Chitosan-Based Polysaccharide-Gated Flexible Indium Tin Oxide Synaptic Transistor with Learning Abilities

A Monolithic Neuromorphic Device for In-Sensor Tactile Computing

To emulate the tactile perception of human skin, the integration of tactile sensors with neuromorphic devices has emerged as a promising approach to achieve near-sensor information processing. Here, we present a monolithic electronic device that seamlessly integrates tactile perception and neuromorphic computing functionalities within a single architecture, with synaptic plasticity directly tunable by tactile inputs. This unique capability stems from our engineered device structure employing SnO2 nanowires as the conductive channel coupled with a pressure-sensitive chitosan layer ionic gating layer. The device demonstrates pressure-dependent memory retention and learning behaviors, effectively mimicking the enhanced cognitive functions observed in humans under stressful conditions. Furthermore, the integrated design exhibits potential for implementing bioinspired electronic systems requiring adaptive tactile information processing.

Natural biomaterials for sustainable flexible neuromorphic devices

Neuromorphic electronics use neural models in hardware to emulate brain-like behavior, and provide power-efficient, extremely compact, and massively-parallel processing, so they are ideal candidates for next-generation information-processing units. However, traditional rigid neuromorphic devices are limited by their unavoidable mechanical and geometrical mismatch with human tissues or organs. At the same time, the rapid development of these electronic devices has generated a large amount of electronic waste, thereby causing severe ecological problems. Natural biomaterials have mechanical properties compatible with biological tissues, and are environmentally benign, ultra-thin, and lightweight, so use of these materials can address these limitations and be used to create next-generation sustainable flexible neuromorphic electronics. Here, we explore the advantages of natural biomaterials in simulating synaptic behavior of sustainable neuromorphic devices. We present the flexibility, biocompatibility, and biodegradability of these neuromorphic devices, and consider the potential applicability of these properties in wearable and implantable bioelectronics. Finally, we consider the challenges of device fabrication and neuromorphic system integration by natural biomaterials, then suggest future research directions.

Electrolyte Gated Transistors for Brain Inspired Neuromorphic Computing and Perception Applications: A Review

Emerging neuromorphic computing offers a promising and energy-efficient approach to developing advanced intelligent systems by mimicking the information processing modes of the human brain. Moreover, inspired by the high parallelism, fault tolerance, adaptability, and low power consumption of brain perceptual systems, replicating these efficient and intelligent systems at a hardware level will endow artificial intelligence (AI) and neuromorphic engineering with unparalleled appeal. Therefore, construction of neuromorphic devices that can simulate neural and synaptic behaviors are crucial for achieving intelligent perception and neuromorphic computing. As novel memristive devices, electrolyte-gated transistors (EGTs) stand out among numerous neuromorphic devices due to their unique interfacial ion coupling effects. Thus, the present review discusses the applications of the EGTs in neuromorphic electronics. First, operational modes of EGTs are discussed briefly. Second, the advancements of EGTs in mimicking biological synapses/neurons and neuromorphic computing functions are introduced. Next, applications of artificial perceptual systems utilizing EGTs are discussed. Finally, a brief outlook on future developments and challenges is presented.

Nanomaterials for Flexible Neuromorphics

The quest to imbue machines with intelligence akin to that of humans, through the development of adaptable neuromorphic devices and the creation of artificial neural systems, has long stood as a pivotal goal in both scientific inquiry and industrial advancement. Recent advancements in flexible neuromorphic electronics primarily rely on nanomaterials and polymers owing to their inherent uniformity, superior mechanical and electrical capabilities, and versatile functionalities. However, this field is still in its nascent stage, necessitating continuous efforts in materials innovation and device/system design. Therefore, it is imperative to conduct an extensive and comprehensive analysis to summarize current progress. This review highlights the advancements and applications of flexible neuromorphics, involving inorganic nanomaterials (zero-/one-/two-dimensional, and heterostructure), carbon-based nanomaterials such as carbon nanotubes (CNTs) and graphene, and polymers. Additionally, a comprehensive comparison and summary of the structural compositions, design strategies, key performance, and significant applications of these devices are provided. Furthermore, the challenges and future directions pertaining to materials/devices/systems associated with flexible neuromorphics are also addressed. The aim of this review is to shed light on the rapidly growing field of flexible neuromorphics, attract experts from diverse disciplines (e.g., electronics, materials science, neurobiology), and foster further innovation for its accelerated development.

Blood-based biomemristor for hyperglycemia and hyperlipidemia monitoring

Thanks to its structural characteristics and signal patterns similar to those of human brain synapses, memristors are widely believed to be applicable for neuromorphic computing. However, to our knowledge, memristors have not been effectively applied in the biomedical field, especially in disease diagnosis and health monitoring. In this work, a blood-based biomemristor was prepared for in vitro detection of hyperglycemia and hyperlipidemia. It was found that the device exhibits excellent resistance switching (RS) behavior at lower voltage biases. Through mechanism analysis, it has been confirmed that the RS behavior is driven by Ohmic conduction and ion rearrangement. Furthermore, the hyperglycemia and hyperlipidemia detection devices were constructed for the first time based on memristor logic circuits, and circuit simulations were conducted. These results confirm the feasibility of blood-based biomemristors in detecting hyperglycemia and hyperlipidemia, providing new prospects for the important application of memristors in the biomedical field.

PEDOT:PSS-Based Prolonged Long-Term Decay Synaptic OECT with Proton-Permeable Material, Nafion

Poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS), a conductive polymer, has gained popularity as the channel layer in organic electrochemical transistors (OECTs) due to its high conductivity and straightforward processing. However, difficulties arise in controlling its conductivity through gate voltage, presenting a challenge. To address this issue, aromatic amidine base, diazabicyclo[4.3.0]non-5-ene (DBN), is used to stabilize the doping state of the PEDOT chain through a reliable chemical de-doping process. Furthermore, the addition of the proton-penetrable material Nafion to the PEDOT:PSS channel layer induces phase separation between the substances. By utilizing a solution containing both PEDOT:PSS and Nafion as the channel layer of OECTs, the efficiency of ion movement into the channel from the electrolyte is enhanced, resulting in improved OECT performance. The inclusion of Nafion in the OECTs' channel layer modifies ion movement dynamics, allowing for the adjustment of synaptic properties such as pulse-paired facilitation, memory level, short-term plasticity, and long-term plasticity. This research aims to introduce new possibilities in the field of neuromorphic computing and contribute to biomimetic technology through the enhancement of electronic component performance.

