Semiconductor Quantum Dots for Memories and Neuromorphic Computing Systems

Multilevel resistive switching in hydrothermally synthesized FeWO4 thin film-based memristive device for non-volatile memory application

The memristors offer significant advantages as a key element in non-volatile and brain-inspired neuromorphic systems because of their salient features such as remarkable endurance, ability to store multiple bits, fast operation speed, and extremely low energy usage. This work reports the resistive switching (RS) characteristics of the hydrothermally synthesized iron tungstate (FeWO4) based thin film memristive device. The detailed physicochemical analysis was investigated using Rietveld's refinement, X-ray photoelectron spectroscopy (XPS), field emission scanning electron microscopy (FE-SEM), and transmission electron microscopy (TEM) techniques. The fabricated Ag/FWO/FTO memristive device exhibits bipolar resistive switching (BRS) behavior. In addition, the devices exhibit negative differential resistance (NDR) at both positive and negative bias. The charge-flux relation portrayed the non-ideal or memristive nature of the devices. The reliability in the RS process was analyzed in detail using Weibull distribution and time series analysis techniques. The device exhibits stable and multilevel endurance and retention characteristics which demonstrates the suitability of the device for the high-density non-volatile memory application. The current conduction of the device was dominated by Ohmic and trap controlled-space charge limited current (TC-SCLC) mechanisms and filamentary RS process responsible for the BRS in the device. In a nutshell, the present investigations reveal the potential use of the iron tungstate for the fabrication of memristive devices for the non-volatile memory application.

Observation of anodic electrochemiluminescence from silicon quantum dots for the detection of hydrogen peroxide

Silicon quantum dots (QDs) with stable positively charged intermediates are prepared using chemical etching to generate strong anodic electrochemiluminescence (ECL) under a positive potential. Their surfaces could be passivated in the presence of strong oxidants, leading to enhanced ECL and offering the ability to carry out analysis for hydrogen peroxide.

Investigation of Resistance Switching and Synaptic Properties of VO x for Neuromorphic Applications

The taking run on artificial intelligence in the last decades is based on the von Neumann architecture where memory and computation units are separately located from each other. This configuration causes a large amount of energy and time to be dissipated during data transfer between these two units, in contrast to synapses in biological neurons. A new paradigm has been proposed inspired by biological neurons in human brains, known as neuromorphic computing. Due to the unusual current-voltage characteristic of memristor devices such as pinched hysteresis loops, memristors are considered a key element of neuromorphic architecture. In this study, we report the basic current-voltage characteristic of the memristor devices in the form of Si/SiO2/Pt(30 nm)/VO x (3, 13, 25 nm)/Pt (30 nm) sandwich structure. Synaptic functions such as spike-time-dependent plasticity (STDP), paired-pulse facilitation (PPF), long-term potentiation (LTP), and long-term depression (LTD) of memristor devices were examined in detail. The oxide layer VO x has been grown by using the VO2 target in a pulsed laser deposition (PLD) chamber. The composition and oxidation states of the oxide layer were examined using the X-ray photoelectron spectroscopy (XPS) technique. The status of oxygen vacancies, which play an active role in the operation of the devices, was examined with a photoluminescence (PL) technique. The experimental results showed that the thickness of the oxide layer can significantly influence the synaptic and resistive switching properties of the devices.

Highly Sensitive, Low-Energy-Consumption Biomimetic Olfactory Synaptic Transistors Based on the Aggregation of the Semiconductor Films

Artificial olfactory synaptic devices with low energy consumption and low detection limits are important for the further development of neuromorphic computing and intelligent robotics. In this work, an ultralow energy consumption and low detection limit imitation olfactory synaptic device based on organic field-effect transistors (OFETs) was prepared. The aggregation state of poly(diketopyrrolopyrrole-selenophene) (PTDPP) semiconductor films is modulated by adding unfavorable solvents and annealing treatments to obtain excellent charge transfer and gas synaptic properties. The regulated OFET device can execute basic biological synaptic functions, including excitatory postsynaptic currents (EPSCs), paired-pulse facilitation (PPF), and the transition from short-term to long-term plasticity, at an ultralow operating voltage of -0.0005 V. The ultralow energy consumption during the biomimetic simulation is in the range of 8.94-88 fJ per spike. Noteworthily, the gas detection limit of the device is as low as 50 ppb, well below normal human NO2 gas perception limits (100-1000 ppb). Additionally, high-pass filtering, Pavlovian conditioned reflexes, and decoding of "Morse code" were simulated. Finally, a grid-free conformal device with outstanding flexibility and stability was fabricated. In conclusion, the control of semiconductor thin-film aggregation provides effective guidance for preparing low-energy-consumption, highly sensitive olfactory nerve-mimicking devices and promoting the development of wearable electronics.

Memristive Switching Mechanism in Colloidal InP/ZnSe/ZnS Quantum Dot-Based Synaptic Devices for Neuromorphic Computing

Quantum dots (QDs) have garnered a significant amount of attention as promising memristive materials owing to their size-dependent tunable bandgap, structural stability, and high level of applicability for neuromorphic computing. Despite these advantageous properties, the development of QD-based memristors has been hindered by challenges in understanding and adjusting the resistive switching (RS) behavior of QDs. Herein, we propose three types of InP/ZnSe/ZnS QD-based memristors to elucidate the RS mechanism, employing a thin poly(methyl methacrylate) layer. This approach not only allows us to identify which carriers (electron or hole) are trapped within the QD layer but also successfully demonstrates QD-based synaptic devices. Furthermore, to utilize the QD memristor as a synapse, long-term potentiation/depression (LTP/LTD) characteristics are measured, resulting in a low nonlinearity of LTP/LTD at 0.1/1. On the basis of the LTP/LTD characteristics, single-layer perceptron simulations were performed using the Extended Modified National Institute of Standards and Technology, verifying a maximum recognition rate of 91.46%.

