions, respectively. Furthermore, the aligned organic heterostructure in the thin-film enables linearly polarized light to be absorbed with a dichroic ratio of 1.4 and 3.7 under transverse polarized blue and red light illumination, respectively. These features allow polarized light sensitive postsynaptic functions in the device. Consequently, a simple polarization imaging sensor array is successfully demonstrated using photonic synapses, which suggests that a supramolecular material is an important candidate for the development of spectropolarimetric neuromorphic vision systems.
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Affiliation(s)
- Jin Hong Kim
- Center for Nanosystems Chemistry (CNC) and Bavarian Polymer Institute (BPI), Universität Würzburg, 97074 Würzburg, Germany
| | - Matthias Stolte
- Center for Nanosystems Chemistry (CNC) and Bavarian Polymer Institute (BPI), Universität Würzburg, 97074 Würzburg, Germany
- Institut für Organische Chemie, Universität Würzburg, 97074 Würzburg, Germany
| | - Frank Würthner
- Center for Nanosystems Chemistry (CNC) and Bavarian Polymer Institute (BPI), Universität Würzburg, 97074 Würzburg, Germany
- Institut für Organische Chemie, Universität Würzburg, 97074 Würzburg, Germany
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16
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Shen R, Jiang Y, Li Z, Tian J, Li S, Li T, Chen Q. Near-Infrared Artificial Optical Synapse Based on the P(VDF-TrFE)-Coated InAs Nanowire Field-Effect Transistor. MATERIALS (BASEL, SWITZERLAND) 2022; 15:8247. [PMID: 36431733 PMCID: PMC9698720 DOI: 10.3390/ma15228247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 10/27/2022] [Accepted: 11/08/2022] [Indexed: 06/16/2023]
Abstract
Optical synapse is the basic component for optical neuromorphic computing and is attracting great attention, mainly due to its great potential in many fields, such as image recognition, artificial intelligence and artificial visual perception systems. However, optical synapse with infrared (IR) response has rarely been reported. InAs nanowires (NWs) have a direct narrow bandgap and a large surface to volume ratio, making them a promising material for IR detection. Here, we demonstrate a near-infrared (NIR) (750 to 1550 nm) optical synapse for the first time based on a poly(vinylidene fluoride-trifluoroethylene) (P(VDF-TrFE))-coated InAs NW field-effect transistor (FET). The responsivity of the P(VDF-TrFE)-coated InAs NW FET reaches 839.3 A/W under 750 nm laser illumination, demonstrating the advantage of P(VDF-TrFE) coverage. The P(VDF-TrFE)-coated InAs NW device exhibits optical synaptic behaviors in response to NIR light pulses, including excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF) and a transformation from short-term plasticity (STP) to long-term plasticity (LTP). The working mechanism is attributed to the polarization effect in the ferroelectric P(VDF-TrFE) layer, which dominates the trapping and de-trapping characteristics of photogenerated holes. These findings have significant implications for the development of artificial neural networks.
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Affiliation(s)
- Rui Shen
- Key Laboratory for the Physics and Chemistry of Nanodevices, School of Electronics, Peking University, Beijing 100871, China
| | - Yifan Jiang
- Key Laboratory for the Physics and Chemistry of Nanodevices, School of Electronics, Peking University, Beijing 100871, China
| | - Zhiwei Li
- Key Laboratory for the Physics and Chemistry of Nanodevices, School of Electronics, Peking University, Beijing 100871, China
| | - Jiamin Tian
- Key Laboratory for the Physics and Chemistry of Nanodevices, School of Electronics, Peking University, Beijing 100871, China
| | - Shuo Li
- Key Laboratory for the Physics and Chemistry of Nanodevices, School of Electronics, Peking University, Beijing 100871, China
| | - Tong Li
- Key Laboratory for the Physics and Chemistry of Nanodevices, School of Electronics, Peking University, Beijing 100871, China
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Qing Chen
- Key Laboratory for the Physics and Chemistry of Nanodevices, School of Electronics, Peking University, Beijing 100871, China
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17
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Wang W, Gao S, Wang Y, Li Y, Yue W, Niu H, Yin F, Guo Y, Shen G. Advances in Emerging Photonic Memristive and Memristive-Like Devices. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022; 9:e2105577. [PMID: 35945187 PMCID: PMC9534950 DOI: 10.1002/advs.202105577] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 06/06/2022] [Indexed: 05/19/2023]
Abstract
Possessing the merits of high efficiency, low consumption, and versatility, emerging photonic memristive and memristive-like devices exhibit an attractive future in constructing novel neuromorphic computing and miniaturized bionic electronic system. Recently, the potential of various emerging materials and structures for photonic memristive and memristive-like devices has attracted tremendous research efforts, generating various novel theories, mechanisms, and applications. Limited by the ambiguity of the mechanism and the reliability of the material, the development and commercialization of such devices are still rare and in their infancy. Therefore, a detailed and systematic review of photonic memristive and memristive-like devices is needed to further promote its development. In this review, the resistive switching mechanisms of photonic memristive and memristive-like devices are first elaborated. Then, a systematic investigation of the active materials, which induce a pivotal influence in the overall performance of photonic memristive and memristive-like devices, is highlighted and evaluated in various indicators. Finally, the recent advanced applications are summarized and discussed. In a word, it is believed that this review provides an extensive impact on many fields of photonic memristive and memristive-like devices, and lay a foundation for academic research and commercial applications.
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Affiliation(s)
- Wenxiao Wang
- School of Information Science and EngineeringShandong Provincial Key Laboratory of Network Based Intelligent ComputingUniversity of JinanJinan250022China
| | - Song Gao
- School of Information Science and EngineeringShandong Provincial Key Laboratory of Network Based Intelligent ComputingUniversity of JinanJinan250022China
| | - Yaqi Wang
- School of Information Science and EngineeringShandong Provincial Key Laboratory of Network Based Intelligent ComputingUniversity of JinanJinan250022China
| | - Yang Li
- School of Information Science and EngineeringShandong Provincial Key Laboratory of Network Based Intelligent ComputingUniversity of JinanJinan250022China
| | - Wenjing Yue
- School of Information Science and EngineeringShandong Provincial Key Laboratory of Network Based Intelligent ComputingUniversity of JinanJinan250022China
| | - Hongsen Niu
- School of Information Science and EngineeringShandong Provincial Key Laboratory of Network Based Intelligent ComputingUniversity of JinanJinan250022China
| | - Feifei Yin
- School of Information Science and EngineeringShandong Provincial Key Laboratory of Network Based Intelligent ComputingUniversity of JinanJinan250022China
| | - Yunjian Guo
- School of Information Science and EngineeringShandong Provincial Key Laboratory of Network Based Intelligent ComputingUniversity of JinanJinan250022China
| | - Guozhen Shen
- School of Integrated Circuits and ElectronicsBeijing Institute of TechnologyBeijing100081China
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18
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Shen J, Cheng Z, Zhou P. Optical and optoelectronic neuromorphic devices based on emerging memory technologies. NANOTECHNOLOGY 2022; 33:372001. [PMID: 35605580 DOI: 10.1088/1361-6528/ac723f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Accepted: 05/23/2022] [Indexed: 06/15/2023]
Abstract
As artificial intelligence continues its rapid development, inevitable challenges arise for the mainstream computing hardware to process voluminous data (Big data). The conventional computer system based on von Neumann architecture with separated processor unit and memory is approaching the limit of computational speed and energy efficiency. Thus, novel computing architectures such as in-memory computing and neuromorphic computing based on emerging memory technologies have been proposed. In recent years, light is incorporated into computational devices, beyond the data transmission in traditional optical communications, due to its innate superiority in speed, bandwidth, energy efficiency, etc. Thereinto, photo-assisted and photoelectrical synapses are developed for neuromorphic computing. Additionally, both the storage and readout processes can be implemented in optical domain in some emerging photonic devices to leverage unique properties of photonics. In this review, we introduce typical photonic neuromorphic devices rooted from emerging memory technologies together with corresponding operational mechanisms. In the end, the advantages and limitations of these devices originated from different modulation means are listed and discussed.
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Affiliation(s)
- Jiabin Shen
- State Key Laboratory of ASIC and Systems, School of Microelectronics, Fudan University, Shanghai 200433, People's Republic of China
- Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 201210, People's Republic of China
| | - Zengguang Cheng
- State Key Laboratory of ASIC and Systems, School of Microelectronics, Fudan University, Shanghai 200433, People's Republic of China
- Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 201210, People's Republic of China
| | - Peng Zhou
- State Key Laboratory of ASIC and Systems, School of Microelectronics, Fudan University, Shanghai 200433, People's Republic of China
- Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 201210, People's Republic of China
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19
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Kumar M, Kim U, Lee W, Seo H. Ultrahigh-Speed In-Memory Electronics Enabled by Proximity-Oxidation-Evolved Metal Oxide Redox Transistors. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2022; 34:e2200122. [PMID: 35288987 DOI: 10.1002/adma.202200122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 03/02/2022] [Indexed: 06/14/2023]
Abstract
The pursuit of a universal device that combines nonvolatile multilevel storage, ultrafast writing/erasing speed, nondestructive readout, and embedded processing with low power consumption demands the development of innovative architectures. Although thin-film transistors and redox-based resistive-switching devices have independently been proven to be ideal building blocks for data processing and storage, it is still difficult to achieve both well-controlled multilevel memory and high-precision ultrafast processing in a single unit, even though this is essential for the large-scale hardware implementation of in-memory computing. In this work, an ultrafast (≈42 ns) and programable redox thin-film transistor (ReTFT) memory made of a proximity-oxidation-grown TiO2 layer is developed, which has on/off ratio of 105 , nonvolatile multilevel analog storage with a long retention time, strong durability, and high reliability. Utilizing the proof-of-concept ReTFTs, circuits capable of performing fundamental NOT, AND, and OR operations with reconfigurable logic-in-memory processing are developed. Further, on-demand signal memory-processing operations, like multi-terminal addressable memory, learning, pattern recognition, and classification, are explored for prospective application in neuromorphic hardware. This device, which operates on a fundamentally different mechanism, presents an alternate solution to the problems associated with the creation of high-performing in-memory processing technology.
