Multifunctional Optoelectronic Synapses Based on Arrayed MoS2 Monolayers Emulating Human Association Memory

Reconfigurable Artificial Synapses Based on Ambipolar Environmentally Stable Tellurium for Neuromorphic Computing

Neuromorphic computing, a promising solution to the von Neumann bottleneck, is paving the way for next-generation computing and sensing systems. However, most studies of artificial synapses mimic only static plasticity, which is far from achieving the complex behaviors of the human brain. Here, we report a reliable neuromorphic computing system that integrates a top floating gate memory architecture and uses peculiar ambipolar tellurium (Te) as a channel material to fabricate reliable nonvolatile memory cells. The memory device clearly exhibits exceptional retention (∼104 s) and endurance (∼104 cycles) properties for ambipolar memory with on/off ratios of 108 (electrons) and 106 (holes). Furthermore, we have also achieved reconfigurable excitatory and inhibitory synapse functions based on a Te ambipolarity device and explored its application in neuromorphic computing for recognition of different levels of complexity images with high accuracy generally above 90%, demonstrating its potential in neuromorphic computing. These findings highlight the prospects of ambipolar Te memory for advancing the future in memory computing hardware.

Synaptic Plasticity and Memory Retention in ZnO-CNT Nanocomposite Optoelectronic Synaptic Devices

This study presents the fabrication and characterization of ZnO-CNT composite-based optoelectronic synaptic devices via a sol-gel process. By incorporating various concentrations of CNTs (0-2.0 wt%) into ZnO thin films, we investigated their effects on synaptic behaviors under ultraviolet (UV) stimulation. The CNT addition enhanced the electrical and optical performance by forming a p-n heterojunction with ZnO, which promoted charge separation and suppressed recombination. As a result, the 1.5 wt% CNT device exhibited the highest excitatory postsynaptic current (EPSC), improved paired-pulse facilitation, and prolonged memory retention. Learning-forgetting cycles revealed that repeated stimulation reduced the number of pulses required for relearning while extending the forgetting time, mimicking biological memory reinforcement. Energy consumption per pulse was estimated at 16.34 nJ, suggesting potential for low-power neuromorphic applications. A 3 × 3 device array was also employed for visual memory simulation, showing spatially controllable and stable memory states depending on CNT content. To support these findings, structural and optical analyses were conducted using scanning electron microscopy (SEM), UV-visible absorption spectroscopy, photoluminescence (PL) spectroscopy, and Raman spectroscopy. These findings demonstrate that the synaptic characteristics of ZnO-based devices can be finely tuned through CNT incorporation, providing a promising pathway for the development of energy-efficient and adaptive optoelectronic neuromorphic systems.

Neuromorphic Computing Using Synaptic Plasticity of Supercapacitors

Neuromorphic computing systems convert multimodal signals to electrical responses for artificial intelligence recognition. Energy is consumed during both the response enhancement and depression, making the systems suffer from high energy consumption. This study presents a neuromorphic computing pathway based on supercapacitors. MXene Ti₃C₂Tx supercapacitors are fabricated and convert current stimuli to voltage responses. The response enhancement and depression are tunable through adjusting charging and discharging current stimuli, thus exhibiting synaptic plasticity. Typical synaptic behaviors are demonstrated, including short-term memory, long-term memory, paired-pulse facilitation, and learning experience. Next, the voltage responses are used to recognize Braille numbers represented by 3 × 4 arrays. A charging/discharging current pulse train representing each Braille array is applied to the supercapacitor. The voltage responses are collected and converted to 12-pixel greyscale images. Once the images representing Braille numbers 0-9 are input into artificial neural networks and deep diffraction neural networks, 100% accuracy can be achieved for recognizing the ten numbers. Because energy is stored during response enhancement in the supercapacitor and released once the response declines, this research demonstrates the potential applications of energy storage devices in neuromorphic computing, providing an innovative way to develop energy-efficient brain-like computing systems.