Transient N-GQDs/PVA nanocomposite thin film for memristor application

In recent years quantum dot (QDs) based resistive switching devices(memristors) have gained a lot of attention. Here we report the resistive switching behavior of nitrogen-doped graphene quantum dots/Polyvinyl alcohol (N-GQDs/PVA) degradable nanocomposite thin film with different weight percentages (wt.%) of N-GQDs. The memristor device was fabricated by a simple spin coating technique. It was found that 1 wt% N-GQDs/PVA device shows a prominent resistive switching phenomenon with good cyclic stability, high on/off ratio of ~102and retention time of ∼104s. From a detailed experimental study of band structure, we conclude that memristive behavior originates from the space charge controlled conduction (SCLC) mechanism. Further transient property of built memristive device was studied. Within three minutes of being submerged in distilled water, the fabricated memory device was destroyed. This phenomenon facilitates the usage of fabricated memristor devices to develop memory devices for military and security purposes.

Interface engineering in ZnO/CdO hybrid nanocomposites to enhanced resistive switching memory for neuromorphic computing

Resistive random-access memory (RRAMs) has attracted significant interest for their potential applications in embedded storage and neuromorphic computing. Materials based on metal chalcogenides have emerged as promising candidates for the fulfilment of these requirements. Due to its ability to manipulate electronic states and control trap states through controlled compositional dynamics, metal chalcogenide RRAM has excellent non-volatile resistive memory properties. In the present we have synthesized ZnO-CdO hybrid nanocomposite by using hydrothermal method as an active layer. The Ag/C15ZO/Pt hybrid nanocomposite structure memristors showed electrical properties similar to biological synapses. The device exhibited remarkably stable resistive switching properties that have a low SET/RESET (0.41/-0.2) voltage, a high RON/OFF ratio of approximately 105, a high retention stability, excellent endurance reliability up to 104 cycles and multilevel device storage performance by controlling the compliance current. Furthermore, they exhibited an impressive performance in terms of emulating biological synaptic functions, which include long-term potentiation (LTP), long-term depression (LTD), and paired-pulse facilitation (PPF), via the continuous modulation of conductance. The hybrid nanocomposite memristors notably achieved an impressive recognition accuracy of up to 92.6 % for handwritten digit recognition under artificial neural network (ANN). This study shows that hybrid-nanocomposite memristor performance could lead to efficient future neuromorphic architectures.

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.

Technology and Integration Roadmap for Optoelectronic Memristor

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.

Tailoring Classical Conditioning Behavior in TiO2 Nanowires: ZnO QDs-Based Optoelectronic Memristors for Neuromorphic Hardware

Neuromorphic hardware equipped with associative learning capabilities presents fascinating applications in the next generation of artificial intelligence. However, research into synaptic devices exhibiting complex associative learning behaviors is still nascent. Here, an optoelectronic memristor based on Ag/TiO2 Nanowires: ZnO Quantum dots/FTO was proposed and constructed to emulate the biological associative learning behaviors. Effective implementation of synaptic behaviors, including long and short-term plasticity, and learning-forgetting-relearning behaviors, were achieved in the device through the application of light and electrical stimuli. Leveraging the optoelectronic co-modulated characteristics, a simulation of neuromorphic computing was conducted, resulting in a handwriting digit recognition accuracy of 88.9%. Furthermore, a 3 × 7 memristor array was constructed, confirming its application in artificial visual memory. Most importantly, complex biological associative learning behaviors were emulated by mapping the light and electrical stimuli into conditioned and unconditioned stimuli, respectively. After training through associative pairs, reflexes could be triggered solely using light stimuli. Comprehensively, under specific optoelectronic signal applications, the four features of classical conditioning, namely acquisition, extinction, recovery, and generalization, were elegantly emulated. This work provides an optoelectronic memristor with associative behavior capabilities, offering a pathway for advancing brain-machine interfaces, autonomous robots, and machine self-learning in the future.

Quantitative Analysis of Resistance to Deformation of the DNA Origami Framework Supported by Struts

Nanostructures with controlled shapes are of particular interest due to their consistent physical and chemical properties and their potential for assembly into complex superstructures. The use of supporting struts has proven to be effective in the construction of precise DNA polyhedra. However, the influence of struts on the structure of DNA origami frameworks on the nanoscale remains unclear. In this study, we developed a flexible square DNA origami (SDO) framework and enhanced its structural stability by incorporating interarm supporting struts (SDO-s). Comparing the framework with and without such struts, we found that SDO-s demonstrated a significantly improved resistance to deformation. We assessed the deformability of these two DNA origami structures through the statistical analysis of interior angles of polygons based on atomic force microscopy and transmission electron microscopy data. Our results showed that SDO-s exhibited more centralized interior angle distributions compared to SDO, reducing from 30-150° to 60-120°. Furthermore, molecular dynamics simulations indicated that supporting struts significantly decreased the thermodynamic fluctuations of the SDO-s, as described by the root-mean-square fluctuation parameter. Finally, we experimentally demonstrated that the 2D arrays assembled from SDO-s exhibited significantly higher quality than those assembled from SDO. These quantitative analyses provide an understanding of how supporting struts can enhance the structural integrity of DNA origami frameworks.

Quasi-2D Lead-Tin Perovskite Memory Devices Fabricated by Blade Coating

Two terminal passive devices are regarded as one of the promising candidates to solve the processor-memory bottleneck in the Von Neumann computing architectures. Many different materials are used to fabricate memory devices, which have the potential to act as synapses in future neuromorphic electronics. Metal halide perovskites are attractive for memory devices as they display high density of defects with a low migration barrier. However, to become promising for a future neuromorphic technology, attention should be paid on non-toxic materials and scalable deposition processes. Herein, it is reported for the first time the successful fabrication of resistive memory devices using quasi-2D tin-lead perovskite of composition (BA)2 MA4 (Pb0.5 Sn0.5 )5 I16 by blade coating. The devices show typical memory characteristics with excellent endurance (2000 cycles), retention (105  s), and storage stability (3 months). Importantly, the memory devices successfully emulate synaptic behaviors such as spike-timing-dependent plasticity, paired-pulse facilitation, short-term potentiation, and long-term potentiation. A mix of slow (ionic) transport and fast (electronic) transport (charge trapping and de-trapping) is proven to be responsible for the observed resistive switching behavior.