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Affiliation(s)
- Mohit Kumar
- Department of Energy Systems Research, Ajou University, Suwon, 16499, Republic of Korea
- Department of Materials Science and Engineering, Ajou University, Suwon, 16499, Republic of Korea
| | - Unjeong Kim
- Department of Energy Systems Research, Ajou University, Suwon, 16499, Republic of Korea
| | - WangGon Lee
- Department of Energy Systems Research, Ajou University, Suwon, 16499, Republic of Korea
| | - Hyungtak Seo
- Department of Energy Systems Research, Ajou University, Suwon, 16499, Republic of Korea
- Department of Materials Science and Engineering, Ajou University, Suwon, 16499, Republic of Korea
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20
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Yang W, Lin Y, Inagaki S, Shimizu H, Ercan E, Hsu L, Chueh C, Higashihara T, Chen W. Low-Energy-Consumption and Electret-Free Photosynaptic Transistor Utilizing Poly(3-hexylthiophene)-Based Conjugated Block Copolymers. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022; 9:e2105190. [PMID: 35064648 PMCID: PMC8922097 DOI: 10.1002/advs.202105190] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Revised: 01/03/2022] [Indexed: 05/14/2023]
Abstract
Neuromorphic computation possesses the advantages of self-learning, highly parallel computation, and low energy consumption, and is of great promise to overcome the bottleneck of von Neumann computation. In this work, a series of poly(3-hexylthiophene) (P3HT)-based block copolymers (BCPs) with different coil segments, including polystyrene, poly(2-vinylpyridine) (P2VP), poly(2-vinylnaphthalene), and poly(butyl acrylate), are utilized in photosynaptic transistor to emulate paired-pulse facilitation, spike time/rate-dependent plasticity, short/long-term neuroplasticity, and learning-forgetting-relearning processes. P3HT serves as a carrier transport channel and a photogate, while the insulating coils with electrophilic groups are for charge trapping and preservation. Three main factors are unveiled to govern the properties of these P3HT-based BCPs: i) rigidity of the insulating coil, ii) energy levels between the constituent polymers, and iii) electrophilicity of the insulating coil. Accordingly, P3HT-b-P2VP-based photosynaptic transistor with a sought-after BCP combination demonstrates long-term memory behavior with current contrast up to 105 , short-term memory behavior with high paired-pulse facilitation ratio of 1.38, and an ultralow energy consumption of 0.56 fJ at an operating voltage of -0.0003 V. As far as it is known, this is the first work to utilize conjugated BCPs in an electret-free photosynaptic transistor showing great potential to the artificial intelligence technology.
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Affiliation(s)
- Wei‐Chen Yang
- Department of Chemical EngineeringNational Taiwan UniversityTaipei10617Taiwan
- Advanced Research Center for Green Materials Science and TechnologyNational Taiwan UniversityTaipei10617Taiwan
| | - Yan‐Cheng Lin
- Department of Chemical EngineeringNational Taiwan UniversityTaipei10617Taiwan
- Advanced Research Center for Green Materials Science and TechnologyNational Taiwan UniversityTaipei10617Taiwan
| | - Shin Inagaki
- Department of Organic Materials ScienceGraduate School of Organic Materials ScienceYamagata UniversityYonezawaYamagata992‐8510Japan
| | - Hiroya Shimizu
- Department of Organic Materials ScienceGraduate School of Organic Materials ScienceYamagata UniversityYonezawaYamagata992‐8510Japan
| | - Ender Ercan
- Department of Chemical EngineeringNational Taiwan UniversityTaipei10617Taiwan
- Advanced Research Center for Green Materials Science and TechnologyNational Taiwan UniversityTaipei10617Taiwan
| | - Li‐Che Hsu
- Advanced Research Center for Green Materials Science and TechnologyNational Taiwan UniversityTaipei10617Taiwan
- Institute of Polymer Science and EngineeringNational Taiwan UniversityTaipei10617Taiwan
| | - Chu‐Chen Chueh
- Department of Chemical EngineeringNational Taiwan UniversityTaipei10617Taiwan
- Advanced Research Center for Green Materials Science and TechnologyNational Taiwan UniversityTaipei10617Taiwan
| | - Tomoya Higashihara
- Department of Organic Materials ScienceGraduate School of Organic Materials ScienceYamagata UniversityYonezawaYamagata992‐8510Japan
| | - Wen‐Chang Chen
- Department of Chemical EngineeringNational Taiwan UniversityTaipei10617Taiwan
- Advanced Research Center for Green Materials Science and TechnologyNational Taiwan UniversityTaipei10617Taiwan
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21
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Kwon KC, Baek JH, Hong K, Kim SY, Jang HW. Memristive Devices Based on Two-Dimensional Transition Metal Chalcogenides for Neuromorphic Computing. NANO-MICRO LETTERS 2022; 14:58. [PMID: 35122527 PMCID: PMC8818077 DOI: 10.1007/s40820-021-00784-3] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 12/03/2021] [Indexed: 05/21/2023]
Abstract
Two-dimensional (2D) transition metal chalcogenides (TMC) and their heterostructures are appealing as building blocks in a wide range of electronic and optoelectronic devices, particularly futuristic memristive and synaptic devices for brain-inspired neuromorphic computing systems. The distinct properties such as high durability, electrical and optical tunability, clean surface, flexibility, and LEGO-staking capability enable simple fabrication with high integration density, energy-efficient operation, and high scalability. This review provides a thorough examination of high-performance memristors based on 2D TMCs for neuromorphic computing applications, including the promise of 2D TMC materials and heterostructures, as well as the state-of-the-art demonstration of memristive devices. The challenges and future prospects for the development of these emerging materials and devices are also discussed. The purpose of this review is to provide an outlook on the fabrication and characterization of neuromorphic memristors based on 2D TMCs.
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Affiliation(s)
- Ki Chang Kwon
- Department of Materials Science and Engineering, Research Institute of Advanced Materials, Seoul National University, Seoul, 08826 Republic of Korea
- Interdisciplinary Materials Measurement Institute, Korea Research Institute of Standards and Science (KRISS), Daejeon, 34133 Republic of Korea
| | - Ji Hyun Baek
- Department of Materials Science and Engineering, Research Institute of Advanced Materials, Seoul National University, Seoul, 08826 Republic of Korea
| | - Kootak Hong
- Department of Materials Science and Engineering, Research Institute of Advanced Materials, Seoul National University, Seoul, 08826 Republic of Korea
| | - Soo Young Kim
- Department of Materials Science and Engineering, Institute of Green Manufacturing Technology, Korea University, Seoul, 02841 Republic of Korea
| | - Ho Won Jang
- Department of Materials Science and Engineering, Research Institute of Advanced Materials, Seoul National University, Seoul, 08826 Republic of Korea
- Advanced Institute of Convergence Technology, Seoul National University, Suwon, 16229 Korea
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22
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Meng J, Wang T, Zhu H, Ji L, Bao W, Zhou P, Chen L, Sun QQ, Zhang DW. Integrated In-Sensor Computing Optoelectronic Device for Environment-Adaptable Artificial Retina Perception Application. NANO LETTERS 2022; 22:81-89. [PMID: 34962129 DOI: 10.1021/acs.nanolett.1c03240] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
With the development and application of artificial intelligence, there is an appeal to the exploitation of various sensors and memories. As the most important perception of human beings, vision occupies more than 80% of all the received information. Inspired by biological eyes, an artificial retina based on 2D Janus MoSSe was fabricated, which could simulate functions of visual perception with electronic/ion and optical comodulation. Furthermore, inspired by human brain, sensing, memory, and neuromorphic computing functions were integrated on one device for multifunctional intelligent electronics, which was beneficial for scalability and high efficiency. Through the formation of faradic electric double layer (EDL) at the metal-oxide/electrolyte interfaces could realize synaptic weight changes. On the basis of the optoelectronic performances, light adaptation of biological eyes, preprocessing, and recognition of handwritten digits were implemented successfully. This work may provide a strategy for the future integrated sensing-memory-processing device for optoelectronic artificial retina perception application.
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Affiliation(s)
- Jialin Meng
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
| | - Tianyu Wang
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
| | - Hao Zhu
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
- National Integrated Circuit Innovation Center, No. 825 Zhangheng Road, Shanghai 201203, China
| | - Li Ji
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
- National Integrated Circuit Innovation Center, No. 825 Zhangheng Road, Shanghai 201203, China
| | - Wenzhong Bao
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
| | - Peng Zhou
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
- National Integrated Circuit Innovation Center, No. 825 Zhangheng Road, Shanghai 201203, China
| | - Lin Chen
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
- National Integrated Circuit Innovation Center, No. 825 Zhangheng Road, Shanghai 201203, China
| | - Qing-Qing Sun
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
- National Integrated Circuit Innovation Center, No. 825 Zhangheng Road, Shanghai 201203, China
| | - David Wei Zhang
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
- National Integrated Circuit Innovation Center, No. 825 Zhangheng Road, Shanghai 201203, China
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23
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Minohara M, Asanuma S, Asai H, Dobashi Y, Samizo A, Tezuka Y, Ozawa K, Mase K, Hase I, Kikuchi N, Aiura Y. Elaboration of near‐valence band defect states leading deterioration of ambipolar operation in SnO thin‐film transistors. NANO SELECT 2021. [DOI: 10.1002/nano.202100272] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Affiliation(s)
- Makoto Minohara
- Research Institute for Advanced Electronics and Photonics National Institute of Advanced Industrial Science and Technology (AIST) Tsukuba Ibaraki Japan
| | - Shutaro Asanuma
- Device Technology Research Institute National Institute of Advanced Industrial Science and Technology (AIST) Tsukuba Ibaraki Japan
| | - Hidehiro Asai
- Device Technology Research Institute National Institute of Advanced Industrial Science and Technology (AIST) Tsukuba Ibaraki Japan
| | - Yuka Dobashi
- Department of Materials Science and Technology Tokyo University of Science Katsushika Tokyo Japan
| | - Akane Samizo
- Department of Materials Science and Technology Tokyo University of Science Katsushika Tokyo Japan
| | - Yasuhisa Tezuka
- Graduate School of Science and Technology Hirosaki University Hirosaki Aomori Japan
| | - Kenichi Ozawa
- Department of Chemistry Tokyo Institute of Technology Meguro Tokyo Japan
- Institute of Materials Structure Science High Energy Accelerator Research Organization (KEK) Tsukuba Ibaraki Japan
| | - Kazuhiko Mase
- Institute of Materials Structure Science High Energy Accelerator Research Organization (KEK) Tsukuba Ibaraki Japan
- Department of Materials Structure Science SOKENDAI (The Graduate University for Advanced Studies) Tsukuba Ibaraki Japan
| | - Izumi Hase
- Research Institute for Advanced Electronics and Photonics National Institute of Advanced Industrial Science and Technology (AIST) Tsukuba Ibaraki Japan
| | - Naoto Kikuchi
- Research Institute for Advanced Electronics and Photonics National Institute of Advanced Industrial Science and Technology (AIST) Tsukuba Ibaraki Japan
| | - Yoshihiro Aiura
- Research Institute for Advanced Electronics and Photonics National Institute of Advanced Industrial Science and Technology (AIST) Tsukuba Ibaraki Japan
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24
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Huang X, Guo Y, Liu Y. Perovskite photodetectors and their application in artificial photonic synapses. Chem Commun (Camb) 2021; 57:11429-11442. [PMID: 34642713 DOI: 10.1039/d1cc04447h] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Organic-inorganic hybrid perovskites exhibit superior optoelectrical properties and have been widely used in photodetectors. Perovskite photodetectors with excellent detectivity have great potential for developing artificial photonic synapses which can merge data transmission and storage. They are highly desired for next generation neuromorphic computing. The recent progress of perovskite photodetectors and their application in artificial photonic synapses are summarized in this review. Firstly, the key performance parameters of photodetectors are briefly introduced. Secondly, the recent research progress of photodetectors including photoconductors, photodiodes, and phototransistors is summarized. Finally, the applications of perovskite photodetectors in artificial photonic synapses in recent years are highlighted. All these demonstrate the great potential of perovskite photonic synapses for the development of artificial intelligence.