Humidity-Induced Protein-Based Artificial Synaptic Devices for Neuroprosthetic Applications

Neuroprosthetics and brain-machine interfaces are immensely beneficial for people with neurological disabilities, and the future generation of neural repair systems will utilize neuromorphic devices for the advantages of energy efficiency and real-time performance abilities. Conventional synaptic devices are not compatible to work in such conditions. The cerebrospinal fluid (CSF) in the central part of the nervous system is composed of 99% water. Therefore, artificial synaptic devices, which are the fundamental component of neuromorphic devices, should resemble biological nerves while being biocompatible, and functional in high-humidity environments with higher functional stability for real-time applications in the human body. In this work, artificial synaptic devices are fabricated based on gelatin-PEDOT: PSS composite as an active material to work more effectively in a highly humid environment (≈90% relative humidity). These devices successfully mimic various synaptic properties by the continuous variation of conductance, like, excitatory/inhibitory post-synaptic current(EPSC/IPSC), paired-pulse facilitation/depression(PPF/PPD), spike-voltage dependent plasticity (SVDP), spike-duration dependent plasticity (SDDP), and spike-rate dependent plasticity (SRDP) in environments at a relative humidity levels of ≈90%.

Oxide Ionic Neuro-Transistors for Bio-inspired Computing

Current computing systems rely on Boolean logic and von Neumann architecture, where computing cells are based on high-speed electron-conducting complementary metal-oxide-semiconductor (CMOS) transistors. In contrast, ions play an essential role in biological neural computing. Compared with CMOS units, the synapse/neuron computing speed is much lower, but the human brain performs much better in many tasks such as pattern recognition and decision-making. Recently, ionic dynamics in oxide electrolyte-gated transistors have attracted increasing attention in the field of neuromorphic computing, which is more similar to the computing modality in the biological brain. In this review article, we start with the introduction of some ionic processes in biological brain computing. Then, electrolyte-gated ionic transistors, especially oxide ionic transistors, are briefly introduced. Later, we review the state-of-the-art progress in oxide electrolyte-gated transistors for ionic neuromorphic computing including dynamic synaptic plasticity emulation, spatiotemporal information processing, and artificial sensory neuron function implementation. Finally, we will address the current challenges and offer recommendations along with potential research directions.

Hydrogel-Gated FETs in Neuromorphic Computing to Mimic Biological Signal: A Review

Hydrogel-gated synaptic transistors offer unique advantages, including biocompatibility, tunable electrical properties, being biodegradable, and having an ability to mimic biological synaptic plasticity. For processing massive data with ultralow power consumption due to high parallelism and human brain-like processing abilities, synaptic transistors have been widely considered for replacing von Neumann architecture-based traditional computers due to the parting of memory and control units. The crucial components mimic the complex biological signal, synaptic, and sensing systems. Hydrogel, as a gate dielectric, is the key factor for ionotropic devices owing to the excellent stability, ultra-high linearity, and extremely low operating voltage of the biodegradable and biocompatible polymers. Moreover, hydrogel exhibits ionotronic functions through a hybrid circuit of mobile ions and mobile electrons that can easily interface between machines and humans. To determine the high-efficiency neuromorphic chips, the development of synaptic devices based on organic field effect transistors (OFETs) with ultra-low power dissipation and very large-scale integration, including bio-friendly devices, is needed. This review highlights the latest advancements in neuromorphic computing by exploring synaptic transistor developments. Here, we focus on hydrogel-based ionic-gated three-terminal (3T) synaptic devices, their essential components, and their working principle, and summarize the essential neurodegenerative applications published recently. In addition, because hydrogel-gated FETs are the crucial members of neuromorphic devices in terms of cutting-edge synaptic progress and performances, the review will also summarize the biodegradable and biocompatible polymers with which such devices can be implemented. It is expected that neuromorphic devices might provide potential solutions for the future generation of interactive sensation, memory, and computation to facilitate the development of multimodal, large-scale, ultralow-power intelligent systems.

Organic-Inorganic Hybrid Synaptic Transistors: Methyl-Silsesquioxanes-Based Electric Double Layer for Enhanced Synaptic Functionality and CMOS Compatibility

Electrical double-layer (EDL) synaptic transistors based on organic materials exhibit low thermal and chemical stability and are thus incompatible with complementary metal oxide semiconductor (CMOS) processes involving high-temperature operations. This paper proposes organic-inorganic hybrid synaptic transistors using methyl silsesquioxane (MSQ) as the electrolyte. MSQ, derived from the combination of inorganic silsesquioxanes and the organic methyl (-CH3) group, exhibits exceptional thermal and chemical stability, thus ensuring compatibility with CMOS processes. We fabricated Al/MSQ electrolyte/Pt capacitors, exhibiting a substantial capacitance of 1.89 µF/cm2 at 10 Hz. MSQ-based EDL synaptic transistors demonstrated various synaptic behaviors, such as excitatory post-synaptic current, paired-pulse facilitation, signal pass filtering, and spike-number-dependent plasticity. Additionally, we validated synaptic functions such as information storage and synapse weight adjustment, simulating brain synaptic operations through potentiation and depression. Notably, these synaptic operations demonstrated stability over five continuous operation cycles. Lastly, we trained a multi-layer artificial deep neural network (DNN) using a handwritten Modified National Institute of Standards and Technology image dataset. The DNN achieved an impressive recognition rate of 92.28%. The prepared MSQ-based EDL synaptic transistors, with excellent thermal/chemical stability, synaptic functionality, and compatibility with CMOS processes, harbor tremendous potential as materials for next-generation artificial synapse components.

Ferroelectric artificial synapse for neuromorphic computing and flexible applications

Research of artificial synapses is increasing in popularity with the development of bioelectronics and the appearance of wearable devices. Because the high-temperature treatment process of inorganic materials is not compatible with flexible substrates, organic ferroelectric materials that are easier to process have emerged as alternatives. An organic synaptic device based on P(VDF-TrFE) was prepared in this study. The device showed reliable P/E endurance over 104 cycles and a data storage retention capability at 80 °C over 104 s. Simultaneously, it possessed excellent synaptic functions, including short-term/ long-term synaptic plasticity and spike-timing-dependent plasticity. In addition, the ferroelectric performance of the device remained stable even under bending (7 mm bending radius) or after 500 bending cycles. This work shows that low-temperature processed organic ferroelectric materials can provide new ideas for the future development of wearable electronics and flexible artificial synapses.

Biodegradable Oxide Neuromorphic Transistors for Neuromorphic Computing and Anxiety Disorder Emulation

Brain-inspired neuromorphic computing and portable intelligent electronic products have received increasing attention. In the present work, nanocellulose-gated indium tin oxide neuromorphic transistors are fabricated. The device exhibits good electrical performance. Short-term synaptic plasticities were mimicked, including excitatory postsynaptic current, paired-pulse facilitation, and dynamic high-pass synaptic filtering. Interestingly, an effective linear synaptic weight updating strategy was adopted, resulting in an excellent recognition accuracy of ∼92.93% for the Modified National Institute of Standard and Technology database adopting a two-layer multilayer perceptron neural network. Moreover, with unique interfacial protonic coupling, anxiety disorder behavior was conceptually emulated, exhibiting "neurosensitization", "primary and secondary fear", and "fear-adrenaline secretion-exacerbated fear". Finally, the neuromorphic transistors could be dissolved in water, demonstrating potential in "green" electronics. These findings indicate that the proposed oxide neuromorphic transistors would have potential as implantable chips for nerve health diagnosis, neural prostheses, and brain-machine interfaces.