Hierarchies in Visual Pathway: Functions and Inspired Artificial Vision

The development of artificial intelligence has posed a challenge to machine vision based on conventional complementary metal-oxide semiconductor (CMOS) circuits owing to its high latency and inefficient power consumption originating from the data shuffling between memory and computation units. Gaining more insights into the function of every part of the visual pathway for visual perception can bring the capabilities of machine vision in terms of robustness and generality. Hardware acceleration of more energy-efficient and biorealistic artificial vision highly necessitates neuromorphic devices and circuits that are able to mimic the function of each part of the visual pathway. In this paper, we review the structure and function of the entire class of visual neurons from the retina to the primate visual cortex within reach (Chapter 2) are reviewed. Based on the extraction of biological principles, the recent hardware-implemented visual neurons located in different parts of the visual pathway are discussed in detail in Chapters 3 and 4. Furthermore, valuable applications of inspired artificial vision in different scenarios (Chapter 5) are provided. The functional description of the visual pathway and its inspired neuromorphic devices/circuits are expected to provide valuable insights for the design of next-generation artificial visual perception systems.

Acid selenites as new selenium precursor for CdSe quantum dot synthesis

Chemical precursors for nanomaterials synthesis have become essential to tune particle size, composition, morphology, and unique properties. New inexpensive precursors investigation that precisely controls these characteristics is highly relevant. We studied new Se precursors, the acid selenites (R-O-SeOOH), to synthesize CdSe quantum dots (QDs). They were produced at room temperature by the Image 1 reaction with alcohols having different alkyl chains and were characterized by 1H NMR confirming their structures. This unprecedented precursor generates high-quality CdSe nanocrystals with narrow size distribution in the zinc-blend structure showing controlled optical properties. Advanced characterization detailed the CdSe structure showing stacking fault defects and its dependence on the used R-O-SeOOH. The QDs formation was examined using a time-dependent growth kinetics model. Differences in the nanoparticle surface structure influenced the optical properties, and they were correlated to the Se-precursor nature. Small alkyl chain acid selenites generally lead to more controlled QDs morphology, while the bigger alkyl chain leads to slightly upper quantum yields. Acid selenites can potentially replace Se-precursors at competitive costs in the metallic chalcogenide nanoparticles. Image 1 is chemically stable, and alcohols are cheap and less toxic than the reactants used today, making acid selenites a more sustainable Se precursor.

MoS2 Quantum Dot-Optimized Conductive Channels for a Conjugated Polymer-Based Synaptic Memristor

Donor-acceptor-type conjugated polymers are widely used in memristors due to their unique push-pull electron structures and charge transfer mechanisms. However, the inherently inhomogeneous microstructure of polymer films and their low crystallinity produce randomness that destabilizes formed conductive channels, giving polymer-based memristors unstable switching behavior. In this contribution, we prepared a synaptic device based on PM6-MoS2 QD (molybdenum disulfide quantum dot) nanocomposites. In the composites, MoS2 QDs provided the active centers for forming conductive channels via electron trapping and detrapping. They also controlled the directional formation of conductive channels between PM6 and MoS2 QDs, reducing randomness and giving devices a narrow switching voltage range and cycling longevity. The device exhibited continuous multistage conductance states under a direct current voltage sweep and simulated a variety of synaptic functions, including long-term potentiation, long-term depression, short-term potentiation, short-term depression, paired-pulse facilitation, spiking-rate-dependent plasticity, and "learning experience" behavior. The memristor could also perform arithmetic, including "counting" and "subtraction" operations. This work provides a new approach to improving the performance of memristors for neuromorphic computing.

Bidirectional Invisible Photoresponse Implemented in a Traps Matrix-Combination toward Fully Optical Artificial Synapses

Fully optical artificial synapses are crucial hardware for neuromorphic computing, which is very promising to address the future large-scale computing capacity problem. The key characteristic required in a semiconductor device to emulate synaptic potentiation and depression in a fully optical artificial synapse is the bidirectional photoresponse. This work integrates wide-band-gap TiO2 polycrystals and narrow-band-gap PbS quantum dots into a graphene transistor simultaneously, providing the device with both near-ultraviolet and near-infrared photoresponses through the photogating effect. Moreover, the TiO2 serves as a hole-trapping matrix and the PbS as an electron-trapping matrix, which impose opposite effects to the device after photoexcitation, resulting in a photoresponse in the opposite polarity. As a result, the device demonstrates a wavelength-dependent bidirectional photoresponse, which enables it to be utilized as a fully optical artificial synapse. By using near-ultraviolet or near-infrared lights as stimuli, the device successfully mimics synaptic plasticity, including synaptic potentiation/depression, paired-pulse facilitation, and spike-rating-dependent plasticity, as well as the human brain-like transition of short-term memory and long-term memory and learning-experience behavior. This work validates the methodology of combining different trap matrices to achieve the bidirectional photoresponse, which can significantly inspire future research in fully optical artificial synapses.

Bioinspired theranostic quantum dots: Paving the road to a new paradigm for cancer diagnosis and therapeutics

Despite extensive research, a complete cure remains lacking for most types of cancer. Nanotechnology-based carriers, such as liposomes, nanoparticles (NPs), dendrimers, nanoemulsions, and other nanocarriers, can target cancer cells, but their in vivo fate is unpredictable. Bioinspired quantum dots (BQDs) offer enhanced aqueous solubility, exceptionally low toxicity, biocompatibility, easy biofunctionalization, and selective cancer targeting. Due to their photoluminescence, high longitudinal relaxation value, photothermal effect upon laser irradiation, generation of singlet oxygen, and production of H2S for gas therapy, BQDs are excellent cancer theranostic agents. In this review, we highlight the theranostic application of, and existing challenges relating to BQDs.

Coexistent, Competing Tunnelling, and Hopping Charge Transport in Compressed Metal Nanocluster Crystals

Understanding charge transport among metal particles with sizes of approximately 1 nm poses a great challenge due to the ultrasmall nanosize, yet it holds great significance in the development of innovative materials as substitutes for traditional semiconductors, which are insulative and unstable in less than ∼10 nm thickness. Herein, atomically precise gold nanoclusters with well-defined compositions and structures were investigated to establish a mathematical relation between conductivity and interparticle distance. This was accomplished using high-pressure in situ resistance characterizations, synchrotron X-ray diffraction (XRD), and the Murnaghan equation of state. Based on this precise correlation, it was predicted that the conductivity of Au25(SNap)18 (SNap: 1-naphthalenethiolate) solid is comparable to that of bulk silver when the interparticle distance is reduced to approximately 3.6 Å. Furthermore, the study revealed the coexisting, competing tunneling, and incoherent hopping charge transport mechanisms, which differed from those previously reported. The introduction of conjugation-structured ligands, tuning of the structures of metal nanoclusters, and use of high-pressure techniques contributed to enhanced conductivity, and thus, the charge carrier types were determined using Hall measurements. Overall, this study provides valuable insight into the charge transport in gold nanocluster solids and represents an important advancement in metal nanocluster semiconductor research.