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Affiliation(s)
- Xin Huang
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Organic Solids, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, P. R. China.
| | - Yunlong Guo
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Organic Solids, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, P. R. China.
| | - Yunqi Liu
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Organic Solids, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, P. R. China.
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25
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Bian H, Goh YY, Liu Y, Ling H, Xie L, Liu X. Stimuli-Responsive Memristive Materials for Artificial Synapses and Neuromorphic Computing. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2021; 33:e2006469. [PMID: 33837601 DOI: 10.1002/adma.202006469] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Revised: 12/03/2020] [Indexed: 06/12/2023]
Abstract
Neuromorphic computing holds promise for building next-generation intelligent systems in a more energy-efficient way than the conventional von Neumann computing architecture. Memristive hardware, which mimics biological neurons and synapses, offers high-speed operation and low power consumption, enabling energy- and area-efficient, brain-inspired computing. Here, recent advances in memristive materials and strategies that emulate synaptic functions for neuromorphic computing are highlighted. The working principles and characteristics of biological neurons and synapses, which can be mimicked by memristive devices, are presented. Besides device structures and operation with different external stimuli such as electric, magnetic, and optical fields, how memristive materials with a rich variety of underlying physical mechanisms can allow fast, reliable, and low-power neuromorphic applications is also discussed. Finally, device requirements are examined and a perspective on challenges in developing memristive materials for device engineering and computing science is given.
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Affiliation(s)
- Hongyu Bian
- Department of Chemistry, National University of Singapore, Singapore, 117543, Singapore
| | - Yi Yiing Goh
- Department of Chemistry, National University of Singapore, Singapore, 117543, Singapore
- NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore, 119077, Singapore
| | - Yuxia Liu
- Department of Chemistry, National University of Singapore, Singapore, 117543, Singapore
- Center for Functional Materials, National University of Singapore Suzhou Research Institute, Suzhou, 215123, China
| | - Haifeng Ling
- Key Laboratory for Organic Electronics and Information Displays and Institute of Advanced Materials (IAM), Jiangsu National Synergetic Innovation Center for Advanced Materials (SICAM), Nanjing University of Posts and Telecommunications, Nanjing, 210023, China
| | - Linghai Xie
- Key Laboratory for Organic Electronics and Information Displays and Institute of Advanced Materials (IAM), Jiangsu National Synergetic Innovation Center for Advanced Materials (SICAM), Nanjing University of Posts and Telecommunications, Nanjing, 210023, China
| | - Xiaogang Liu
- Department of Chemistry, National University of Singapore, Singapore, 117543, Singapore
- Center for Functional Materials, National University of Singapore Suzhou Research Institute, Suzhou, 215123, China
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26
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Kumar M, Park JY, Seo H. An Artificial Mechano-Nociceptor with Mott Transition. SMALL METHODS 2021; 5:e2100566. [PMID: 34927926 DOI: 10.1002/smtd.202100566] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/29/2021] [Revised: 08/18/2021] [Indexed: 06/14/2023]
Abstract
Intelligent touch sensing is now becoming an essential part of various human-machine interactions and communication, including in touchpads, autonomous vehicles, and smart robotics. Usually, sensing of physical objects is enabled by applied force/pressure sensors; however, reported conventional tactile devices are not able to differentiate sharp and blunt objects, although sharp objects can cause unavoidable damage. Therefore, it is central issue to implement electronic devices that can classify sense of touch and simultaneously generate pain signals to avoid further potential damage from sharp objects. Here, concept of force-enabled nociceptive behavior is proposed and demonstrated using vanadium oxide-based artificial receptors. Specifically, versatile criteria of bio-nociceptor like threshold, relaxation, no adaptation, allodynia, and hyperalgesia behaviors are triggered by pointed force, but the device does not mimic any of these by the force applied by blunt objects; thus, the proposed device classifies the intent of touch. Further, supported by finite element simulation, the nanoscale dynamic is unambiguously revealed by conductive atomic force microscopy and results are attributed to the point force-triggered Mott transition, as also confirmed by temperature-dependent measurements. The reported features open a new avenue for developing mechano-nociceptors, which enable a high-level of artificial intelligence within the device to classify physical touch.
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Affiliation(s)
- Mohit Kumar
- Department of Energy Systems Research, Ajou University, Suwon, 16499, Republic of Korea
- Department of Materials Science and Engineering, Ajou University, Suwon, 16499, Republic of Korea
| | - Ji-Yong Park
- Department of Energy Systems Research, Ajou University, Suwon, 16499, Republic of Korea
- Department of Physics, Ajou University, Suwon, 16499, Republic of Korea
| | - Hyungtak Seo
- Department of Energy Systems Research, Ajou University, Suwon, 16499, Republic of Korea
- Department of Materials Science and Engineering, Ajou University, Suwon, 16499, Republic of Korea
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27
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Abnavi A, Ahmadi R, Hasani A, Fawzy M, Mohammadzadeh MR, De Silva T, Yu N, Adachi MM. Free-Standing Multilayer Molybdenum Disulfide Memristor for Brain-Inspired Neuromorphic Applications. ACS APPLIED MATERIALS & INTERFACES 2021; 13:45843-45853. [PMID: 34542262 DOI: 10.1021/acsami.1c11359] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Recently, atomically thin two-dimensional (2D) transition-metal dichalcogenides (TMDs) have attracted great interest in electronic and opto-electronic devices for high-integration-density applications such as data storage due to their small vertical dimension and high data storage capability. Here, we report a memristor based on free-standing multilayer molybdenum disulfide (MoS2) with a high current on/off ratio of ∼103 and a stable retention for at least 3000 s. Through light modulation of the carrier density in the suspended MoS2 channel, the on/off ratio can be further increased to ∼105. Moreover, the essential photosynaptic functions with short- and long-term memory (STM and LTM) behaviors are successfully mimicked by such devices. These results also indicate that STM can be transferred to LTM by increasing the light stimuli power, pulse duration, and number of pulses. The electrical measurements performed under vacuum and ambient air conditions propose that the observed resistive switching is due to adsorbed oxygen and water molecules on both sides of the MoS2 channel. Thus, our free-standing 2D multilayer MoS2-based memristors propose a simple approach for fabrication of a low-power-consumption and reliable resistive switching device for neuromorphic applications.
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Affiliation(s)
- Amin Abnavi
- School of Engineering Science, Simon Fraser University, Burnaby V5A 1S6, British Columbia, Canada
| | - Ribwar Ahmadi
- School of Engineering Science, Simon Fraser University, Burnaby V5A 1S6, British Columbia, Canada
| | - Amirhossein Hasani
- School of Engineering Science, Simon Fraser University, Burnaby V5A 1S6, British Columbia, Canada
| | - Mirette Fawzy
- Department of Physics, Simon Fraser University, Burnaby V5A 1S6, British Columbia, Canada
| | | | - Thushani De Silva
- School of Engineering Science, Simon Fraser University, Burnaby V5A 1S6, British Columbia, Canada
| | - Niannian Yu
- School of Science, Wuhan University of Technology, Wuhan 430070, China
| | - Michael M Adachi
- School of Engineering Science, Simon Fraser University, Burnaby V5A 1S6, British Columbia, Canada
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28
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Wang R, Chen P, Hao D, Zhang J, Shi Q, Liu D, Li L, Xiong L, Zhou J, Huang J. Artificial Synapses Based on Lead-Free Perovskite Floating-Gate Organic Field-Effect Transistors for Supervised and Unsupervised Learning. ACS APPLIED MATERIALS & INTERFACES 2021; 13:43144-43154. [PMID: 34470204 DOI: 10.1021/acsami.1c08424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Synaptic devices are expected to overcome von Neumann's bottleneck and served as one of the foundations for future neuromorphic computing. Lead halide perovskites are considered as promising photoactive materials but limited by the toxicity of lead. Herein, lead-free perovskite CsBi3I10 is utilized as a photoactive material to fabricate organic synaptic transistors with a floating-gate structure for the first time. The devices can maintain the Ilight/Idark ratio of 103 for 4 h and have excellent stability within the 30 days test even without encapsulation. Synaptic functions are successfully simulated. Notably, by combining the decent charge transport property of the organic semiconductor and the excellent photoelectronic property of CsBi3I10, synaptic performance can be realized even with an operating voltage as low as -0.01 V, which is rare among floating-gate synaptic transistors. Furthermore, artificial neural networks are constructed. We propose a new method that can simulate the synaptic weight value in multiple digit form to achieve complete gradient descent. The image recognition test exhibits thrilling recognition accuracy for both supervised (91%) and unsupervised (81%) classifications. These results demonstrate the great potential of floating-gate organic synaptic transistors in neuromorphic computing.