Emerging Iontronic Neural Devices for Neuromorphic Sensory Computing

Living organisms have a very mysterious and powerful sensory computing system based on ion activity. Interestingly, studies on iontronic devices in the past few years have proposed a promising platform for simulating the sensing and computing functions of living organisms, because: 1) iontronic devices can generate, store, and transmit a variety of signals by adjusting the concentration and spatiotemporal distribution of ions, which analogs to how the brain performs intelligent functions by alternating ion flux and polarization; 2) through ionic-electronic coupling, iontronic devices can bridge the biosystem with electronics and offer profound implications for soft electronics; 3) with the diversity of ions, iontronic devices can be designed to recognize specific ions or molecules by customizing the charge selectivity, and the ionic conductivity and capacitance can be adjusted to respond to external stimuli for a variety of sensing schemes, which can be more difficult for electron-based devices. This review provides a comprehensive overview of emerging neuromorphic sensory computing by iontronic devices, highlighting representative concepts of both low-level and high-level sensory computing and introducing important material and device breakthroughs. Moreover, iontronic devices as a means of neuromorphic sensing and computing are discussed regarding the pending challenges and future directions.

Emerging electrolyte-gated transistors for neuromorphic perception

With the rapid development of intelligent robotics, the Internet of Things, and smart sensor technologies, great enthusiasm has been devoted to developing next-generation intelligent systems for the emulation of advanced perception functions of humans. Neuromorphic devices, capable of emulating the learning, memory, analysis, and recognition functions of biological neural systems, offer solutions to intelligently process sensory information. As one of the most important neuromorphic devices, Electrolyte-gated transistors (EGTs) have shown great promise in implementing various vital neural functions and good compatibility with sensors. This review introduces the materials, operating principle, and performances of EGTs, followed by discussing the recent progress of EGTs for synapse and neuron emulation. Integrating EGTs with sensors that faithfully emulate diverse perception functions of humans such as tactile and visual perception is discussed. The challenges of EGTs for further development are given.

Recent advances in neuromorphic transistors for artificial perception applications: FOCUS ISSUE REVIEW

Conventional von Neumann architecture is insufficient in establishing artificial intelligence (AI) in terms of energy efficiency, computing in memory and dynamic learning. Delightedly, rapid developments in neuromorphic computing provide a new paradigm to solve this dilemma. Furthermore, neuromorphic devices that can realize synaptic plasticity and neuromorphic function have extraordinary significance for neuromorphic system. A three-terminal neuromorphic transistor is one of the typical representatives. In addition, human body has five senses, including vision, touch, auditory sense, olfactory sense and gustatory sense, providing abundant information for brain. Inspired by the human perception system, developments in artificial perception system will give new vitality to intelligent robots. This review discusses the operation mechanism, function and application of neuromorphic transistors. The latest progresses in artificial perception systems based on neuromorphic transistors are provided. Finally, the opportunities and challenges of artificial perception systems are summarized.

Biocompatible Potato-Starch Electrolyte-Based Coplanar Gate-Type Artificial Synaptic Transistors on Paper Substrates

In this study, we propose the use of artificial synaptic transistors with coplanar-gate structures fabricated on paper substrates comprising biocompatible and low-cost potato-starch electrolyte and indium-gallium-zinc oxide (IGZO) channels. The electrical double layer (EDL) gating effect of potato-starch electrolytes enabled the emulation of biological synaptic plasticity. Frequency dependence measurements of capacitance using a metal-insulator-metal capacitor configuration showed a 1.27 μF/cm2 at a frequency of 10 Hz. Therefore, strong capacitive coupling was confirmed within the potato-starch electrolyte/IGZO channel interface owing to EDL formation because of internal proton migration. An electrical characteristics evaluation of the potato-starch EDL transistors through transfer and output curve resulted in counterclockwise hysteresis caused by proton migration in the electrolyte; the hysteresis window linearly increased with maximum gate voltage. A synaptic functionality evaluation with single-spike excitatory post-synaptic current (EPSC), paired-pulse facilitation (PPF), and multi-spike EPSC resulted in mimicking short-term synaptic plasticity and signal transmission in the biological neural network. Further, channel conductance modulation by repetitive presynaptic stimuli, comprising potentiation and depression pulses, enabled stable modulation of synaptic weights, thereby validating the long-term plasticity. Finally, recognition simulations on the Modified National Institute of Standards and Technology (MNIST) handwritten digit database yielded a 92% recognition rate, thereby demonstrating the applicability of the proposed synaptic device to the neuromorphic system.

Ultralow-Thermal-Budget-Driven IWO-Based Thin-Film Transistors and Application Explorations

Exploiting multifunctional thin film transistors (TFTs) by low-temperature manufacturing strategy is a crucial step toward flexible electronics. Herein, a multifunctional indium-tungsten-oxide (IWO)-based TFT, gated by solid-state chitosan electrolyte membrane, is fabricated on paper substrate at room temperature. The chitosan exhibits a high specific electric-double-layer capacitance of 2.0 µF cm^-2 due to the existence of mobile protons. The IWO-based TFT possesses excellent electrical properties, including a low threshold voltage of 0.2 V, larger current switching ratio of 1.3 × 10⁶, high field effect mobility of 15.0 cm² V^-1s^-1, and small subthreshold swing of 117 mV/decade, respectively. Multifunctional operations including inverter, Schmitt triggers, and NAND gate are successfully demonstrated. As an example of information processing, the essential signal transmission functions of biological synapses also be emulated in the fabricated IWO-based TFTs. The experimental results indicate that such flexible IWO-based TFTs on low-cost and biodegradable paper provide the new-concept building blocks for flexible electronics.

Binary-Synaptic Plasticity in Ambipolar Ni-Silicide Schottky Barrier Poly-Si Thin Film Transistors Using Chitosan Electric Double Layer

We propose an ambipolar chitosan synaptic transistor that effectively responds to binary neuroplasticity. We fabricated the synaptic transistors by applying a chitosan electric double layer (EDL) to the gate insulator of the excimer laser annealed polycrystalline silicon (poly-Si) thin-film transistor (TFT) with Ni-silicide (NiSi) Schottky-barrier source/drain (S/D) junction. The undoped poly-Si channel and the NiSi S/D contact allowed conduction by electrons and holes, resulting in artificial synaptic behavior in both p-type and n-type regions. A slow polarization reaction by the mobile ions such as anions (CH3COO- and OH-) and cations (H+) in the chitosan EDL induced hysteresis window in the transfer characteristics of the ambipolar TFTs. We demonstrated the excitatory post-synaptic current modulations and stable conductance modulation through repetitive potentiation and depression pulse. We expect the proposed ambipolar chitosan synaptic transistor that responds effectively to both positive and negative stimulation signals to provide more complex information process versatility for bio-inspired neuromorphic computing systems.