Porous crystalline materials for memories and neuromorphic computing systems

Porous crystalline materials usually include metal-organic frameworks (MOFs), covalent organic frameworks (COFs), hydrogen-bonded organic frameworks (HOFs) and zeolites, which exhibit exceptional porosity and structural/composition designability, promoting the increasing attention in memory and neuromorphic computing systems in the last decade. From both the perspective of materials and devices, it is crucial to provide a comprehensive and timely summary of the applications of porous crystalline materials in memory and neuromorphic computing systems to guide future research endeavors. Moreover, the utilization of porous crystalline materials in electronics necessitates a shift from powder synthesis to high-quality film preparation to ensure high device performance. This review highlights the strategies for preparing porous crystalline materials films and discusses their advancements in memory and neuromorphic electronics. It also provides a detailed comparative analysis and presents the existing challenges and future research directions, which can attract the experts from various fields (e.g., materials scientists, chemists, and engineers) with the aim of promoting the applications of porous crystalline materials in memory and neuromorphic computing systems.

Physical probing of quantum energy levels in a single indium arsenide (InAs) quantum dot

Indium arsenide (InAs) quantum dots (QDs) grown by molecular beam epitaxy (EBM) on gallium arsenide (GaAs) substrates have exhibited quantized charge-trapping characteristics. An electric charge can be injected in a single QD by a gold-coated AFM nano-probe placed directly on it using a conductive-mode atomic force microscope (C-AFM). The results revealed separate current-voltage (I-V) curves during consecutive measurements, where the turn-on voltages measured at the subsequent voltage sweeps are incrementally lower than that at the initial sweep. We demonstrate that the charge state of the QD can change over a long enough time by measuring the I-V data on the same QD at different time intervals. Discrete energy states (here, five states) have been observed due to the quantized charge leakage from the QD into the surrounding materials. These quantum states with five energy levels have been verified using quantum theory analysis of the quantum-well with the help of a numerical simulation model, which depends on the QD dimensions. The size of the quantum-well in the model is in good agreement with the actual QD size, whose lateral dimension is confirmed using a scanning electron microscope. At the same time, the height is estimated from the atomic force microscope topography.

Tailoring Wavelength-Adaptive Visual Neuroplasticity Transitions of Synaptic Transistors Comprising Rod-Coil Block Copolymers for Dual-Mode Photoswitchable Learning/Forgetting Neural Functions

The vision-inspired artificial neural network based on optical synapses has drawn a tremendous amount of attention for emulating biological senses. Although photoexcitation-induced synaptic functionalities have been widely studied, optical habituation via the photoinhibitory pathway is yet to be demonstrated for sophisticated biomimetic visual adaptive systems. Here, the first optical neuromorphic block copolymer (BCP) phototransistor is demonstrated as an all-optical operation responding to various wavelengths, fulfilling photoassisted dynamic learning/forgetting cycles via optical potentiation without gate bias. The polyfluorene BCPs were precisely designed to enable wavelength-adaptive responses, benefiting from interfacial semiconductor/electret morphology and the crystallinity/electron affinity of the BCPs. Notably, this is the first work to simultaneously exhibit fully light-controlled short- and long-term memory based on organic material systems. The device presents a high current contrast above 100-fold and long-term retention over 104 s. As a proof-of-concept for neural networks, a 6 × 6 array of photosynapses performed outstanding visual pattern learning/forgetting with high accuracy. This study exploits the design strategy of a conjugated BCP electret to unleash the full potential of wavelength-adaptive visual neuroplasticity transitions. It provides an effective architecture for designing high-performance and high-storage capacity required applications in next-generation neuromorphic systems.

Zero Thermal Quenching Phenomenon of Green Emitting Carbon Dots with High Biocompatibility and Stable Multicolor Biological Imaging in a Hot Environment

Carbon dots are emerging fluorescent nanomaterials with unique physical and chemical properties and a wide range of applications. Herein, we have designed and successfully synthesized thermally stable green emissive nitrogen-doped carbon dots (NCDs) with a photoluminescent quantum yield of 11.32% through facile solvent-free carbonization. NCDs demonstrated zero thermal quenching upon various temperatures modulating from 20 to 80 °C. The green emissive NCDs perform very stably even after heating them at 80 °C for 1 h. The thermal stability mechanism demonstrates that C═O and C═N functional groups control the particle aggregation and protect the fluorescent hub from photo-oxidation and thermal oxidation. Highly biocompatible CDs exhibit bright, stable, and multicolor emissions in T-ca cells under hot circumstances (25-45 °C). Additionally, NCDs offer long-term stability in the biosystem, as evidenced by the fact that the cell retains its brightness about 70% after prolonging the incubation time to 8 days. Furthermore, the fluorescent NCDs are utilized as in vivo imaging agents in the hot environment as they display bright and thermally stable imaging (27-45 °C) under 488 nm excitation. The results confirmed that the produced thermally stable NCDs could be used in biology and related medical fields that require hot environment imaging.

Helical Nanofiber Photoelectric Synaptic Devices for an Artificial Vision Nervous System

Inspired by the helical structure and the resultant exquisite functions of biomolecules, helical polymers have received increasing attention. Here, a series of poly(3-hexylthiophene)-block-poly(phenyl isocyanide) (P3HT-b-PPI) copolymers were prepared using a simple one-pot living polymerization method. Interestingly, the P3HT80-b-PPI30 films were found to have a helical nanofiber structure. The corresponding device has superior optoelectronic properties, such as a broadened spectral response range from the visible band to the deep ultraviolet (DUV) and an approximately 5-fold longer carrier decay time after DUV light stimulation. An energy consumption of 1.44 fJ per synaptic event was obtained, which is the lowest energy consumption achieved so far with DUV light stimulation. The encryption and decryption of images are implemented using an array of devices. Finally, a photoreceptor neural pathway was constructed to achieve early warning for the recognition of the display of harmful light. This research provides an effective strategy for the development of a novel optoelectronic synaptic device.