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Affiliation(s)
- Ruizhi Wang
- Interdisciplinary Materials Research Center, School of Materials Science and Engineering, Shanghai Institute of Intelligent Science and Technology, Tongji University, Shanghai 201804, P. R. China
| | - Pengyue Chen
- School of Electronic and Information Engineering, Tongji University, Shanghai 201804, P. R. China
| | - Dandan Hao
- Interdisciplinary Materials Research Center, School of Materials Science and Engineering, Shanghai Institute of Intelligent Science and Technology, Tongji University, Shanghai 201804, P. R. China
| | - Junyao Zhang
- Interdisciplinary Materials Research Center, School of Materials Science and Engineering, Shanghai Institute of Intelligent Science and Technology, Tongji University, Shanghai 201804, P. R. China
| | - Qianqian Shi
- Interdisciplinary Materials Research Center, School of Materials Science and Engineering, Shanghai Institute of Intelligent Science and Technology, Tongji University, Shanghai 201804, P. R. China
| | - Dapeng Liu
- Interdisciplinary Materials Research Center, School of Materials Science and Engineering, Shanghai Institute of Intelligent Science and Technology, Tongji University, Shanghai 201804, P. R. China
| | - Li Li
- Interdisciplinary Materials Research Center, School of Materials Science and Engineering, Shanghai Institute of Intelligent Science and Technology, Tongji University, Shanghai 201804, P. R. China
| | - Lize Xiong
- Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Fourth People's Hospital Affiliated to Tongji University, Shanghai 200434, P. R. China
| | - Junhe Zhou
- School of Electronic and Information Engineering, Tongji University, Shanghai 201804, P. R. China
| | - Jia Huang
- Interdisciplinary Materials Research Center, School of Materials Science and Engineering, Shanghai Institute of Intelligent Science and Technology, Tongji University, Shanghai 201804, P. R. China
- Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Fourth People's Hospital Affiliated to Tongji University, Shanghai 200434, P. R. China
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29
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Fu W, Li J, Li L, Jiang D, Zhu W, Zhang J. High ionic conductivity Li 0.33La 0.557TiO 3nanofiber/polymer composite solid electrolyte for flexible transparent InZnO synaptic transistors. NANOTECHNOLOGY 2021; 32:405207. [PMID: 34225267 DOI: 10.1088/1361-6528/ac1132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 07/05/2021] [Indexed: 06/13/2023]
Abstract
With the rapid development of wearable artificial intelligence devices, there is an increasing demand for flexible oxide neuromorphic transistors with the solid electrolytes. To achieve high-performance flexible synaptic transistors, the solid electrolytes should exhibit good mechanical bending characteristics and high ion conductivity. However, the polymer-based electrolytes with good mechanical bending characteristics show poor ion conductivity (10-6-10-7S cm-1), which limits the performance of flexible synaptic transistors. Thus, it is urgent to improve the ion conductivity of the polymer-based electrolytes. In the work, a new strategy of electrospun Li0.33La0.557TiO3nanofibers-enhanced ion transport pathway is proposed to simultaneously improve the mechanical bending and ion conductivity of polyethylene oxide/polyvinylpyrrolidone-based solid electrolytes. The flexible InZnO synaptic transistors with Li0.33La0.557TiO3nanofibers-based solid electrolytes successfully simulated excitatory post-synaptic current, paired-pulse-facilitation, dynamic time filter, nonlinear summation, two-terminal input dynamic integration and logic function. This work is a useful attempt to develop high-performance synaptic transistors.
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Affiliation(s)
- Wenhui Fu
- School of Material Science and Engineering, Shanghai University, Jiading, Shanghai 201800, People's Republic of China
| | - Jun Li
- School of Material Science and Engineering, Shanghai University, Jiading, Shanghai 201800, People's Republic of China
- Key Laboratory of Advanced Display and System Applications, Ministry of Education, Shanghai University, Shanghai 200072, People's Republic of China
| | - Linkang Li
- School of Material Science and Engineering, Shanghai University, Jiading, Shanghai 201800, People's Republic of China
| | - Dongliang Jiang
- School of Material Science and Engineering, Shanghai University, Jiading, Shanghai 201800, People's Republic of China
| | - Wenqing Zhu
- School of Material Science and Engineering, Shanghai University, Jiading, Shanghai 201800, People's Republic of China
| | - Jianhua Zhang
- Key Laboratory of Advanced Display and System Applications, Ministry of Education, Shanghai University, Shanghai 200072, People's Republic of China
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30
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Liu L, Cheng Z, Jiang B, Liu Y, Zhang Y, Yang F, Wang J, Yu XF, Chu PK, Ye C. Optoelectronic Artificial Synapses Based on Two-Dimensional Transitional-Metal Trichalcogenide. ACS APPLIED MATERIALS & INTERFACES 2021; 13:30797-30805. [PMID: 34169714 DOI: 10.1021/acsami.1c03202] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
The memristor is a foundational device for an artificial synapse, which is essential to realize next-generation neuromorphic computing. Herein, an optoelectronic memristor based on a two-dimensional (2D) transitional-metal trichalcogenide (TMTC) is designed and demonstrated. Owing to the excellent optical and electrical characteristics of titanium trisulfide (TiS3), the memristor exhibits stable bipolar resistance switching (RS) as a result of the controllable formation and rupturing of the conductive aluminum filaments. Multilevel storage is realized with light of multiple wavelengths between 400 and 808 nm, and the synaptic properties such as conduction modulation and spiking timing-dependent plasticity (STDP) are achieved. On the basis of the photonic potentiation and electrical habitual ability, Pavlovian-associative learning is successfully established on this TiS3-based artificial synapse. All these results reveal the large potential of 2D TMTCs in artificial neuromorphic chips.
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Affiliation(s)
- Lei Liu
- Faculty of Physics and Electronic Science, Hubei Key Laboratory of Ferro- & Piezoelectric Materials and Devices, Hubei University, Wuhan 430062, P.R. China
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, P.R. China
| | - Ziqiang Cheng
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, P.R. China
- Department of Applied Physics, East China Jiaotong University, Nanchang 330013, P.R. China
| | - Bei Jiang
- Faculty of Physics and Electronic Science, Hubei Key Laboratory of Ferro- & Piezoelectric Materials and Devices, Hubei University, Wuhan 430062, P.R. China
| | - Yanxin Liu
- Faculty of Physics and Electronic Science, Hubei Key Laboratory of Ferro- & Piezoelectric Materials and Devices, Hubei University, Wuhan 430062, P.R. China
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, P.R. China
| | - Yanli Zhang
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, P.R. China
| | - Fan Yang
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, P.R. China
| | - Jiahong Wang
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, P.R. China
| | - Xue-Feng Yu
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, P.R. China
| | - Paul K Chu
- Department of Physics, Department of Materials Science and Engineering, and Department of Biomedical Engineering, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong 999077, P.R. China
| | - Cong Ye
- Faculty of Physics and Electronic Science, Hubei Key Laboratory of Ferro- & Piezoelectric Materials and Devices, Hubei University, Wuhan 430062, P.R. China
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Duan H, Liang L, Wu Z, Zhang H, Huang L, Cao H. IGZO/CsPbBr 3-Nanoparticles/IGZO Neuromorphic Phototransistors and Their Optoelectronic Coupling Applications. ACS APPLIED MATERIALS & INTERFACES 2021; 13:30165-30173. [PMID: 34143597 DOI: 10.1021/acsami.1c05396] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Optoelectronic synaptic devices are of great scientific and practical importance because of various potential applications such as ocular simulating and optical-electrical managers based on a new optoelectronic coupling mechanism. In this work, we design a novel channel layer with p-type CsPbBr3 nanoparticles (NPs) buried in an InGaZnO (IGZO) film to construct the corresponding thin-film transistors (TFTs), which exhibits intense improvement in visible-light photosensitivity and synaptic plasticity as compared to the pure IGZO counterpart. Specifically, the composite device is able to exhibit versatile synaptic behavior under light stimuli with density as low as 0.12 μW/cm2 and with the gain 5-20 times higher than that of the IGZO TFT in the visible-light region. Based on the band alignment between the IGZO and NPs, the excitation and decay processes of intrinsic and photoinduced carriers are discussed. Moreover, owing to the gate bias control in a three-terminal configuration, our TFT synapses can imitate complex biological behaviors including the famous "Pavlov's dog" experiment and the "reward and punishment mechanism" of the brain via editing the gate voltage/light pulse stimuli.
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Affiliation(s)
- Hongxiao Duan
- Laboratory of Advanced Nano Materials and Devices, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, China
| | - Lingyan Liang
- Laboratory of Advanced Nano Materials and Devices, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, China
- Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Zhendong Wu
- Laboratory of Advanced Nano Materials and Devices, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, China
- Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Hengbo Zhang
- Laboratory of Advanced Nano Materials and Devices, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, China
- Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Lu Huang
- School of Materials Science and Engineering, Shanghai University, Baoshan District, Shanghai 200444, China
| | - Hongtao Cao
- Laboratory of Advanced Nano Materials and Devices, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, China
- Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
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Sun F, Lu Q, Feng S, Zhang T. Flexible Artificial Sensory Systems Based on Neuromorphic Devices. ACS NANO 2021; 15:3875-3899. [PMID: 33507725 DOI: 10.1021/acsnano.0c10049] [Citation(s) in RCA: 51] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/23/2023]
Abstract
Emerging flexible artificial sensory systems using neuromorphic electronics have been considered as a promising solution for processing massive data with low power consumption. The construction of artificial sensory systems with synaptic devices and sensing elements to mimic complicated sensing and processing in biological systems is a prerequisite for the realization. To realize high-efficiency neuromorphic sensory systems, the development of artificial flexible synapses with low power consumption and high-density integration is essential. Furthermore, the realization of efficient coupling between the sensing element and the synaptic device is crucial. This Review presents recent progress in the area of neuromorphic electronics for flexible artificial sensory systems. We focus on both the recent advances of artificial synapses, including device structures, mechanisms, and functions, and the design of intelligent, flexible perception systems based on synaptic devices. Additionally, key challenges and opportunities related to flexible artificial perception systems are examined, and potential solutions and suggestions are provided.