A Flexible Artificial Sensory Nerve Enabled by Nanoparticle-Assembled Synaptic Devices for Neuromorphic Tactile Recognition

Tactile perception enabled by somatosensory system in human is essential for dexterous tool usage, communication, and interaction. Imparting tactile recognition functions to advanced robots and interactive systems can potentially improve their cognition and intelligence. Here, a flexible artificial sensory nerve that mimics the tactile sensing, neural coding, and synaptic processing functions in human sensory nerve is developed to achieve neuromorphic tactile recognition at device level without relying on algorithms or computing resources. An interfacial self-assembly technique, which produces uniform and defect-less thin film of semiconductor nanoparticles on arbitrary substrates, is employed to prepare the flexible synaptic device. The neural facilitation and sensory memory characteristics of the proton-gating synaptic device enable this system to identify material hardness during robotic grasping and recognize tapping patterns during tactile interaction in a continuous, real-time, high-accuracy manner, demonstrating neuromorphic intelligence and recognition capabilities. This artificial sensory nerve produced in wearable and portable form can be readily integrated with advanced robots and smart human-machine interfaces for implementing human-like tactile cognition in neuromorphic electronics toward robotic and wearable applications.

Synaptic Plasticity and Quantized Conductance States in TiN-Nanoparticles-Based Memristor for Neuromorphic System

Controlled conductive filament formation in the resistive random access memory device is an essential requirement for analog resistive switching to develop artificial synapses. In this work, we have studied Au/Ti/HfAlOx/TiN-NP/HfAlOx/ITO RRAM device to demonstrate conductance quantization behavior to achieve the high-density memory application. Stepwise change in conductance under DC and pulse voltage confirms the quantized conductance states with integer and half-integer multiples of G0. Reactive TiN-NPs inside the switching layer helps to form and rupture the atomic scale conductive filaments due to enhancing the local electric field inside. Bipolar resistive switching characteristics at low SET/RESET voltage were obtained with memory window > 10 and stable endurance of 103 cycles. Short-term and long-term plasticities are successfully demonstrated by modulating the pre-spike number, magnitude, and frequency. The quantized conductance behavior with promising synaptic properties obtained in the experiments suggests HfAlOx/TiN-NP/HfAlOx switching layer is suitable for multilevel high-density storage RRAM devices.

Multi-Bit Biomemristic Behavior for Neutral Polysaccharide Dextran Blended with Chitosan

Natural biomaterials applicable for biomemristors have drawn prominent attention and are of benefit to sustainability, biodegradability, biocompatibility, and metabolism. In this work, multi-bit biomemristors based on the neutral polysaccharide dextran were built using the spin-casting method, which was also employed to explore the effect of dextran on the ternary biomemristic behaviors of dextran–chitosan nanocomposites. The doping of 50 wt% dextran onto the bio-nanocomposite optimized the ratio of biomemristance in high-, intermediate-, and low-resistance states (10⁵:10⁴:1). The interaction between dextran and chitosan (hydrogen-bond network) was verified by Fourier transform infrared (FTIR) and Raman spectroscopy analysis; through this interaction, protons derived from the self-dissociation of water may migrate under the electric field, and so proton conduction may be the reason for the ternary biomemristic behaviors. Observations from X-ray diffraction (XRD), thermogravimetric analysis (TGA), and differential scanning calorimetry (DSC) analysis displayed that the 50 wt% dextran/50 wt% chitosan nanocomposite had the greatest amorphous ratio as well as the highest decomposition and peak transition temperatures in comparison with the other three dextran–chitosan nanocomposites. This work lays the foundation for neutral biomaterials applied to green ultra-high-density data-storage systems.

Oxygen-Vacancy-Induced Synaptic Plasticity in an Electrospun InGdO Nanofiber Transistor for a Gas Sensory System with a Learning Function

The perceptual learning function of a simulating human body is very important for constructing a neural computing system and a brainlike computer in the future. The sense of smell is an important part of the human sensory nervous system. However, current gas sensors simply convert gas concentrations into electrical signals and do not have the same learning and memory function as synapses. To solve this problem, we propose a new sensing idea to induce and activate the synaptic properties of transistors by adjusting the oxygen vacancy in the active layer. This sensor combines gas detection with synaptic memory and learning and overcomes the disadvantage of the separation of synaptic transistors and sensors, thus greatly reducing the cost of production. This work combines the detection of N,N-dimethylformamide (DMF) gas with the synaptic mechanism of human olfactory nerves. We successfully fabricated an InGdO nanofiber field-effect transistor by electrostatic spinning and simulated the response of human olfactory synapses to target gas by regulating the oxygen vacancy of the InGdO nanofiber. The synaptic transistor response under different concentrations of unmodulated pulses is tested, and the pavlovian conditioned reflex experiment is simulated successfully. This work provides a new idea of a gas sensor device, which is very important for the development of high-performance gas sensors and bionic electronic devices in the future.

Sol-Gel Composites-Based Flexible and Transparent Amorphous Indium Gallium Zinc Oxide Thin-Film Synaptic Transistors for Wearable Intelligent Electronics

In this study, we propose the fabrication of sol-gel composite-based flexible and transparent synaptic transistors on polyimide (PI) substrates. Because a low thermal budget process is essential for the implementation of high-performance synaptic transistors on flexible PI substrates, microwave annealing (MWA) as a heat treatment process suitable for thermally vulnerable substrates was employed and compared to conventional thermal annealing (CTA). In addition, a solution-processed wide-bandgap amorphous In-Ga-Zn (2:1:1) oxide (a-IGZO) channel, an organic polymer chitosan electrolyte-based electric double layer (EDL), and a high-k Ta₂O₅ thin-film dielectric layer were applied to achieve high flexibility and transparency. The essential synaptic plasticity of the flexible and transparent synaptic transistors fabricated with the MWA process was demonstrated by single spike, paired-pulse facilitation, multi-spike facilitation excitatory post-synaptic current (EPSC), and three-cycle evaluation of potentiation and depression behaviors. Furthermore, we verified the mechanical robustness of the fabricated device through repeated bending tests and demonstrated that the electrical properties were stably maintained. As a result, the proposed sol-gel composite-based synaptic transistors are expected to serve as transparent and flexible intelligent electronic devices capable of stable neural operation.

Flexible artificial Si-In-Zn-O/ion gel synapse and its application to sensory-neuromorphic system for sign language translation

We propose a flexible artificial synapse based on a silicon-indium-zinc-oxide (SIZO)/ion gel hybrid structure directly fabricated on a polyimide substrate, where the channel conductance is effectively modulated via ion movement in the ion gel. This synaptic operation is possible because of the low-temperature deposition process of the SIZO layer (<150°C) and the surface roughness improvement of the poly(4-vinylphenol) buffer layer (12.29→1.81 nm). The flexible synaptic device exhibits extremely stable synaptic performance under high mechanical (bending 1500 times with a radius of 5 mm) and electrical stress (application of voltage pulses 10⁴ times) without any degradation. Last, a sensory-neuromorphic system for sign language translation, which consists of stretchable resistive sensors and flexible artificial synapses, is designed and successfully evaluated via training and recognition simulation using hand sign patterns obtained by stretchable sensors (maximum recognition rate, 99.4%).