Quantum dots derived from two-dimensional transition metal dichalcogenides: synthesis, optical properties and optoelectronic applications

Zero-dimensional transition metal dichalcogenides (TMD) quantum dots (QDs) have attracted a lot of attention due to their interesting fundamental properties and various applications. Compared to TMD monolayers, the QD counterpart exhibits larger values for direct transition energies, exciton binding energies, absorption coefficient, luminescence efficiency, and specific surface area. These characteristics make them useful in optoelectronic devices. In this review, recent exciting progress on synthesis, optical properties, and applications of TMD QDs is highlighted. The first part of this article begins with a brief description of the synthesis approaches, which focus on microwave-assistant heating and pulsed laser ablation methods. The second part introduces the fundamental optical properties of TMD QDs, including quantum confinement in optical absorption, excitation-wavelength-dependent photoluminescence, and many-body effects. These properties are highlighted. In the third part, we discuss lastest advancements in optoelectronic devices based on TMD QDs These devices include light-emitting diodes, solar cells, photodetectors, optical sensors, and light-controlled memory devices. Finally, a brief summary and outlook will be provided.

ECRAM Materials, Devices, Circuits and Architectures: A Perspective

Non-von-Neumann computing using neuromorphic systems based on two-terminal resistive nonvolatile memory elements has emerged as a promising approach, but its full potential has not been realized due to the lack of materials and devices with the appropriate attributes. Unlike memristors, which require large write currents to drive phase transformations or filament growth, electrochemical random access memory (ECRAM) decouples the "write" and "read" operations using a "gate" electrode to tune the conductance state through charge-transfer reactions, and every electron transferred through the external circuit in ECRAM corresponds to the migration of ≈1 ion used to store analogue information. Like static dopants in traditional semiconductors, electrochemically inserted ions modulate the conductivity by locally perturbing a host's electronic structure; however, ECRAM does so in a dynamic and reversible manner. The resulting change in conductance can span orders of magnitude, from gradual increments needed for analog elements, to large, abrupt changes for dynamically reconfigurable adaptive architectures. In this in-depth perspective, the history of ECRAM, the recent progress in devices spanning organic, inorganic, and 2D materials, circuits, architectures, the rich portfolio of challenging, fundamental questions, and how ECRAM can be harnessed to realize a new paradigm for low-power neuromorphic computing are discussed.

Covalent Organic Frameworks for Neuromorphic Devices

Neuromorphic computing could enable the potential to break the inherent limitations of conventional von Neumann architectures, which has led to widespread research interest in developing novel neuromorphic memory devices, such as memristors and bioinspired artificial synaptic devices. Covalent organic frameworks (COFs), as crystalline porous polymers, have tailorable skeletons and pores, providing unique platforms for the interplay with photons, excitons, electrons, holes, ions, spins, and molecules. Such features encourage the rising research interest in COF materials in neuromorphic electronics. To develop high-performance COF-based neuromorphic memory devices, it is necessary to comprehensively understand materials, devices, and applications. Therefore, this Perspective focuses on discussing the use of COF materials for neuromorphic memory devices in terms of molecular design, thin-film processing, and neuromorphic applications. Finally, we provide an outlook for future directions and potential applications of COF-based neuromorphic electronics.

Metal-Oxide Heterojunction Optoelectronic Synapse and Multilevel Memory Devices Enabled by Broad Spectral Photocarrier Modulation

Broad spectral response and high photoelectric conversion efficiency are key milestones for realizing multifunctional, low-power optoelectronic devices such as artificial synapse and reconfigurable memory devices. Nevertheless, the wide bandgap and narrow spectral response of metal-oxide semiconductors are problematic for efficient metal-oxide optoelectronic devices such as photonic synapse and optical memory devices. Here, a simple titania (TiO2 )/indium-gallium-zinc-oxide (IGZO) heterojunction structure is proposed for efficient multifunctional optoelectronic devices, enabling widen spectral response range and high photoresponsivity. By overlaying a TiO2 film on IGZO, the light absorption range extends to red light, along with enhanced photoresponsivity in the full visible light region. By implementing the TiO2 /IGZO heterojunction structure, various synaptic behaviors are successfully emulated such as short-term memory/long-term memory and paired pulse facilitation. Also, the TiO2 /IGZO synaptic transistor exhibits a recognition rate up to 90.3% in recognizing handwritten digit images. Moreover, by regulating the photocarrier dynamics and retention behavior using gate-bias modulation, a reconfigurable multilevel (≥8 states) memory is demonstrated using visible light.

Flexible Quantum Dot Light-Emitting Device for Emerging Multifunctional and Smart Applications

Quantum dot light-emitting diodes (QLEDs), owing to their exceptional performances in device efficiency, color purity/tunability in the visible region and solution-processing ability on various substrates, become a potential candidate for flexible and ultrathin electroluminescent (EL) lighting and display. Moreover, beyond the lighting and display, flexible QLEDs are enabled with endless possibilities in the era of the internet of things and artificial intelligence by acting as input/output ports in wearable integrated systems. Challenges remain in the development of flexible QLEDs with the goals for high performance, excellent flexibility/even stretchability, and emerging applications. In this paper, the recent developments of QLEDs including quantum dot materials, working mechanism, flexible/stretchable strategies and patterning strategies, and highlight its emerging multifunctional integrations and smart applications covering wearable optical medical devices, pressure-sensing EL devices, and neural smart EL devices, are reviewed. The remaining challenges are also summarized and an outlook on the future development of flexible QLEDs made. The review is expected to offer a systematic understanding and valuable inspiration for flexible QLEDs to simultaneously satisfy optoelectronic and flexible properties for emerging applications.