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Affiliation(s)
- Fuqin Sun
- i -Lab, Key Laboratory of Multifunctional Nanomaterials and Smart Systems, Suzhou Institute of Nano-Tech and Nano-Bionics (SINANO), Chinese Academy of Sciences (CAS), 398 Ruoshui Road, Suzhou 215123, P. R. China
- School of Nano Technology and Nano Bionics, University of Science and Technology of China, 96 Jinzhai Road, Hefei, Anhui 230026, P. R. China
| | - Qifeng Lu
- i -Lab, Key Laboratory of Multifunctional Nanomaterials and Smart Systems, Suzhou Institute of Nano-Tech and Nano-Bionics (SINANO), Chinese Academy of Sciences (CAS), 398 Ruoshui Road, Suzhou 215123, P. R. China
| | - Simin Feng
- i -Lab, Key Laboratory of Multifunctional Nanomaterials and Smart Systems, Suzhou Institute of Nano-Tech and Nano-Bionics (SINANO), Chinese Academy of Sciences (CAS), 398 Ruoshui Road, Suzhou 215123, P. R. China
| | - Ting Zhang
- i -Lab, Key Laboratory of Multifunctional Nanomaterials and Smart Systems, Suzhou Institute of Nano-Tech and Nano-Bionics (SINANO), Chinese Academy of Sciences (CAS), 398 Ruoshui Road, Suzhou 215123, P. R. China
- School of Nano Technology and Nano Bionics, University of Science and Technology of China, 96 Jinzhai Road, Hefei, Anhui 230026, P. R. China
- Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
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Huang W, Xia X, Zhu C, Steichen P, Quan W, Mao W, Yang J, Chu L, Li X. Memristive Artificial Synapses for Neuromorphic Computing. NANO-MICRO LETTERS 2021; 13:85. [PMID: 34138298 PMCID: PMC8006524 DOI: 10.1007/s40820-021-00618-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Accepted: 01/29/2021] [Indexed: 05/06/2023]
Abstract
Neuromorphic computing simulates the operation of biological brain function for information processing and can potentially solve the bottleneck of the von Neumann architecture. This computing is realized based on memristive hardware neural networks in which synaptic devices that mimic biological synapses of the brain are the primary units. Mimicking synaptic functions with these devices is critical in neuromorphic systems. In the last decade, electrical and optical signals have been incorporated into the synaptic devices and promoted the simulation of various synaptic functions. In this review, these devices are discussed by categorizing them into electrically stimulated, optically stimulated, and photoelectric synergetic synaptic devices based on stimulation of electrical and optical signals. The working mechanisms of the devices are analyzed in detail. This is followed by a discussion of the progress in mimicking synaptic functions. In addition, existing application scenarios of various synaptic devices are outlined. Furthermore, the performances and future development of the synaptic devices that could be significant for building efficient neuromorphic systems are prospected.
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Affiliation(s)
- Wen Huang
- New Energy Technology Engineering Laboratory of Jiangsu Province and School of Science, Nanjing University of Posts and Telecommunications (NJUPT), Nanjing, 210023, People's Republic of China.
| | - Xuwen Xia
- New Energy Technology Engineering Laboratory of Jiangsu Province and School of Science, Nanjing University of Posts and Telecommunications (NJUPT), Nanjing, 210023, People's Republic of China
| | - Chen Zhu
- College of Electronic and Optical Engineering and College of Microelectronics, Nanjing University of Posts and Telecommunications (NJUPT), Nanjing, 210023, People's Republic of China
| | - Parker Steichen
- Department of Materials Science and Engineering, University of Washington, Seattle, WA, 98195-2120, USA
| | - Weidong Quan
- New Energy Technology Engineering Laboratory of Jiangsu Province and School of Science, Nanjing University of Posts and Telecommunications (NJUPT), Nanjing, 210023, People's Republic of China
| | - Weiwei Mao
- New Energy Technology Engineering Laboratory of Jiangsu Province and School of Science, Nanjing University of Posts and Telecommunications (NJUPT), Nanjing, 210023, People's Republic of China
| | - Jianping Yang
- New Energy Technology Engineering Laboratory of Jiangsu Province and School of Science, Nanjing University of Posts and Telecommunications (NJUPT), Nanjing, 210023, People's Republic of China
| | - Liang Chu
- New Energy Technology Engineering Laboratory of Jiangsu Province and School of Science, Nanjing University of Posts and Telecommunications (NJUPT), Nanjing, 210023, People's Republic of China.
| | - Xing'ao Li
- New Energy Technology Engineering Laboratory of Jiangsu Province and School of Science, Nanjing University of Posts and Telecommunications (NJUPT), Nanjing, 210023, People's Republic of China.
- Key Laboratory for Organic Electronics and Information Displays and Institute of Advanced Materials, Jiangsu National Synergistic Innovation Center for Advanced Materials, School of Materials Science and Engineering, Nanjing University of Posts and Telecommunications (NUPT), 9 Wenyuan Road, Nanjing, 210023, People's Republic of China.
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Li KH, Kang CH, Min JH, Alfaraj N, Liang JW, Braic L, Guo Z, Hedhili MN, Ng TK, Ooi BS. Single-Crystalline All-Oxide α-γ-β Heterostructures for Deep-Ultraviolet Photodetection. ACS APPLIED MATERIALS & INTERFACES 2020; 12:53932-53941. [PMID: 33203211 DOI: 10.1021/acsami.0c15398] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Recent advancements in gallium oxide (Ga2O3)-based heterostructures have allowed optoelectronic devices to be used extensively in the fields of power electronics and deep-ultraviolet photodetection. While most previous research has involved realizing single-crystalline Ga2O3 layers on native substrates for high conductivity and visible-light transparency, presented and investigated herein is a single-crystalline β-Ga2O3 layer grown on an α-Al2O3 substrate through an interfacial γ-In2O3 layer. The single-crystalline transparent conductive oxide layer made of wafer-scalable γ-In2O3 provides high carrier transport, visible-light transparency, and antioxidation properties that are critical for realizing vertically oriented heterostructures for transparent oxide photonic platforms. Physical characterization based on X-ray diffraction and high-resolution transmission electron microscopy imaging confirms the single-crystalline nature of the grown films and the crystallographic orientation relationships among the monoclinic β-Ga2O3, cubic γ-In2O3, and trigonal α-Al2O3, while the elemental composition and sharp interfaces across the heterostructure are confirmed by Rutherford backscattering spectrometry. Furthermore, the energy-band offsets are determined by X-ray photoelectron spectroscopy at the β-Ga2O3/γ-In2O3 interface, elucidating a type-II heterojunction with conduction- and valence-band offsets of 0.16 and 1.38 eV, respectively. Based on the single-crystalline β-Ga2O3/γ-In2O3/α-Al2O3 all-oxide heterostructure, a vertically oriented DUV photodetector is fabricated that exhibits a high photoresponsivity of 94.3 A/W, an external quantum efficiency of 4.6 × 104%, and a specific detectivity of 3.09 × 1012 Jones at 250 nm. The present demonstration lays a strong foundation for and paves the way to future all-oxide-based transparent photonic platforms.
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Affiliation(s)
- Kuang-Hui Li
- Photonics Laboratory, Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
| | - Chun Hong Kang
- Photonics Laboratory, Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
| | - Jung-Hong Min
- Photonics Laboratory, Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
| | - Nasir Alfaraj
- Photonics Laboratory, Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
| | - Jian-Wei Liang
- Photonics Laboratory, Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
| | - Laurentiu Braic
- Nanofabrication Core Lab, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
| | - Zaibing Guo
- Nanofabrication Core Lab, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
| | - Mohamed Nejib Hedhili
- Imaging and Characterization Core Lab, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
| | - Tien Khee Ng
- Photonics Laboratory, Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
| | - Boon S Ooi
- Photonics Laboratory, Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
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Lin TR, Shih LC, Cheng PJ, Chen KT, Chen JS. Violet-light stimulated synaptic and learning functions in a zinc-tin oxide photoelectric transistor for neuromorphic computation. RSC Adv 2020; 10:42682-42687. [PMID: 35514904 PMCID: PMC9057943 DOI: 10.1039/d0ra08777g] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Accepted: 11/09/2020] [Indexed: 11/21/2022] Open
Abstract
In contrast to the commonly present UV light-stimulated synaptic oxide thin-film transistors, this study demonstrates a violet light (wavelength of 405 nm) stimulated zinc-tin oxide (ZTO) photoelectric transistor for potential application in optical neuromorphic computation. Owing to the light-induced oxygen vacancy ionization and persistent photoconductivity effect in ZTO, this device well imitates prominent synaptic functions, including photonic potentiation, electric depression, and short-term memory (STM) to long-term memory (LTM) transition. A highly linear and broad dynamic range of photonic potentiation can be achieved by modulating the light power density, while electric depression is realized by gate voltage pulsing. In addition, the brain-like re-learning experience with extended forgetting time (200 s) is well mimicked by the ZTO photoelectric transistor. As a result, the ZTO photoelectric transistor provides excessive synaptic function with multi-series of synaptic weight levels (90 levels for each given light power density), which makes it prevalent in the neuromorphic computation of massive data as well as in learning-driven artificial intelligence computation.
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Affiliation(s)
- Ting-Ruei Lin
- Department of Materials Science and Engineering, National Cheng Kung University Tainan 70101 Taiwan
| | - Li-Chung Shih
- Department of Materials Science and Engineering, National Cheng Kung University Tainan 70101 Taiwan
| | - Po-Jen Cheng
- Department of Materials Science and Engineering, National Cheng Kung University Tainan 70101 Taiwan
| | - Kuan-Ting Chen
- Department of Materials Science and Engineering, National Cheng Kung University Tainan 70101 Taiwan
| | - Jen-Sue Chen
- Department of Materials Science and Engineering, National Cheng Kung University Tainan 70101 Taiwan
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36
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Gupta V, Lucarelli G, Castro-Hermosa S, Brown T, Ottavi M. Investigation of hysteresis in hole transport layer free metal halide perovskites cells under dark conditions. NANOTECHNOLOGY 2020; 31:445201. [PMID: 32679576 DOI: 10.1088/1361-6528/aba713] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Recent research is a testimony to the fact that perovskite material based solar cells are most efficient since they exhibit high power conversion efficiency and low cost of fabrication. Various perovskite materials display hysteresis in their current-voltage characteristic which accounts for memory behaviour. In this paper, we demonstrate efficient non-volatile memory devices based on hybrid organic-inorganic perovskite (CH3NH3PbI3) as a resistive switching layer on a Glass/Indium Tin Oxide (ITO) substrate. Our perovskite solar cells have been developed over the fully solution processed electron transport layer (ETL) which is a combination of SnO2 and mesoporous (m)-TiO2 scaffold layers. Hysteresis behaviour was observed in the current-voltage analysis achieving high ratio of ON & OFF current under dark and ambient conditions. Proposed perovskite-based Glass/ITO/SnO2/m-TiO2/CH3NH3PbI3/Au device has a hole transport layer (HTL) free structure, which is mainly responsible for a large ratio of ON & OFF current. The presence of voids in the scaffold m-TiO2 layer are also accountable for increasing electron/hole path length which escalates the recombination rate at the surface of the ETL/perovskite interface resulting in large hysteresis in the I-V curve. This memristor device operates at a low energy due to SnO2 layer's higher electron mobility and wide energy band gap. Our experimental results also show the dependency of voltage scan range & rate of scanning on the hysteresis behaviour in dark conditions. This memristive behaviour of the proposed device depicts drift in hysteresis loop with respect to the number of cycles, which would have a significant impact in neuromorphic applications. Moreover, due to the identical fabrication process of the proposed perovskite-based memristor device and perovskite solar cells, this device could be integrated inside a photovoltaic array to work as a power-on-chip device, where generation and computation could be possible on the same substrate for memory and neuromorphic applications.