Defect-engineered 2D Bi2Se3-based broadband optoelectronic synapses with ultralow energy consumption for neuromorphic computing

Optoelectronic synapses (OES) inspired by the human brain have gained attention in addressing the von Neumann bottleneck facing traditional computing. Numerous candidates, including topological insulators and other 2D materials, have been used to fabricate OES devices with different degrees of success. Se vacancies commonly appearing in epitaxially grown Bi2Se3 and importantly the ability to modulate the vacancies by changing the growth temperature make it a worthy candidate to construct an OES system. The vacancies effectively trap and release charges, leading to persistent photoconductivity, which is the mechanism behind OES operation. A defect-induced Bi2Se3-based synapse using an ultrathin layer grown by chemical vapor deposition is shown herein to successfully demonstrate basic synapse characteristics such as paired-pulse facilitation (PPF), short-term and long-term memory, and learning-relearning behavior. This OES device shows a very high PPF index of 201.7%, a long memory retention time of 523.1 s, and an ultralow energy consumption of 9.2 fJ per spike, which is at the low end of the 1-100 fJ range for biological systems. Density functional theory simulations reinforce the definite role of trap centers induced by the Se vacancies in the device operation. Our device realizes a high recognition accuracy of 90.12% for MNIST handwritten digital images in simulations based on an artificial neural network algorithm. The exceptional results achieved here show the potential of Bi2Se3 for synaptic applications and pave the way for exploiting its potential in future high-performance neuromorphic computing and other artificial visual perception systems.

Enhanced Long-Term In-Sensing Memory in ZnO Nanoparticle-Based Optoelectronic Synaptic Devices Through Thermal Treatment

Two-terminal optoelectronic synaptic devices based on ZnO nanoparticles (NPs) were fabricated to investigate the effects of thermal annealing control (200 °C-500 °C) in nitrogen and oxygen atmospheres on surface morphology, optical response, and synaptic functionality. Atomic force microscopy (AFM) analysis revealed improved grain growth and reduced surface roughness. At the same time, UV-visible spectroscopy and photoluminescence confirmed a blue shift in the absorption edge and enhanced near-band-edge emission, particularly in nitrogen-annealed devices due to increased oxygen vacancies. X-ray photoelectron spectroscopy (XPS) analysis of the O 1s spectra confirmed that oxygen vacancies were more pronounced in nitrogen-annealed devices than in oxygen-annealed ones at 500 °C. Optical resistive switching was observed, where 365 nm ultraviolet (UV) irradiation induced a transition from a high-resistance state (HRS) to a low-resistance state (LRS), attributed to electron-hole pair generation and oxygen desorption. The electrical reset process, achieved by applying -1.0 V to -5.0 V, restored the initial HRS, demonstrating stable switching behavior. Nitrogen-annealed devices with higher oxygen vacancies exhibited superior synaptic performance, including higher excitatory postsynaptic currents, stronger paired-pulse facilitation, and extended persistent photoconductivity (PPC) duration, enabling long-term memory retention. By systematically varying UV exposure time, intensity, pulse number, and frequency, ZnO NPs-based devices demonstrated the transition from short-term to long-term memory, mimicking biological synaptic behavior. Learning and forgetting simulations showed faster learning and slower decay in nitrogen-annealed devices, emphasizing their potential for next-generation neuromorphic computing and energy-efficient artificial synapses.

Frontier applications of retinal nanomedicine: progress, challenges and perspectives

The human retina is a fragile and sophisticated light-sensitive tissue in the central nervous system. Unhealthy retinas can cause irreversible visual deterioration and permanent vision loss. Effective therapeutic strategies are restricted to the treatment or reversal of these conditions. In recent years, nanoscience and nanotechnology have revolutionized targeted management of retinal diseases. Pharmaceuticals, theranostics, regenerative medicine, gene therapy, and retinal prostheses are indispensable for retinal interventions and have been significantly advanced by nanomedical innovations. Hence, this review presents novel insights into the use of versatile nanomaterial-based nanocomposites for frontier retinal applications, including non-invasive drug delivery, theranostic contrast agents, therapeutic nanoagents, gene therapy, stem cell-based therapy, retinal optogenetics and retinal prostheses, which have mainly been reported within the last 5 years. Furthermore, recent progress, potential challenges, and future perspectives in this field are highlighted and discussed in detail, which may shed light on future clinical translations and ultimately, benefit patients with retinal disorders.