Organic multilevel (opto)electronic memories towards neuromorphic applications

In the past decades, neuromorphic computing has attracted the interest of the scientific community due to its potential to circumvent the von Neumann bottleneck. Organic materials, owing to their fine tunablility and their ability to be used in multilevel memories, represent a promising class of materials to fabricate neuromorphic devices with the key requirement of operation with synaptic weight. In this review, recent studies of organic multilevel memory are presented. The operating principles and the latest achievements obtained with devices exploiting the main approaches to reach multilevel operation are discussed, with emphasis on organic devices using floating gates, ferroelectric materials, polymer electrets and photochromic molecules. The latest results obtained using organic multilevel memories for neuromorphic circuits are explored and the major advantages and drawbacks of the use of organic materials for neuromorphic applications are discussed.

Fabrication of a lamellar alginate-based aerogel decorated with carbon quantum dots for controlled fluorescence behaviors

This study aimed to construct an alginate aerogel doped with carbon quantum dots and investigate the fluorescence properties of the composites. The carbon quantum dots with the highest fluorescence intensity were obtained using a methanol-water ratio of 1 : 1, a reaction time of 90 minutes, and a reaction temperature of 160 °C. The fluorescent carbon quantum dot sodium alginate-based aerogel (FCSA) obtained by compounding alginate and carbon quantum dots exhibited excellent fluorescence properties when the concentration of nano-carbon quantum dot solution was 10.0 vol%. By incorporating nano-carbon quantum dots, the fluorescence properties of the lamellar alginate aerogel can be easily and efficiently adjusted. The alginate aerogel decorated with nano-carbon quantum dots exhibits promising potential in biomedical applications due to its biodegradable, biocompatible, and sustainable properties.

Recent progress in neuromorphic and memory devices based on graphdiyne

Graphdiyne (GDY) is an emerging two-dimensional carbon allotrope featuring a direct bandgap and fascinating physical and chemical properties, and it has demonstrated its promising potential in applications of catalysis, energy conversion and storage, electrical/optoelectronic devices, etc. In particular, the recent breakthrough in the synthesis of large-area, high-quality and ultrathin GDY films provides a feasible approach to developing high-performance electrical devices based on GDY. Recently, various GDY-based electrical and optoelectronic devices including multibit optoelectronic memories, ultrafast nonvolatile memories, artificial synapses and memristors have been proposed, in which GDY plays a crucial role. It is essential to summarize the recent breakthrough of GDY in device applications as a guidance, especially considering that the existing GDY-related reviews mainly focus on the applications in catalysis and energy-related fields. Herein, we review GDY-based novel memory and neuromorphic devices and their applications in neuromorphic computing and artificial visual systems. This review will provide an insight into the design and preparation of GDY-based devices and broaden the application fields of GDY.

How structural and vibrational features affect optoelectronic properties of non-stoichiometric quantum dots: computational insights

While stoichiometric quantum dots (QDs) have been well studied, a significant knowledge gap remains in the atomistic understanding of the non-stoichiometric ones, which are predominantly present during the experimental synthesis. Here, we investigate the effect of thermal fluctuations on structural and vibrational properties of non-stoichiometric cadmium selenide (CdSe) nanoclusters: anion-rich (Se-rich) and cation-rich (Cd-rich) using ab initio molecular dynamics (AIMD) simulations. While the excess atoms on the surface fluctuate more for a given QD type, the optical phonon modes are mostly composed of Se atoms dynamics, irrespective of the composition. Moreover, Se-rich QDs have higher bandgap fluctuations compared to Cd-rich QDs, suggesting poor optical properties of Se-rich QDs. Additionally, non-adiabatic molecular dynamics (NAMD) suggests faster non-radiative recombination for Cd-rich QDs. Altogether, this work provides insights into the dynamic electronic properties of non-stoichiometric QDs and proposes a rationale for the observed optical stability and superiority of cation-rich candidates for light emission applications.

Quantum dots are time bomb: Multiscale toxicological study

The use of quantum dots has spread widely into many applications. Works on the study of quantum dots on living organisms have had conflicting results on toxicity. There are no full-scale long-term toxicological studies with multiple administration of quantum dots. Understanding the toxicity of quantum dots is still limited. Here we present data on the effects of quantum dots on animals. In this work for the first time, it is shown that at a single administration of quantum dots in the body they have moderate species-specific toxicity, but repeated administration of quantum dots for 14 days even in the amount of 0.5 mg/kg leads to a delayed not completely irreversible hematotoxic effect, delayed irreversible disorders of barrier function of the liver, irreversible nephrotoxic effect, and to pathological changes in the thymus, kidneys and spleen. Administration of quantum dots in the amount of 2.5 mg/kg for 14 days leads to irreversible changes in the lungs, liver, spleen, kidneys and thyroid gland. This phenomenon is based on immunological reactions. On the one hand, these data confirm that quantum dots at a single administration can show relatively low toxicity. On the other hand, they cause to a delayed irreversible organ and tissue damage when repeatedly administered to the body even in small quantities. This study demonstrates that quantum dots are not as low in toxicity as previously thought to be and pose a serious risk when entering living organisms. Detecting and treating poisoning using standard methods of diagnosis and treatment of heavy metal poisoning may not be effective. This study demonstrates that toxic effects of quantum dots on a living body are quite complex and cannot be generalized based on previously reported assumptions.

Current trends in carbon-based quantum dots development from solid wastes and their applications

Urbanization and a massive population boom have immensely increased the solid wastes (SWs) generation and are expected to reach 3.40 billion tons by 2050. In many developed and emerging nations, SWs are prevalent in both major and small cities. As a result, in the current context, the reusability of SWs through various applications has taken on added importance. Carbon-based quantum dots (Cb-QDs) and their many variants are synthesized from SWs in a straightforward and practical method. Cb-QDs are a new type of semiconductor that has attracted the interest of researchers due to their wide range of applications, which include everything from energy storage, chemical sensing, to drug delivery. This review is primarily focused on the conversion of SWs into useful materials, which is an essential aspect of waste management for pollution reduction. In this context, the goal of the current review is to investigate the sustainable synthesis routes of carbon quantum dots (CQDs), graphene quantum dots (GQDs), and graphene oxide quantum dots (GOQDs) from various types SWs. The applications of CQDs, GQDs, and GOQDs in the different areas are also been discussed. Finally, the challenges in implementing the existing synthesis methods and future research directions are highlighted.