UV light modulated synaptic behavior of MoTe2/BN heterostructure

Electrical synaptic devices are the basic components for the hardware based neuromorphic computational systems, which are expected to break the bottleneck of current von Neumann architecture. So far, synaptic devices based on three-terminal transistors are considered to provide the most stable performance, which usually use gate pulses to modulate the channel conductance through a floating gate and/or charge trapping layer. Herein, we report a three-terminal synaptic device based on a two-dimensional molybdenum ditelluride (MoTe₂)/hexagonal boron nitride (hBN) heterostructure. This structure enables stable and prominent conductance modulation of the MoTe₂channel by the photo-induced doping method through electron migration between the MoTe₂channel and ultraviolet (UV) light excited mid-gap defect states in hBN. Therefore, it is free of the floating gate and charge trapping layer to reduce the thickness and simplify the fabrication/design of the device. Moreover, since UV illumination is indispensable for stable doping in MoTe₂channel, the device can realize both short- (without UV illumination) and long- (with UV illumination) term plasticity. Meanwhile, the introduction of UV light allows additional tunability on the MoTe₂channel conductance through the wavelength and power intensity of incident UV, which may be important to mimic advanced synaptic functions. In addition, the photo-induced doping method can bidirectionally dope MoTe₂channel, which not only leads to large high/low resistance ratio for potential multi-level storage, but also implement both potentiation (n-doping) and depression (p-doping) of synaptic weight. This work explores alternative three-terminal synaptic configuration without floating gate and charge trapping layer, which may inspire researches on novel electrical synapse mechanisms.

Natural biopolymers as proton conductors in bioelectronics

Bioelectronic devices sense or deliver information at the interface between living systems and electronics by converting biological signals into electronic signals and vice-versa. Biological signals are typically carried by ions and small molecules. As such, ion conducting materials are ideal candidates in bioelectronics for an optimal interface. Among these materials, ion conducting polymers that are able to uptake water are particularly interesting because, in addition to ionic conductivity, their mechanical properties can closely match the ones of living tissue. In this review, we focus on a specific subset of ion-conducting polymers: proton (H⁺ ) conductors that are naturally derived. We first provide a brief introduction of the proton conduction mechanism, and then outline the chemical structure and properties of representative proton-conducting natural biopolymers: polysaccharides (chitosan and glycosaminoglycans), peptides and proteins, and melanin. We then highlight examples of using these biopolymers in bioelectronic devices. We conclude with current challenges and future prospects for broader use of natural biopolymers as proton conductors in bioelectronics and potential translational applications.

Artificial Skin Perception

Skin is the largest organ, with the functionalities of protection, regulation, and sensation. The emulation of human skin via flexible and stretchable electronics gives rise to electronic skin (e-skin), which has realized artificial sensation and other functions that cannot be achieved by conventional electronics. To date, tremendous progress has been made in data acquisition and transmission for e-skin systems, while the implementation of perception within systems, that is, sensory data processing, is still in its infancy. Integrating the perception functionality into a flexible and stretchable sensing system, namely artificial skin perception, is critical to endow current e-skin systems with higher intelligence. Here, recent progress in the design and fabrication of artificial skin perception devices and systems is summarized, and challenges and prospects are discussed. The strategies for implementing artificial skin perception utilize either conventional silicon-based circuits or novel flexible computing devices such as memristive devices and synaptic transistors, which enable artificial skin to surpass human skin, with a distributed, low-latency, and energy-efficient information-processing ability. In future, artificial skin perception would be a new enabling technology to construct next-generation intelligent electronic devices and systems for advanced applications, such as robotic surgery, rehabilitation, and prosthetics.

An Artificial Electrical-Chemical Mixed Synapse Based on Ion-Gated MoS2 Nanosheets for Real-Time Facilitation Index Tuning

Tunability of facilitation in short-term memory (STM) provides great potential in bioinspired computing. Recently, several doping strategies were proposed to modify the intrinsic features of materials, resulting in the optimization of the facilitation index (FI). However, real-time scale tuning, which is implemented on the same synaptic device, has not yet been demonstrated. Inspired by the chemical-electrical mixed synapse structure in the brain, we propose a three-terminal artificial synapse based on an ion-gated MoS₂ memristor. The gate terminal serves as a nonvolatile ionic pump via chemical intercalation, which effectively affects both the conductance baseline and the hysteresis degree of the STM effect of the memristor. We further modeled the postsynaptic current (PSC) behavior and used it for reservoir computing. Simulation results show that, due to the real-time tuning ability, the built reservoir can be programmed for specific handwritten recognition tasks with the pruning of neurons from 784 to 50. The developed artificial mixed synapse is promising for a downsampling module in neural network design.

Evolution of Bio-Inspired Artificial Synapses: Materials, Structures, and Mechanisms

Artificial synapses (ASs) are electronic devices emulating important functions of biological synapses, which are essential building blocks of artificial neuromorphic networks for brain-inspired computing. A human brain consists of several quadrillion synapses for information storage and processing, and massively parallel computation. Neuromorphic systems require ASs to mimic biological synaptic functions, such as paired-pulse facilitation, short-term potentiation, long-term potentiation, spatiotemporally-correlated signal processing, and spike-timing-dependent plasticity, etc. Feature size and energy consumption of ASs need to be minimized for high-density energy-efficient integration. This work reviews recent progress on ASs. First, synaptic plasticity and functional emulation are introduced, and then synaptic electronic devices for neuromorphic computing systems are discussed. Recent advances in flexible artificial synapses for artificial sensory nerves are also briefly introduced. Finally, challenges and opportunities in the field are discussed.

Selective Release of Different Neurotransmitters Emulated by a p-i-n Junction Synaptic Transistor for Environment-Responsive Action Control

The design of the first p-i-n junction synaptic transistor (JST) based on n-type TiO2 film covered with poly(methyl methacrylate) (PMMA) and with a p-type P3HT/PEO nanowire (NW) on top. Except for basic synaptic functions that can be realized by a single neurotransmitter, the electronic device emulates the multiplexed neurotransmission of different neurotransmissions, i.e., glutamate and acetylcholine, for fast switching between short- and long-term plasticity (STP and LTP). This is realized by the special p-i-n junction with hole transport in the p-type P3HT NW to form STP, and electron transport in the n-type TiO2 layer and trapped under the PMMA inversion layer to form LTP. Altering the external input induces changes of the polarity of the charge carriers in the conductive channel, promoting fast switching between STP and LTP modes. When stimulated using two parallel inputs, the response of PMMA/TiO2 emulates the synergistic effect of taste and aroma on the control of food-intake in the brain. Because of the bipolarity, the p-i-n JST has excellent reconfigurability, which importantly is attributed to simulate the plasticity of synapses and to mimic how distinct types of gustatory receptor neurons respond to different concentrations of salt. The electronic device lays the technical foundation for the realization of the future complex artificial neural networks.