Ferroelectric/Electric-Double-Layer-Modulated Synaptic Thin Film Transistors toward an Artificial Tactile Perception System

Tactile sensation and recognition in the human brain are indispensable for interaction between the human body and the surrounding environment. It is quite significant for intelligent robots to simulate human perception and decision-making functions in a more human-like way to perform complex tasks. A combination of tactile piezoelectric sensors with neuromorphic transistors provides an alternative way to achieve perception and cognition functions for intelligent robots in human-machine interaction scenarios. To promote both long-term and short-term plasticity of the artificial synaptic transistor, a composite gate dielectric composed of ferroelectric terpolymer P(VDF-TrFE-CFE) and chitosan was intendedly developed, while amorphous metal oxide InZnO was adopted as the channel layer. The transition from short-term to long-term plasticity function was realized on the basis of the electric-double-layer effect and ferroelectric polarization. Benefiting from its low-voltage operation performance, this synaptic transistor was functionalized by connecting with a flexible piezoelectric poly(vinylidene fluoride) capacitor to exhibit tactile stimulus-excited synaptic behavior. Feedback control was further introduced into the tactile synaptic system to imitate two typical scenarios of sensation and response, including the action of a mechanical claw to pain sensation and spontaneous scratching to itch sensation. This work provides a perspective on achieving intelligent perception for soft robotics and healthcare application.

Plasmon-Enhanced Optoelectronic Graded Neurons for Dual-Waveband Image Fusion and Motion Perception

Motion recognition based on vision detectors requires the synchronous encoding and processing of temporal and spatial information in wide wavebands. Here, the dual-waveband sensitive optoelectronic synapses performing as graded neurons are reported for high-accuracy motion recognition and perception. Wedge-shaped nanostructures are designed and fabricated on molybdenum disulfide (MoS2) monolayers, leading to plasmon-enhanced wideband absorption across the visible to near-infrared spectral range. Due to the charge trapping and release at shallow trapping centers within the device channel, the optoelectronic graded neurons demonstrate remarkable photo-induced conductance plasticity at both 633 and 980 nm wavelengths. A dynamic vision system consisting of 20 × 20 optoelectronic neurons demonstrates remarkable capabilities in the precise detection and perception of various motions. Moreover, neural network computing systems have been built as visual motion perceptron to identify target object movement. The recognition accuracy of dual-wavelength fused images for various motion trajectories has experienced a remarkable enhancement, transcending the previous level of less than 80% to impressive values exceeding 99%.

Light-Mediated Multilevel Neuromorphic Switching in a Hybrid Organic-Inorganic Memristor

Modulating memristors optically paves the way for new optoelectronic devices with applications in computer vision, neuromorphic computing, and artificial intelligence. Here, we report on memristors based on a hybrid material of vertically aligned zinc oxide nanorods (ZnO NRs) and poly(methyl methacrylate) (PMMA). The memristors require no forming step and exhibit the typical electronic switching properties of a bipolar memristor. The devices can also be switched optically and demonstrate an optically tunable multilevel switching behavior upon illumination with UV light. Additionally, the devices demonstrate high-performance photonic synaptic functionalities, including excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), and enhanced potentiation/depression and learning-forgetting characteristics. Notably, after the removal of the UV light, the optoelectronic memristor exhibits a short-term memory due to a persistent photoconductance (PPC) effect. Such a behavior has application in the fabrication of cloned neural networks with pretrained information. The work provides a promising pathway for the fabrication of simple, easy-to-make, and low-cost optoelectronic devices for memory and optically tuned neuromorphic computing applications.