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Affiliation(s)
- Vishal Gupta
- Department of Electronic Engineering, University of Rome, Tor Vergata, Roma, Italy
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37
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Kumar M, Lim J, Kim S, Seo H. Environment-Adaptable Photonic-Electronic-Coupled Neuromorphic Angular Visual System. ACS NANO 2020; 14:14108-14117. [PMID: 32985189 DOI: 10.1021/acsnano.0c06874] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
Environment-adaptable photonic-electronic-coupled devices can help overcome major challenges related to the extraction of highly specific angular information, such as human visual perception. However, a true implementation of such a device has rarely been investigated thus far. Herein, we provide an approach and demonstrate a proof-of-concept solid-state semiconductor-based highly transparent, optical-electrical-coupled, self-adaptive angular visual perception system that can fulfill the versatile criteria of the human vision system. Specifically, all of the primitive functions of visual perception, such as broad angular sensing, processing, and manifold memory storage, are demonstrated and comodulated using optical and electric pulses. This development represents an essential step forward in the fabrication of an environment-adaptable artificial angular perception framework with deep implications in the fields of optoelectronics, artificial eyes, and memory storage applications.
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Affiliation(s)
- Mohit Kumar
- Department of Materials Science and Engineering, Ajou University, Suwon 16499, Republic of Korea
| | - Jaeseong Lim
- Department of Energy Systems Research, Ajou University, Suwon 16499, Republic of Korea
| | - Sangwan Kim
- Department of Electrical and Computer Engineering, Ajou University, Suwon 16499, Republic of Korea
| | - Hyungtak Seo
- Department of Materials Science and Engineering, Ajou University, Suwon 16499, Republic of Korea
- Department of Energy Systems Research, Ajou University, Suwon 16499, Republic of Korea
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38
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Xu H, Karbalaei Akbari M, Verpoort F, Zhuiykov S. Nano-engineering and functionalization of hybrid Au-Me xO y-TiO 2 (Me = W, Ga) hetero-interfaces for optoelectronic receptors and nociceptors. NANOSCALE 2020; 12:20177-20188. [PMID: 32697233 DOI: 10.1039/d0nr02184a] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Bio-inspired nano-electronic devices are key instruments for the development of advanced artificial intelligence systems, which will shape the future of humanoid nano-robotics. An emerging demand is realized for an accurate reception of environmental stimuli via visual perception, processing and realization of optical signals. The present study demonstrates the capability of functionalized all-oxide heterostructured two-dimensional (2D) plasmonic devices for the self-adaptive recognition of visual optical pulses. Specifically, the nano-engineering of the metal/semiconductor interface and co-modulation of heterostructured 2D semiconductor hetero-interfaces of Au/WO3 : TiO2 and Au/Ga2O3 : TiO2 facilitated the receptive and nociceptive detection of visible light pulses. A decrease in the dark current of the Au/WO3 : TiO2 unit resulted in the development of sensitive visible light photoreceptors. Furthermore, the modulation of charge transfers at the Au/Ga2O3 : TiO2 hetero-interfaces were the key parameter to determine the optical reception characteristics and nociceptive performance of all-oxide optoelectronic devices. Specifically, the rapid thermal annealing (RTA) of 2D Ga2O3 in N2 atmosphere ensured the modulation of charge transfer at Au/Ga2O3 : TiO2 hetero-interfaces in plasmonic devices. Thus, hetero-interface engineering enabled the effective control of charge transfer at 2D hetero-interfaces for an adaptive perception of visible optical pulses. Consequently, the fabricated sensitive Au/Ga2O3 (N2) : TiO2 bio-inspired unit emulated the optical functionalities of corneal nociceptors.
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Affiliation(s)
- Hongyan Xu
- School of Materials Science & Engineering, North University of China, Taiyuan, 030051 Shanxi, PR China
| | - Mohammad Karbalaei Akbari
- Centre for Environmental & Energy Research, Ghent University, Global Campus, 21985, Incheon, South Korea. and Department of Solid State Sciences, Faculty of Science, Ghent University, 9000 Ghent, Belgium
| | - Francis Verpoort
- Centre for Environmental & Energy Research, Ghent University, Global Campus, 21985, Incheon, South Korea. and State Key Laboratory of Advanced Technology for Materials Synthesis & Processing, Wuhan University of Technology, Wuhan, 630070, PR China
| | - Serge Zhuiykov
- School of Materials Science & Engineering, North University of China, Taiyuan, 030051 Shanxi, PR China and Centre for Environmental & Energy Research, Ghent University, Global Campus, 21985, Incheon, South Korea. and Department of Solid State Sciences, Faculty of Science, Ghent University, 9000 Ghent, Belgium
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39
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Blachowicz T, Ehrmann A. Magnetic Elements for Neuromorphic Computing. Molecules 2020; 25:E2550. [PMID: 32486173 PMCID: PMC7321415 DOI: 10.3390/molecules25112550] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2020] [Revised: 05/18/2020] [Accepted: 05/28/2020] [Indexed: 01/02/2023] Open
Abstract
Neuromorphic computing is assumed to be significantly more energy efficient than, and at the same time expected to outperform, conventional computers in several applications, such as data classification, since it overcomes the so-called von Neumann bottleneck. Artificial synapses and neurons can be implemented into conventional hardware using new software, but also be created by diverse spintronic devices and other elements to completely avoid the disadvantages of recent hardware architecture. Here, we report on diverse approaches to implement neuromorphic functionalities in novel hardware using magnetic elements, published during the last years. Magnetic elements play an important role in neuromorphic computing. While other approaches, such as optical and conductive elements, are also under investigation in many groups, magnetic nanostructures and generally magnetic materials offer large advantages, especially in terms of data storage, but they can also unambiguously be used for data transport, e.g., by propagation of skyrmions or domain walls. This review underlines the possible applications of magnetic materials and nanostructures in neuromorphic systems.
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Affiliation(s)
- Tomasz Blachowicz
- Institute of Physics–Center for Science and Education, Silesian University of Technology, 44-100 Gliwice, Poland;
| | - Andrea Ehrmann
- Faculty of Engineering and Mathematics, Bielefeld University of Applied Sciences, 33619 Bielefeld, Germany
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Karbalaei Akbari M, Hu J, Verpoort F, Lu H, Zhuiykov S. Nanoscale All-Oxide-Heterostructured Bio-inspired Optoresponsive Nociceptor. NANO-MICRO LETTERS 2020; 12:83. [PMID: 34138106 PMCID: PMC7770938 DOI: 10.1007/s40820-020-00419-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Accepted: 03/02/2020] [Indexed: 06/01/2023]
Abstract
Retina nociceptor, as a key sensory receptor, not only enables the transport of warning signals to the human central nervous system upon its exposure to noxious stimuli, but also triggers the motor response that minimizes potential sensitization. In this study, the capability of two-dimensional all-oxide-heterostructured artificial nociceptor as a single device with tunable properties was confirmed. Newly designed nociceptors utilize ultra-thin sub-stoichiometric TiO2-Ga2O3 heterostructures, where the thermally annealed Ga2O3 films play the role of charge transfer controlling component. It is discovered that the phase transformation in Ga2O3 is accompanied by substantial jump in conductivity, induced by thermally assisted internal redox reaction of Ga2O3 nanostructure during annealing. It is also experimentally confirmed that the charge transfer in all-oxide heterostructures can be tuned and controlled by the heterointerfaces manipulation. Results demonstrate that the engineering of heterointerfaces of two-dimensional (2D) films enables the fabrication of either high-sensitive TiO2-Ga2O3 (Ar) or high-threshold TiO2-Ga2O3 (N2) nociceptors. The hypersensitive nociceptor mimics the functionalities of corneal nociceptors of human eye, whereas the delayed reaction of nociceptor is similar to high-threshold nociceptive characteristics of human sensory system. The long-term stability of 2D nociceptors demonstrates the capability of heterointerfaces engineering for effective control of charge transfer at 2D heterostructured devices.
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Affiliation(s)
- Mohammad Karbalaei Akbari
- Centre for Environmental and Energy Research, Ghent University Global Campus, Incheon, South Korea.
- Department of Green Chemistry and Technology, Faculty of Bioscience Engineering, Ghent University, 9000, Ghent, Belgium.
| | - Jie Hu
- College of Information Engineering, Taiyuan University of Technology, Taiyuan, 030024, Shanxi, People's Republic of China
| | - Francis Verpoort
- Laboratory of Organometallics, Catalysis and Ordered Materials, State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Wuhan University of Technology, Wuhan, 430070, People's Republic of China
| | - Hongliang Lu
- School of Microelectronic, Fudan University, Shanghai, 200433, People's Republic of China
| | - Serge Zhuiykov
- Centre for Environmental and Energy Research, Ghent University Global Campus, Incheon, South Korea.
- Department of Green Chemistry and Technology, Faculty of Bioscience Engineering, Ghent University, 9000, Ghent, Belgium.