Recent Process of Flexible Transistor-Structured Memory

Flexible transistor-structured memory (FTSM) has attracted great attention for its important role in flexible electronics. For nonvolatile information storage, FTSMs with floating-gate, charge-trap, and ferroelectric mechanisms have been developed. By introducing an optical sensory module, FTSM can be operated by optical inputs to function as an optical memory transistor. As a special type of FTSM, transistor-structured artificial synapse emulates important functions of a biological synapse to mimic brain-inspired memory behaviors and nervous signal transmissions. This work reviews the recent development of the above mentioned FTSMs, with a focus on working mechanism and materials, and flexibility.

Solution-processed electronics for artificial synapses

Artificial synaptic devices and systems have become hot topics due to parallel computing, high plasticity, integration of storage, and processing to meet the challenges of the traditional Von Neumann computers. Currently, two-terminal memristors and three-terminal transistors have been mainly developed for high-density storage with high switching speed and high reliability because of the adjustable resistivity, controllable ion migration, and abundant choices of functional materials and fabrication processes. To achieve the low-cost, large-scale, and easy-process fabrication, solution-processed techniques have been extensively employed to develop synaptic electronics towards flexible and highly integrated three-dimensional (3D) neural networks. Herein, we have summarized and discussed solution-processed techniques in the fabrication of two-terminal memristors and three-terminal transistors for the application of artificial synaptic electronics mainly reported in the recent five years from the view of fabrication processes, functional materials, electronic operating mechanisms, and system applications. Furthermore, the challenges and prospects were discussed in depth to promote solution-processed techniques in the future development of artificial synapse with high performance and high integration.

Lithography Processable Ta2O5 Barrier-Layered Chitosan Electric Double Layer Synaptic Transistors

We proposed a synaptic transistor gated using a Ta₂O₅ barrier-layered organic chitosan electric double layer (EDL) applicable to a micro-neural architecture system. In most of the previous studies, a single layer of chitosan electrolyte was unable to perform lithography processes due to poor mechanical/chemical resistance. To overcome this limitation, we laminated a high-k Ta₂O₅ thin film on chitosan electrolyte to ensure high mechanical/chemical stability to perform a lithographic process for micropattern formation. Artificial synaptic behaviors were realized by protonic mobile ion polarization in chitosan electrolytes. In addition, neuroplasticity modulation in the amorphous In–Ga–Zn-oxide (a-IGZO) channel was implemented by presynaptic stimulation. We also demonstrated synaptic weight changes through proton polarization, excitatory postsynaptic current modulations, and paired-pulse facilitation. According to the presynaptic stimulations, the magnitude of mobile proton polarization and the amount of weight change were quantified. Subsequently, the stable conductance modulation through repetitive potential and depression pulse was confirmed. Finally, we consider that proposed synaptic transistor is suitable for advanced micro-neural architecture because it overcomes the instability caused when using a single organic chitosan layer.

Flexible organic field-effect transistor arrays for wearable neuromorphic device applications

With the advent of wearable microelectronic devices in the interdisciplinary bio-electronics research field, synaptic devices with capability of neuromorphic computing are attracting more and more attention as the building blocks for the next generation computing structure. Conventional flash-like synaptic transistors are built on rigid solid-state substrates, and the inorganic materials and the high-temperature processing steps have severely limited their applications in various flexible electronic devices and systems. Here, flexible organic flash-like synaptic devices have been fabricated on a flexible substrate with the organic C8-BTBT as the conducting channel. The device exhibits a memory window greater than 20 V and excellent synaptic functions including short/long-term synaptic plasticity and spike-timing-dependent plasticity. In addition, even under the bending condition (7 mm bending radius), the transistor can still stably achieve a variety of synaptic functions. This work shows that low-temperature processing technology with the integration of organic materials can pave a promising pathway for the realization of flexible synaptic systems and the future development of wearable electronic devices.

Hardware implementation of photoelectrically modulated dendritic arithmetic and spike-timing-dependent plasticity enabled by an ion-coupling gate-tunable vertical 0D-perovskite/2D-MoS2 hybrid-dimensional van der Waals heterostructure

Brain-inspired nanodevices have been demonstrated to possess outstanding characteristics for implementing neuromorphic computing. Among these devices, photoelectrically modulated neuromorphic transistors are regarded as the basic building blocks for applications in emerging brain-like devices. However, to date, efficient optoelectronic-hybrid neuromorphic devices are still lacking. Because conventional transistors based on mono-semiconductor materials cannot absorb adequate light to ensure efficient light-matter interactions, they pose significant challenges to the synchronous processing of photoelectric information. Here, a novel photoelectrically modulated neuromorphic device based on an ion-coupling gate-tunable vertical 0D-CsPbBr3-quantum-dots/2D-MoS2 hybrid-dimensional van der Waals heterojunction is demonstrated by using a polymer ion gel electrolyte as the gate dielectric. A super-efficient heterojunction interface for photo-carrier transport is developed by integrating CsPbBr3 quantum dots with 2D-layered MoS2 semiconductors. We experimentally demonstrate that the drain-source current can be modulated by applying spikes to the drain and gate terminals, and the conductance can also be tuned by external light stimulus. Most importantly, photoelectrically modulated spiking Boolean logics, dendritic integrations in both temporal and spatial modes, and Hebbian learning rules can be successfully mimicked in our proposed hybrid-dimensional device using this intriguing optical and electrical synergy approach. These results suggest that the proposed device has great potential in intelligent cognitive systems and neuromorphic computing applications.

Flexible and Transparent Artificial Synapse Devices Based on Thin-Film Transistors with Nanometer Thickness

Background

Artificial synaptic behaviors are necessary to investigate and implement since they are considered to be a new computing mechanism for the analysis of complex brain information. However, flexible and transparent artificial synapse devices based on thin-film transistors (TFTs) still need further research.

Purpose

To study the application of flexible and transparent thin-film transistors with nanometer thickness on artificial synapses.

Materials and Methods

Here, we report the design and fabrication of flexible and transparent artificial synapse devices based on TFTs with polyethylene terephthalate (PET) as the flexible substrate, indium tin oxide (ITO) as the gate and a polyvinyl alcohol (PVA) grid insulating layer as the gate insulation layer at room temperature.

Results

The charge and discharge of the carriers in the flexible and transparent thin-film transistors with nanometer thickness can be used for artificial synaptic behavior.

Conclusion

In summary, flexible and transparent thin-film transistors with nanometer thickness can be used as pressure and temperature sensors. Besides, inherent charge transfer characteristics of indium gallium zinc oxide semiconductors have been employed to study the biological synapse-like behaviors, including synaptic plasticity, excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), and long-term memory (LTM). More precisely, the spike rate plasticity (SRDP), one representative synaptic plasticity, has been demonstrated. Such TFTs are interesting for building future neuromorphic systems and provide a possibility to act as fundamental blocks for neuromorphic system applications.