Biological function simulation in neuromorphic devices: from synapse and neuron to behavior

As the boom of data storage and processing, brain-inspired computing provides an effective approach to solve the current problem. Various emerging materials and devices have been reported to promote the development of neuromorphic computing. Thereinto, the neuromorphic device represented by memristor has attracted extensive research due to its outstanding property to emulate the brain's functions from synaptic plasticity, sensory-memory neurons to some intelligent behaviors of living creatures. Herein, we mainly review the progress of these brain functions mimicked by neuromorphic devices, concentrating on synapse (i.e. various synaptic plasticity trigger by electricity and/or light), neurons (including the various sensory nervous system) and intelligent behaviors (such as conditioned reflex represented by Pavlov's dog experiment). Finally, some challenges and prospects related to neuromorphic devices are presented.

Highly water-stable, luminescent, and monodisperse polymer-coated CsPbBr3 nanocrystals for imaging in living cells with better sensitivity

Recently, CsPbX₃ (X= Cl, Br, I) nanocrystals (NCs) have evolved as a potential contender for various optoelectronic applications due to some of their excellent photophysical properties. Their superior non-linear optical properties enable them to take part in bioimaging applications due to their longer penetration depth and less scattering effect in living cells. However, the poor stability of perovskite NCs in aqueous media still remains a great challenge for practical usage. Comparatively stable silica-coated NCs have a tendency to agglomerate among other NCs and transform into bigger particles. Such big particles clog the inside of narrow channels during the uptake and can't effectively reach the targeted cells. To tackle such issues, we introduce a fast and reproducible synthesis process of CsPbBr₃ NCs that are coated with different long-chained organic ligands/polymers and compared their photophysical properties. Among them, polyvinylpyrrolidone (PVP) encapsulated NCs are highly luminescent in the green spectral region and showed a maximum photoluminescence quantum yield (PLQY) of up to 84%. The incorporation of n-isopropyl acrylamide (NIPAM) along with PVP further improves the stability of the PVP-coated NCs against heat and moisture. These NCs exhibit higher water stability compared to silica-coated NCs and maintained their emission properties for about one week in DI water. The smaller particle size, uniform size distribution, higher structural stability, and better dispersivity of polymer-coated NCs in the aqueous media enable them to perform as fluorescent probes for live cell imaging in mammalian Chinese Hamster Ovary (CHO-K1) cells. There is no adverse affect in the cells' viability and morphology even after long incubation periods (∼72 hours). The dosage of Pb-ions contained in the polymer-coated NCs is calculated as below 5 μg mL^-1, which is suitable for live cell imaging. This work provides insight for expanding the use of these NCs significantly into bioimaging applications with higher sensitivity.

One-Step Preparation of Semiconductor/Dielectric Bilayer Structures for the Simulation of Flexible Bionic Photonic Synapses

Flexible synaptic devices with information sensing, processing, and storage functions are indispensable in the development of wearable artificial intelligence electronic systems. Here, a semiconductor/dielectric bilayer structure was prepared by a one-step deposition method and used for the first time in a flexible biomimetic photonic synaptic transistor device. Specifically, poly(3-hexylthiophene)-block-poly(phenyl isocyanide) with pentafluorophenyl ester (P3HT-b-PPI(5F)) was prepared as the device active layer, where the P3HT segment served as a carrier transport channel and optical gate and the PPI(5F) segment was used for charge trapping. Various biomimetic synaptic behaviors, such as excitatory postsynaptic currents, paired-pulse facilitation, and short-term/long-term memory, were successfully simulated under green light stimulation. An ultra-low energy consumption of 1.82 fJ was achieved with a greatly reduced operating voltage. Further, the "Morse-code" optical decoding was simulated using the excellent synaptic plasticity of the device. In addition, flexible synaptic devices were prepared by a one-step deposition method and can be well-affixed to arbitrary substrates. This has promising applications in the field of wearable bionic electronics.

Studies on Oxygen Permeation Resistance of SiCN Thin Film and RRAM Applications

In this study, a silicon carbon nitride (SiCN) thin film was grown with a thickness of 5~70 nm by the plasma-enhanced chemical vapor deposition (PECVD) method, and the oxygen permeation characteristics were analyzed according to the partial pressure ratio (PPR) of tetramethylsilane (4MS) to the total gas amount during the film deposition. X-ray photoelectron spectroscopy (XPS), Fourier transform infrared spectroscopy (FT-IR), and X-ray reflectivity (XRR) were used to investigate the composition and bonding structures of the SiCN film. An atomic force microscope (AFM) was used to examine the surface morphology of the SiCN films to see the porosity. The analysis indicated that Si-N bonds were dominant in the SiCN films, and a higher carbon concentration made the film more porous. To evaluate the oxygen permeation, a highly accelerated temperature and humidity stress test (HAST) evaluation was performed. The films grown at a high 4MS PPR were more susceptible to oxygen penetration, which changed Si-N bonds to Si-N-O bonds during the HAST. These results indicate that increasing the 4MS PPR made the SiCN film more porous and containable for oxygen. As an application, for the first time, SiCN dielectric film is suggested to be applied to resistive random access memory (RRAM) as an oxygen reservoir to store oxygen and prevent a reaction between metal electrodes and oxygen. The endurance characteristics of RRAM are found to be enhanced by applying the SiCN.

Solution-Processed Synaptic Memristors Based on Halide Perovskite Nanocrystals

Exploring new materials and structures to construct synaptic devices represents a promising route to fundamentally approach novel forms of computing. Nanocrystals (NCs) of halide perovskites possess unique charge transport characteristics, i.e., ionic-electronic coupling, holding considerable promise for energy-efficient and reconfigurable artificial synapses. Herein, we report solution-processed thin-film memristors from all-inorganic CsPbBr₃ perovskite NCs, functioning as an electrically programmable analog memory with good stability. The devices are demonstrated to successfully emulate a number of essential synaptic functions with low power consumption, including reversible potentiation and depression, short-term plasticity (STP), paired-pulse facilitation (PPF), and long-term plasticity (LTP), such as spike-number-dependent plasticity (SNDP), spike-rate-dependent plasticity (SRDP), spike-timing-dependent plasticity (STDP), and spike-voltage-dependent plasticity (SVDP). It is proposed that a coupled capacitive and inductive phenomenon originating from charge trapping and ion migration in CsPbBr₃ NC films, controlled by the amplitude and timing of the programming pulses, defines the degree of synaptic plasticity. A transition emerges from the fast trap-related capacitive regime to a slow ionic inductive regime, which enables continuous change of the film resistance and the magnitude of the electronic current, analogous to the synaptic weight modulation in biological synapses.