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41
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Lv Z, Wang Y, Chen J, Wang J, Zhou Y, Han ST. Semiconductor Quantum Dots for Memories and Neuromorphic Computing Systems. Chem Rev 2020; 120:3941-4006. [DOI: 10.1021/acs.chemrev.9b00730] [Citation(s) in RCA: 114] [Impact Index Per Article: 28.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Ziyu Lv
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen 518060, P. R. China
| | - Yan Wang
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen 518060, P. R. China
| | - Jingrui Chen
- Institute for Advanced Study, Shenzhen University, Shenzhen 518060, P. R. China
| | - Junjie Wang
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen 518060, P. R. China
| | - Ye Zhou
- Institute for Advanced Study, Shenzhen University, Shenzhen 518060, P. R. China
| | - Su-Ting Han
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen 518060, P. R. China
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42
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Kim MK, Lee JS. Synergistic Improvement of Long-Term Plasticity in Photonic Synapses Using Ferroelectric Polarization in Hafnia-Based Oxide-Semiconductor Transistors. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2020; 32:e1907826. [PMID: 32053265 DOI: 10.1002/adma.201907826] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/28/2019] [Revised: 01/04/2020] [Indexed: 06/10/2023]
Abstract
A number of synapse devices have been intensively studied for the neuromorphic system which is the next-generation energy-efficient computing method. Among these various types of synapse devices, photonic synapse devices recently attracted significant attention. In particular, the photonic synapse devices using persistent photoconductivity (PPC) phenomena in oxide semiconductors are receiving much attention due to the similarity between relaxation characteristics of PPC phenomena and Ca2+ dynamics of biological synapses. However, these devices have limitations in its controllability of the relaxation characteristics of PPC behaviors. To utilize the oxide semiconductor as photonic synapse devices, relaxation behavior needs to be accurately controlled. In this study, a photonic synapse device with controlled relaxation characteristics by using an oxide semiconductor and a ferroelectric layer is demonstrated. This device exploits the PPC characteristics to demonstrate synaptic functions including short-term plasticity, paired-pulse facilitation (PPF), and long-term plasticity (LTP). The relaxation properties are controlled by the polarization of the ferroelectric layer, and this polarization is used to control the amount by which the conductance levels increase during PPF operation and to enhance LTP characteristics. This study provides an important step toward the development of photonic synapses with tunable synaptic functions.
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Affiliation(s)
- Min-Kyu Kim
- Department of Materials Science and Engineering, Pohang University of Science and Technology (POSTECH), Pohang, 37673, Korea
| | - Jang-Sik Lee
- Department of Materials Science and Engineering, Pohang University of Science and Technology (POSTECH), Pohang, 37673, Korea
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Passian A, Imam N. Nanosystems, Edge Computing, and the Next Generation Computing Systems. SENSORS (BASEL, SWITZERLAND) 2019; 19:E4048. [PMID: 31546907 PMCID: PMC6767340 DOI: 10.3390/s19184048] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 09/11/2019] [Accepted: 09/16/2019] [Indexed: 12/24/2022]
Abstract
It is widely recognized that nanoscience and nanotechnology and their subfields, such as nanophotonics, nanoelectronics, and nanomechanics, have had a tremendous impact on recent advances in sensing, imaging, and communication, with notable developments, including novel transistors and processor architectures. For example, in addition to being supremely fast, optical and photonic components and devices are capable of operating across multiple orders of magnitude length, power, and spectral scales, encompassing the range from macroscopic device sizes and kW energies to atomic domains and single-photon energies. The extreme versatility of the associated electromagnetic phenomena and applications, both classical and quantum, are therefore highly appealing to the rapidly evolving computing and communication realms, where innovations in both hardware and software are necessary to meet the growing speed and memory requirements. Development of all-optical components, photonic chips, interconnects, and processors will bring the speed of light, photon coherence properties, field confinement and enhancement, information-carrying capacity, and the broad spectrum of light into the high-performance computing, the internet of things, and industries related to cloud, fog, and recently edge computing. Conversely, owing to their extraordinary properties, 0D, 1D, and 2D materials are being explored as a physical basis for the next generation of logic components and processors. Carbon nanotubes, for example, have been recently used to create a new processor beyond proof of principle. These developments, in conjunction with neuromorphic and quantum computing, are envisioned to maintain the growth of computing power beyond the projected plateau for silicon technology. We survey the qualitative figures of merit of technologies of current interest for the next generation computing with an emphasis on edge computing.
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Affiliation(s)
- Ali Passian
- Computing & Computational Sciences Directorate, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA.
| | - Neena Imam
- Computing & Computational Sciences Directorate, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA.
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Kumar M, Abbas S, Lee JH, Kim J. Controllable digital resistive switching for artificial synapses and pavlovian learning algorithm. NANOSCALE 2019; 11:15596-15604. [PMID: 31403638 DOI: 10.1039/c9nr02027f] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
The fundamental unit of the nervous system is a synapse, which is involved in transmitting information between neurons as well as learning, memory, and forgetting processes. Two-terminal memristors can fulfil most of these requirements; however, their poor dynamic changes in resistance to input electric stimuli remain an obstacle, which must be improved for accurate and quick information processing. Herein, we demonstrate the synaptic properties of ZnO-based memristors, which were significantly enhanced (∼340 times) by geometrical modulation due to the localized electric field enhancement. Specifically, by inserting Ag-nanowires and Ag-dots into the ZnO/Si interface, the resistive switching could be controlled from a digital to analog mode. A finite element simulation revealed that the presence of Ag could enhance the localized electric field, which in turn improved the migration of ionic species. Further, the device showed a variety of comprehensive synaptic functions, for instance, paired-pulse facilitation and transformation from short-term plasticity to long-term plasticity, including the Pavlovian associative learning process in a human brain. Our study presents a novel architecture to enhance the synaptic sensitivity, and its uses in practical applications, including the artificial learning algorithm.
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Affiliation(s)
- Mohit Kumar
- Photoelectric and Energy Device Application Lab (PEDAL), Multidisciplinary Core Institute for Future Energies (MCIFE), Incheon, 22012, Republic of Korea and Department of Electrical Engineering, Incheon National University, 119 Academy Rd. Yeonsu, Incheon, 22012, Republic of Korea.
| | - Sohail Abbas
- Photoelectric and Energy Device Application Lab (PEDAL), Multidisciplinary Core Institute for Future Energies (MCIFE), Incheon, 22012, Republic of Korea and Department of Electrical Engineering, Incheon National University, 119 Academy Rd. Yeonsu, Incheon, 22012, Republic of Korea.
| | - Jung-Ho Lee
- Department of Materials and Chemical Engineering, Hanyang University, Ansan, Kyunggido 15588, Korea.
| | - Joondong Kim
- Photoelectric and Energy Device Application Lab (PEDAL), Multidisciplinary Core Institute for Future Energies (MCIFE), Incheon, 22012, Republic of Korea and Department of Electrical Engineering, Incheon National University, 119 Academy Rd. Yeonsu, Incheon, 22012, Republic of Korea.
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Kumar M, Som T, Kim J. A Transparent Photonic Artificial Visual Cortex. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2019; 31:e1903095. [PMID: 31410882 DOI: 10.1002/adma.201903095] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/14/2019] [Revised: 07/03/2019] [Indexed: 06/10/2023]
Abstract
Mimicking brain-like functionality with an electronic device is an essential step toward the design of future technologies including artificial visual and memory applications. Here, a proof-of-concept all-oxide-based (NiO/TiO2 ) highly transparent (54%) heterostructure is proposed and demonstrated, which mimics the primitive functions of the visual cortex. Specifically, orientation selectivity and spatiotemporal processing similar to that of the visual cortex are demonstrated using direct optical stimuli under the self-biased condition due to photovoltaic effect, illustrating an energy-efficient approach for neuromorphic computing. The photocurrent of the device can be modulated from zero to 80 µA by simply rotating the slit by 90°. The device shows fast rise and fall times of 3 and 6 ms, respectively. Based on Kelvin probe force measurements, the observed results are attributed to a lateral photovoltaic effect. This highly transparent, self-biased, photonic triggered device paves the way for the advancement of energy-efficient neuromorphic computation.
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Affiliation(s)
- Mohit Kumar
- Photoelectric and Energy Device Application Lab (PEDAL), Multidisciplinary Core Institute for Future Energies (MCIFE) and Department of Electrical Engineering, Incheon National University, 119 Academy Rd. Yeonsu, Incheon, 22012, Republic of Korea
| | - Tapobrata Som
- SUNAG Laboratory, Institute of Physics, Bhubaneswar, 751 005, Odisha, India
- Homi Bhabha National Institute, Training School Complex, Anushakti Nagar, Mumbai, 400 085, India
| | - Joondong Kim
- Photoelectric and Energy Device Application Lab (PEDAL), Multidisciplinary Core Institute for Future Energies (MCIFE) and Department of Electrical Engineering, Incheon National University, 119 Academy Rd. Yeonsu, Incheon, 22012, Republic of Korea
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A bioinspired optoelectronically engineered artificial neurorobotics device with sensorimotor functionalities. Nat Commun 2019; 10:3873. [PMID: 31455784 PMCID: PMC6712026 DOI: 10.1038/s41467-019-11823-4] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2019] [Accepted: 07/31/2019] [Indexed: 02/06/2023] Open
Abstract
Development of the next generation of bio- and nano-electronics is inseparably connected to the innovative concept of emulation and reproduction of biological sensorimotor systems and artificial neurobotics. Here, we report for the first time principally new artificial bioinspired optoelectronic sensorimotor system for the controlable immitation of opto-genetically engineered neurons in the biological motor system. The device is based on inorganic optical synapse (In-doped TiO2 nanofilm) assembled into a liquid metal (galinstan) actuator. The optoelectronic synapse generates polarised excitatory and inhibitory postsynaptic potentials to trigger the liquid metal droplet to vibrate and then mimic the expansion and contraction of biological fibre muscle. The low-energy consumption and precise modulation of electrical and mechanical outputs are the distinguished characteristics of fabricated sensorimotor system. This work is the underlying significant step towards the development of next generation of low-energy the internet of things for bioinspired neurorobotic and bioelectronic system.