Solution-Processable Anion-doped Conjugated Polymer for Nonvolatile Organic Transistor Memory with Synaptic Behaviors

Brain-inspired synaptic transistors have been considered as a promising device for next-generation electronics. To mimic the behavior of a biological synapse, both data processing and nonvolatile memory capability are simultaneously required for a single electronic device. In this work, a simple approach to realize a synaptic transistor with improved memory characteristics is demonstrated by doping an ionic additive, tetrabutylammonium perchlorate (TBAP), into an active polymer semiconductor without using any extra charge storage layer. TBAP doping is first revealed to improve the memory window of a derived transistor memory device from 19 to 32 V (∼68% enhancement) with an on/off current ratio over 10³ at V_G = -10 V. Through morphological analysis and theoretical calculations, it is revealed that the association of anion with polymers enhances the charge retention capability of the polymer and facilitates the interchain interactions to result in improved memory characteristics. More critically, the doped device is shown to successfully mimic the synaptic behaviors, such as paired-pulse facilitation (PPF), excitatory and inhibitory postsynaptic currents, and spike-rate dependent plasticity. Notably, the TBAP-doped device is shown to deliver a PPF index of up to 204% in contrast to the negligible value of an undoped device. This study describes a novel approach to prepare a synaptic transistor by doping conjugated polymers, which can promote the future development of artificial neuromorphic systems.

Implementation of an electrically modifiable artificial synapse based on ferroelectric field-effect transistors using Al-doped HfO2 thin films

Human brain-like synaptic behaviors of the ferroelectric field-effect transistors (FeFETs) were emulated by introducing the metal-ferroelectric-metal-insulator-semiconductor (MFMIS) gate stacks employing Al-doped HfO2 (Al:HfO2) ferroelectric thin films even at a low operation voltage. The synaptic plasticity of the MFMIS-FETs could be gradually modulated by the partial polarization characteristics of the Al:HfO2 thin films, which were examined to be dependent on the applied pulse conditions. Based on the ferroelectric polarization switching dynamics of the Al:HfO2 thin films, the proposed devices successfully emulate biological synaptic functions, including excitatory post-synaptic current (EPSC), paired-pulse facilitation (PPF), and spike timing-dependent plasticity (STDP). The channel conductance of the FeFETs could be controlled by partially switching the ferroelectric polarization of the Al:HfO2 gate insulators by means of pulse-number and pulse-amplitude modulations. Furthermore, the 3 × 3 array integrated with the Al:HfO2 MFMIS-FETs was also fabricated, in which electrically modifiable weighted-sum operation could be well verified in the 3 × 3 synapse array configuration.

Multi-Bit Biomemory Based on Chitosan: Graphene Oxide Nanocomposite with Wrinkled Surface

Chitosan (CS) is one of the commonly affluent polysaccharides that are attractive biomaterials as they are easily found in different organisms and are biocompatible. An environment-friendly multi-bit biomemory was successfully achieved on the basis of CS as a favorable candidate for resistive-switching memory applications. By incorporating graphene oxide (GO) into CS, the multi-bit biomemory device (indium tin oxide (ITO)/CS:GO/Ni) was obtained through the solution-processable method, which had a high current ratio among a high, intermediate, and low resistance state as well as a low SET/RESET voltage. GO acting as trapping sites in the active layer might be responsible for the biomemory mechanism. This research opens up a new avenue towards renewable and environmentally benign CS-based materials for biodegradable electronic devices.

Artificial Tactile Perceptual Neuron with Nociceptive and Pressure Decoding Abilities

The neural system is a multifunctional perceptual learning system. Our brain can perceive different kinds of information to form senses, including touch, sight, hearing, and so on. Mimicking such perceptual learning systems is critical for neuromorphic platform applications. Here, an artificial tactile perceptual neuron is realized by utilizing electronic skins (E-skin) with oxide neuromorphic transistors, and this artificial tactile perceptual neuron successfully simulates biological tactile afferent nerves. First, the E-skin device is constructed using microstructured polydimethylsiloxane membranes coated with Ag/indium tin oxide (ITO) layers, exhibiting good sensitivities of ∼2.1 kPa^-1 and fast response time of tens of milliseconds. Then, the chitosan-based electrolyte-gated ITO neuromorphic transistor is fabricated and exhibits high performance and synaptic responses. Finally, the integrated artificial tactile perceptual neuron demonstrates pressure excitatory postsynaptic current and paired-pulse facilitation. The artificial tactile perceptual neuron is featured with low energy consumption as low as ∼0.7 nJ. Moreover, it can mimic acute and chronic pain and nociceptive characteristics of allodynia and hyperalgesia in biological nociceptors. Interestingly, the artificial tactile perceptual neuron can employ "Morse code" pressure-interpreting scheme. This simple and low-cost approach has excellent potential for applications including but not limited to intelligent humanoid robots and replacement neuroprosthetics.

Flexible Neuromorphic Electronics for Computing, Soft Robotics, and Neuroprosthetics

Flexible neuromorphic electronics that emulate biological neuronal systems constitute a promising candidate for next-generation wearable computing, soft robotics, and neuroprosthetics. For realization, with the achievement of simple synaptic behaviors in a single device, the construction of artificial synapses with various functions of sensing and responding and integrated systems to mimic complicated computing, sensing, and responding in biological systems is a prerequisite. Artificial synapses that have learning ability can perceive and react to events in the real world; these abilities expand the neuromorphic applications toward health monitoring and cybernetic devices in the future Internet of Things. To demonstrate the flexible neuromorphic systems successfully, it is essential to develop artificial synapses and nerves replicating the functionalities of the biological counterparts and satisfying the requirements for constructing the elements and the integrated systems such as flexibility, low power consumption, high-density integration, and biocompatibility. Here, the progress of flexible neuromorphic electronics is addressed, from basic backgrounds including synaptic characteristics, device structures, and mechanisms of artificial synapses and nerves, to applications for computing, soft robotics, and neuroprosthetics. Finally, future research directions toward wearable artificial neuromorphic systems are suggested for this emerging area.

Modulation of Binary Neuroplasticity in a Heterojunction-Based Ambipolar Transistor

To keep pace with the upcoming big-data era, the development of a device-level neuromorphic system with highly efficient computing paradigms is underway with numerous attempts. Synaptic transistors based on an all-solution processing method have received growing interest as building blocks for neuromorphic computing based on spikes. Here, we propose and experimentally demonstrated the dual operation mode in poly{2,2-(2,5-bis(2-octyldodecyl)-3,6-dioxo-2,3,5,6-tetrahydropyrrolo[3,4-c]pyrrole-1,4-diyl)dithieno[3,2-b]thiophene-5,5-diyl-alt-thiophen-2,5-diyl}(PDPPBTT)/ZnO junction-based synaptic transistor from ambipolar charge-trapping mechanism to analog the spiking interfere with synaptic plasticity. The heterojunction formed by PDPPBTT and ZnO layers serves as the basis for hole-enhancement and electron-enhancement modes of the synaptic transistor. Distinctive synaptic responses of paired-pulse facilitation (PPF) and paired-pulse depression (PPD) were configured to achieve the training/recognition function for digit image patterns at the device-to-system level. The experimental results indicate the potential application of the ambipolar transistor in future neuromorphic intelligent systems.