Voltage-Controlled Conversion from CDS to MDS in an Azobenzene-Based Organic Memristor for Information Storage and Logic Operations

For organic memristors, non-zero-crossing current-voltage (I-V) curves are often observed, which can be attributed to capacitive effects. If the conversion between the capacitance-dominated state (CDS) and the memristance-dominated state (MDS) can be realized in a controllable manner, more device functions can be obtained. In this work, a two-terminal memristor using a common organic dye, azobenzene (AZB), as the active layer was prepared. It is found that as the applied voltage gradually increases, the device can transition from CDS to MDS. In the low voltage range (<1 V), the device is in CDS, and the capacitance is significantly increased by ∼10⁴ compared to the theoretical value. In the high voltage range (>1 V), the device is in MDS, achieving an HRS (high resistance state)/LRS (low resistance state) resistance ratio of ∼10⁴, and the logic operations are achieved. Through the analysis of the I-V curve, energy diagram of the materials, and computer simulation results, the mechanisms of CDS, MDS, and their conversion are proposed. This work provides an in-depth understanding of the working mechanism of organic memristors and demonstrates the potential of AZB-based organic memristors for information storage and logic display applications.

Low-Dimensional Metal-Halide Perovskites as High-Performance Materials for Memory Applications

Metal-halide perovskites have drawn profuse attention during the past decade, owing to their excellent electrical and optical properties, facile synthesis, efficient energy conversion, and so on. Meanwhile, the development of information storage technologies and digital communications has fueled the demand for novel semiconductor materials. Low-dimensional perovskites have offered a new force to propel the developments of the memory field due to the excellent physical and electrical properties associated with the reduced dimensionality. In this review, the mechanisms, properties, as well as stability and performance of low-dimensional perovskite memories, involving both molecular-level perovskites and structure-level nanostructures, are comprehensively reviewed. The property-performance correlation is discussed in-depth, aiming to present effective strategies for designing memory devices based on this new class of high-performance materials. Finally, the existing challenges and future opportunities are presented.

Quantitative Detection of Gastrointestinal Tumor Markers Using a Machine Learning Algorithm and Multicolor Quantum Dot Biosensor

This work was to explore the application value of gastrointestinal tumor markers based on gene feature selection model of principal component analysis (PCA) algorithm and multicolor quantum dots (QDs) immunobiosensor in the detection of gastrointestinal tumors. Based on the PCA method, the neighborhood rough set algorithm was introduced to improve it, and the tumor gene feature selection model (OPCA) was established to analyze its classification accuracy and accuracy. Four kinds of coupled biosensors were fabricated based on QDs, namely, 525 nm Cd Se/Zn S QDs-carbohydrate antigen 125 (QDs525-CA125 McAb), 605 nm Cd Se/Zn S QDs-cancer antigen 19-9 (QDs605-CA19-9 McAb), 645 nm Cd Se/Zn S QDs-anticancer embryonic antigen (QDs 645-CEA McAb), and 565 nm Cd Se/Zn S QDs-anti-alpha-fetoprotein (QDs565-AFP McAb). The quantum dot-antibody conjugates were identified and quantified by fluorescence spectroscopy and ultraviolet absorption spectroscopy. The results showed that the classification precision of OPCA model in colon tumor and gastric cancer datasets was 99.52% and 99.03%, respectively, and the classification accuracy was 94.86% and 94.2%, respectively, which were significantly higher than those of other algorithms. The fluorescence values of AFP McAb, CEA McAb, CA19-9 McAb, and CA125 McAb reached the maximum when the conjugation concentrations were 25 µg/mL, 20 µg/mL, 30 µg/mL, and 30 µg/m, respectively. The highest recovery rate of AFP was 98.51%, and its fluorescence intensity was 35.78 ± 2.99, which was significantly higher than that of other antigens (P < 0.001). In summary, the OPCA model based on PCA algorithm can obtain fewer feature gene sets and improve the accuracy of sample classification. Intelligent immunobiosensors based on machine learning algorithms and QDs have potential application value in gastrointestinal gene feature selection and tumor marker detection, which provides a new idea for clinical diagnosis of gastrointestinal tumors.

Deep Quantum-Dot Arrays in Moiré Superlattices of Non-van der Waals Materials

Recently, moiré superlattices of twisted van der Waals (vdW) materials have attracted substantial interest due to their strongly correlated properties. However, the vdW interlayer interaction is intrinsically weak, such that many desired properties can only exist at low temperature. Here, we theoretically predict some unusual properties stemming from the chemical bonding between twisted PbS nanosheets as an example of non-vdW moiré superlattices. The strong interlayer coupling in such systems results in giant strain vortices and dipole vortices at the interface. The modified electronic structures become a series of dispersionless bands and artificial-atom states. In real space, these states are analogous to arrays of well-positioned quantum dots, which may be promising for use in single-electron devices. In theory, if the materials are doped with a low concentration of electrons, a Wigner crystal will form even without any magnetic field. To confirm the accessibility and stability of non-vdW moiré superlattices in experiment, we synthesized PbS moiré superlattices with different twist angles. Our transmission-electron-microscope observations reveal the resemblance of the small-angle-twisted structures with the square matrices of quantum dots, which is in good accordance with our calculations.

Nonvolatile Memories in Spiking Neural Network Architectures: Current and Emerging Trends

A sustainable computing scenario demands more energy-efficient processors. Neuromorphic systems mimic biological functions by employing spiking neural networks for achieving brain-like efficiency, speed, adaptability, and intelligence. Current trends in neuromorphic technologies address the challenges of investigating novel materials, systems, and architectures for enabling high-integration and extreme low-power brain-inspired computing. This review collects the most recent trends in exploiting the physical properties of nonvolatile memory technologies for implementing efficient in-memory and in-device computing with spike-based neuromorphic architectures.