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Han H, Yu H, Wei H, Gong J, Xu W. Recent Progress in Three-Terminal Artificial Synapses: From Device to System. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2019; 15:e1900695. [PMID: 30972944 DOI: 10.1002/smll.201900695] [Citation(s) in RCA: 70] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2019] [Revised: 03/03/2019] [Indexed: 05/28/2023]
Abstract
Synapses are essential to the transmission of nervous signals. Synaptic plasticity allows changes in synaptic strength that make a brain capable of learning from experience. During development of neuromorphic electronics, great efforts have been made to design and fabricate electronic devices that emulate synapses. Three-terminal artificial synapses have the merits of concurrently transmitting signals and learning. Inorganic and organic electronic synapses have mimicked plasticity and learning. Optoelectronic synapses and photonic synapses have the prospective benefits of low electrical energy loss, high bandwidth, and mechanical robustness. These artificial synapses provide new opportunities for the development of neuromorphic systems that can use parallel processing to manipulate datasets in real time. Synaptic devices have also been used to build artificial sensory systems. Here, recent progress in the development and application of three-terminal artificial synapses and artificial sensory systems is reviewed.
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Affiliation(s)
- Hong Han
- Institute of Optoelectronic Thin Film Devices and Technology, Nankai University, Tianjin, 300350, China
- Key Laboratory of Optoelectronic Thin Film Devices and Technology of Tianjin, Tianjin, 300350, China
| | - Haiyang Yu
- Institute of Optoelectronic Thin Film Devices and Technology, Nankai University, Tianjin, 300350, China
- Key Laboratory of Optoelectronic Thin Film Devices and Technology of Tianjin, Tianjin, 300350, China
| | - Huanhuan Wei
- Institute of Optoelectronic Thin Film Devices and Technology, Nankai University, Tianjin, 300350, China
- Key Laboratory of Optoelectronic Thin Film Devices and Technology of Tianjin, Tianjin, 300350, China
| | - Jiangdong Gong
- Institute of Optoelectronic Thin Film Devices and Technology, Nankai University, Tianjin, 300350, China
- Key Laboratory of Optoelectronic Thin Film Devices and Technology of Tianjin, Tianjin, 300350, China
| | - Wentao Xu
- Institute of Optoelectronic Thin Film Devices and Technology, Nankai University, Tianjin, 300350, China
- Key Laboratory of Optoelectronic Thin Film Devices and Technology of Tianjin, Tianjin, 300350, China
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Kumar M, Kim HS, Kim J. A Highly Transparent Artificial Photonic Nociceptor. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2019; 31:e1900021. [PMID: 30924201 DOI: 10.1002/adma.201900021] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/02/2019] [Revised: 02/08/2019] [Indexed: 06/09/2023]
Abstract
A nociceptor is an essential element in the human body, alerting us to potential damage from extremes in temperature, pressure, etc. Realizing nociceptive behavior in an electronics device remains a central issue for researchers, designing neuromorphic devices. This study proposes and demonstrates an all-oxide-based highly transparent ultraviolet-triggered artificial nociceptor, which responds in a very similar way to the human eye. The device shows a high transmittance (>65%) and very low absorbance in the visible region. The current-voltage characteristics show loop opening, which is attributed to the charge trapping/detrapping. Further, the ultraviolet-stimuli-induced versatile criteria of a nociceptor such as a threshold, relaxation, allodynia, and hyperalgesia are demonstrated under self-biased condition, providing an energy-efficient approach for the neuromorphic device operation. The reported optically controlled features open a new avenue for the development of transparent optoelectronic nociceptors, artificial eyes, and memory storage applications.
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Affiliation(s)
- Mohit Kumar
- Photoelectric and Energy Device Application Lab (PEDAL), Multidisciplinary Core Institute for Future Energies (MCIFE), Incheon National University, 119 Academy Rd. Yeonsu, Incheon, 22012, Republic of Korea
| | - Hong-Sik Kim
- Photoelectric and Energy Device Application Lab (PEDAL), Multidisciplinary Core Institute for Future Energies (MCIFE), Incheon National University, 119 Academy Rd. Yeonsu, Incheon, 22012, Republic of Korea
| | - Joondong Kim
- Photoelectric and Energy Device Application Lab (PEDAL), Multidisciplinary Core Institute for Future Energies (MCIFE), Incheon National University, 119 Academy Rd. Yeonsu, Incheon, 22012, Republic of Korea
- Department of Electrical Engineering, Incheon National University, 119 Academy Rd. Yeonsu, Incheon, 22012, Republic of Korea
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Gao S, Liu G, Yang H, Hu C, Chen Q, Gong G, Xue W, Yi X, Shang J, Li RW. An Oxide Schottky Junction Artificial Optoelectronic Synapse. ACS NANO 2019; 13:2634-2642. [PMID: 30730696 DOI: 10.1021/acsnano.9b00340] [Citation(s) in RCA: 68] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2023]
Abstract
The rapid development of artificial intelligence techniques and future advanced robot systems sparks emergent demand on the accurate perception and understanding of the external environments via visual sensing systems that can co-locate the self-adaptive detecting, processing, and memorizing of optical signals. In this contribution, a simple indium-tin oxide/Nb-doped SrTiO3 (ITO/Nb:SrTiO3) heterojunction artificial optoelectronic synapse is proposed and demonstrated. Through the light and electric field co-modulation of the Schottky barrier profile at the ITO/Nb:SrTiO3 interface, the oxide heterojunction device can respond to the entire visible light region in a neuromorphic manner, allowing synaptic paired-pulse facilitation, short/long-term memory, and "learning-experience" behavior for optical information manipulation. More importantly, the photoplasticity of the artificial synapse has been modulated by heterosynaptic means with a sub-1 V external voltage, not only enabling an optoelectronic analog of the mechanical aperture device showing adaptive and stable optical perception capability under different illuminating conditions but also making the artificial synapse suitable for the mimicry of interest-modulated human visual memories.
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Affiliation(s)
- Shuang Gao
- CAS Key Laboratory of Magnetic Materials and Devices , Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences , Ningbo , Zhejiang 315201 , China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology , Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences , Ningbo , Zhejiang 315201 , China
| | - Gang Liu
- CAS Key Laboratory of Magnetic Materials and Devices , Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences , Ningbo , Zhejiang 315201 , China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology , Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences , Ningbo , Zhejiang 315201 , China
| | - Huali Yang
- CAS Key Laboratory of Magnetic Materials and Devices , Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences , Ningbo , Zhejiang 315201 , China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology , Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences , Ningbo , Zhejiang 315201 , China
| | - Chao Hu
- CAS Key Laboratory of Magnetic Materials and Devices , Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences , Ningbo , Zhejiang 315201 , China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology , Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences , Ningbo , Zhejiang 315201 , China
| | - Qilai Chen
- CAS Key Laboratory of Magnetic Materials and Devices , Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences , Ningbo , Zhejiang 315201 , China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology , Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences , Ningbo , Zhejiang 315201 , China
| | - Guodong Gong
- CAS Key Laboratory of Magnetic Materials and Devices , Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences , Ningbo , Zhejiang 315201 , China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology , Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences , Ningbo , Zhejiang 315201 , China
| | - Wuhong Xue
- CAS Key Laboratory of Magnetic Materials and Devices , Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences , Ningbo , Zhejiang 315201 , China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology , Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences , Ningbo , Zhejiang 315201 , China
| | - Xiaohui Yi
- CAS Key Laboratory of Magnetic Materials and Devices , Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences , Ningbo , Zhejiang 315201 , China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology , Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences , Ningbo , Zhejiang 315201 , China
| | - Jie Shang
- CAS Key Laboratory of Magnetic Materials and Devices , Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences , Ningbo , Zhejiang 315201 , China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology , Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences , Ningbo , Zhejiang 315201 , China
| | - Run-Wei Li
- CAS Key Laboratory of Magnetic Materials and Devices , Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences , Ningbo , Zhejiang 315201 , China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology , Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences , Ningbo , Zhejiang 315201 , China
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Kumar M, Kim HS, Lee GN, Lim D, Kim J. Piezophototronic Effect Modulated Multilevel Current Amplification from Highly Transparent and Flexible Device Based on Zinc Oxide Thin Film. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2018; 14:e1804016. [PMID: 30457700 DOI: 10.1002/smll.201804016] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2018] [Revised: 10/31/2018] [Indexed: 06/09/2023]
Abstract
In this work, a strain modulated highly transparent and flexible ZnO/Ag-nanowires/polyethylene terephthalate optoelectronic device is developed. By utilizing the applied external strain-induced piezophototronic effects of a ZnO thin film, a UV-generated photocurrent is tuned in a wide range starting from 0.01 to 85.07 µA and it is presented in a comprehensive map. Particularly, the performance of the device is effectively enhanced 7733 times by compressive strain, as compared to its dark current in a strain-free state. The observed results are explained quantitatively based on the modulation of oxygen desorption/absorption on the ZnO surface under the influence of applied strains. The presented simple optoelectronic device can be easily integrated into existing planar structures, with potential applications in highly transparent smart windows, wearable electronics, smartphones, security communication, and so on.
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Affiliation(s)
- Mohit Kumar
- Photoelectric and Energy Device Application Lab (PEDAL), Multidisciplinary Core Institute for Future Energies (MCIFE), Incheon National University, 119 Academy Rd. Yeonsu, Incheon, 22012, Republic of Korea
| | - Hong-Sik Kim
- Photoelectric and Energy Device Application Lab (PEDAL), Multidisciplinary Core Institute for Future Energies (MCIFE), Incheon National University, 119 Academy Rd. Yeonsu, Incheon, 22012, Republic of Korea
| | - Gyeong-Nam Lee
- Photoelectric and Energy Device Application Lab (PEDAL), Multidisciplinary Core Institute for Future Energies (MCIFE), Incheon National University, 119 Academy Rd. Yeonsu, Incheon, 22012, Republic of Korea
- Department of Electrical Engineering, Incheon National University, 119 Academy Rd. Yeonsu, Incheon, 22012, Republic of Korea
| | - Donggun Lim
- Department of IT Convergence, Korea National University of Transportation, 50 Daehak-ro, Chungju, Chungbuk, 380702, Republic of Korea
| | - Joondong Kim
- Photoelectric and Energy Device Application Lab (PEDAL), Multidisciplinary Core Institute for Future Energies (MCIFE), Incheon National University, 119 Academy Rd. Yeonsu, Incheon, 22012, Republic of Korea
- Department of Electrical Engineering, Incheon National University, 119 Academy Rd. Yeonsu, Incheon, 22012, Republic of Korea
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