Biomemristic Behavior for Water-Soluble Chitosan Blended with Graphene Quantum Dot Nanocomposite

Bionanocomposite has promising biomemristic behaviors for data storage inspired by a natural biomaterial matrix. Carboxylated chitosan (CCS), a water-soluble derivative of chitosan avoiding the acidic salt removal, has better biodegradability and bioactivity, and is able to absorb graphene quantum dots (GQDs) employed as charge-trapping centers. In this investigation, biomemristic devices based on water-soluble CCS:GQDs nanocomposites were successfully achieved with the aid of the spin-casting method. The promotion of binary biomemristic behaviors for Ni/CCS:GQDs/indium-tin-oxide (ITO) was evaluated for distinct weight ratios of the chemical components. Fourier transform infrared spectroscopy, Raman spectroscopy (temperature dependence), thermogravimetric analyses and scanning electron microscopy were performed to assess the nature of the CCS:GQDs nanocomposites. The fitting curves on the experimental data further confirmed that the conduction mechanism might be attributed to charge trapping-detrapping in the CCS:GQDs nanocomposite film. Advances in water-soluble CCS-based electronic devices would open new avenues in the biocompatibility and integration of high-performance biointegrated electronics.

Threshold-Tunable, Spike-Rate-Dependent Plasticity Originating from Interfacial Proton Gating for Pattern Learning and Memory

Recently, neuromorphic devices have been receiving increasing interest in the field of artificial intelligence (AI). Realization of fundamental synaptic plasticities on hard-ware devices would endow new intensions for neuromorphic devices. Spike-rate-dependent plasticity (SRDP) is one of the most important synaptic learning mechanisms in brain cognitive behaviors. It is thus interesting to mimic the SRDP behaviors on solid-state neuromorphic devices. In the present work, nanogranular phosphorus silicate glass (PSG)-based proton conductive electrolyte-gated oxide neuromorphic transistors have been proposed. The oxide neuromorphic transistors have good transistor performances and frequency-dependent synaptic plasticity behavior. Moreover, the neuromorphic transistor exhibits SRDP activities. Interestingly, by introducing priming synaptic stimuli, the modulation of threshold frequency value distinguishing synaptic potentiation from synaptic depression is realized for the first time on an electrolyte-gated neuromorphic transistor. Such a mechanism can be well understood with interfacial proton gating effects of the nanogranular PSG-based electrolyte. Furthermore, the effects of SRDP learning rules on pattern learning and memory behaviors have been conceptually demonstrated. The proposed neuromorphic transistors have potential applications in neuromorphic engineering.

All-metal oxide synaptic transistor with modulatable plasticity

The artificial neural system has attracted tremendous attention in the field of artificial intelligence due to operate mode of parallel computation which is superior to traditional Von Neumann computers in processing complex sensory data and real-time situations with extremely low power dissipation. Remarkable progress has been made in the hardware-based electric-double-layer synaptic transistors as its modulation by ion movement is similar to biological synapse for the past few years. Unfortunately, long-term potentiation (LTP) timescale is still a big challenge in hardware-based electric-double-layer synaptic transistors which is essential to processing capacity and memory formation. Meanwhile, the effect of ion concentration on the synaptic plasticity has rarely been reported. Here, a solid state electrolyte-gated transistor using Ta₂O₅ as dielectric layer with unique ionic composition was demonstrated and the regulation of synaptic weight was realized by changing ion concentration. Both the potentiation and depression of synaptic weight such as excitatory post-synaptic current, inhibitory response (IPSC), paired pulse facilitation as well as LTP were successfully simulated. More importantly, oxygen vacancy content was tuned for the first time to modulate synaptic plasticity by varying film thickness and gas ratio, through which the intensity and duration of memory were enhanced with appropriate vacancy concentration. It indicated that appropriate vacancy concentration avoided the effects of internal electric field induced by ion excess, leading to a long-term memory. These results reveal a promising path to improve memory capacity of artificial synapse via ion modulation.

Artificial Synapse Emulated through Fully Aqueous Solution-Processed Low-Voltage In2O3 Thin-Film Transistor with Gd2O3 Solid Electrolyte

Brain-like neuromorphic computing system provides an alternative approach for the future computer for its characteristics of high-efficiency, power-efficient, self-learning, and parallel computing. Therefore, the imitation of synapse behavior based on microelectronics is particularly important. Recently, the synaptic transistors have received widespread attention. Among them, solid oxide-based synaptic transistors are more compatible with the large-scale fabrication than the liquid and organic-based transistors. So the development of oxide synaptic transistor is required. Here, a novel aqueous solution-processed Gd₂O₃ is suggested to be the solid electrolyte for synaptic transistors. The microstructure and the dielectric properties of Gd₂O₃ film are investigated, which show the potential for the simulation of synaptic transmission. Then, the fully aqueous solution-processed In₂O₃/Gd₂O₃ thin-film transistor (TFT) is fabricated. The device exhibits an acceptable electrical performance with a small threshold voltage of 1.24 V, and a small subthreshold swing of 0.12 V/decade. The artificial synapse behavior is stimulated and the short-term plasticity of In₂O₃/Gd₂O₃ TFT is studied. The dependence of its excitatory postsynaptic current on presynaptic pulse magnitude, width, and frequency is verified. Besides, the synapse behavior of devices under continuous illumination stresses is investigated. The lights with different photon energy have different effects on the synaptic transmission, which is related to the ionization of oxygen vacancies. Our results demonstrate that fully aqueous solution-processed In₂O₃ TFT with Gd₂O₃ solid electrolyte is a candidate for the synaptic transistor.

Solution-Processed, Electrolyte-Gated In2O3 Flexible Synaptic Transistors for Brain-Inspired Neuromorphic Applications

Emulating the essential synaptic behaviors using single synaptic transistor has attracted extensive attention for building the brain-inspired neuromorphic systems. However, few reports on synaptic transistors fabricated by solution processes have been reported. In this article, the indium oxide synaptic transistors based on polyimide substrates were fabricated by a nontoxic water-inducement method at a low temperature, and lithium perchlorate (LiClO₄) was dissolved in polyethylene oxide as the gate electrolyte. For water-inducement process, comparable electrical properties of the synaptic transistors can be achieved by prolonging the annealing time rather than high-temperature annealing with a relatively short time. The effect of the annealing time on the electrical performance of the electrolyte-gated transistors annealed at various temperatures was investigated. It is found that the electrolyte-gated-synaptic transistor on polyimide substrate annealed at 200 °C exhibits high electrical performance and good mechanical stability. Due to the ion migration relaxation dynamics in the polymer electrolyte, various important synaptic behaviors such as the excitatory postsynaptic current, paired-pulse facilitation, high-pass filtering characteristics, and long-term memory performance were successfully mimicked. The electrolyte-gated synaptic transistors based on solution-processed In₂O₃ exhibit great potential in neuromorphological applications.