Enhancing Long-Term Memory in Carbon-Nanotube-Based Optoelectronic Synaptic Devices for Neuromorphic Computing

This study investigates the impact of spin-coating speed on the performance of carbon nanotube (CNT)-based optoelectronic synaptic devices, focusing on their long-term memory properties. CNT films fabricated at lower spin speeds exhibited a greater thickness and density compared to those at higher speeds. These denser films showed enhanced persistent photoconductivity, resulting in higher excitatory postsynaptic currents (EPSCs) and the prolonged retention of memory states after UV stimulation. Devices coated at a lower spin-coating speed of 2000 RPM maintained EPSCs above 70% for 3600 s, outperforming their higher-speed counterparts in long-term memory retention. Additionally, the study demonstrated that the learning efficiency improved with repeated UV stimulation, with fewer pulses needed to achieve the maximum EPSC in successive learning cycles. These findings highlight that optimizing spin-coating speeds can significantly enhance the performance of CNT-based synaptic devices, making them suitable for applications in neuromorphic computing and artificial neural networks requiring robust memory retention and efficient learning.

Large-Area Epitaxial Growth of Transition Metal Dichalcogenides

Over the past decade, research on atomically thin two-dimensional (2D) transition metal dichalcogenides (TMDs) has expanded rapidly due to their unique properties such as high carrier mobility, significant excitonic effects, and strong spin-orbit couplings. Considerable attention from both scientific and industrial communities has fully fueled the exploration of TMDs toward practical applications. Proposed scenarios, such as ultrascaled transistors, on-chip photonics, flexible optoelectronics, and efficient electrocatalysis, critically depend on the scalable production of large-area TMD films. Correspondingly, substantial efforts have been devoted to refining the synthesizing methodology of 2D TMDs, which brought the field to a stage that necessitates a comprehensive summary. In this Review, we give a systematic overview of the basic designs and significant advancements in large-area epitaxial growth of TMDs. We first sketch out their fundamental structures and diverse properties. Subsequent discussion encompasses the state-of-the-art wafer-scale production designs, single-crystal epitaxial strategies, and techniques for structure modification and postprocessing. Additionally, we highlight the future directions for application-driven material fabrication and persistent challenges, aiming to inspire ongoing exploration along a revolution in the modern semiconductor industry.

Reconfigurable Neuromorphic Computing with 2D Material Heterostructures for Versatile Neural Information Processing

Reconfigurable neuromorphic computing holds promise for advancing energy-efficient neural network implementation and functional versatility. Previous work has focused on emulating specific neural functions rather than an integrated approach. We propose an all two-dimensional (2D) material-based heterostructure capable of performing multiple neuromorphic operations by reconfiguring output terminals in response to stimuli. Specifically, our device can synergistically emulate the key neural elements of the synapse, neuron, and dendrite, which play important and interrelated roles in information processing. Dendrites, the branches that receive and transmit presynaptic action potentials, possess the ability to nonlinearly integrate and filter incoming signals. The proposed heterostructure allows reconfiguration between different operation modes, demonstrating its potential for diverse computing tasks. As a proof of concept, we show that the device can perform basic Boolean logic functions. This highlights its applicability to complex neural-network-based information processing problems. Our integrated neuromorphic approach may advance the development of versatile, low-power neuromorphic hardware.

Effect of annealing temperature on the optoelectrical synapse behaviors of A-ZnO microtube

Optoelectronic synapses with fast response, low power consumption, and memory function hold great potential in the future of artificial intelligence technologies. Herein, a strategy of annealing in oxygen ambient at different temperatures is presented to improve the optoelectronic synaptic behaviors of acceptor-rich ZnO (A-ZnO) microtubes. The basic synaptic functions of as-grown and annealed A-ZnO microtubes including excitatory postsynaptic current (EPSC), short-term memory (STM) to long-term memory (LTM) conversion, and paired-pulse facilitation (PPF), were successfully emulated. The results show that the annealing temperature of 600 °C yields high figures of merit compared to other annealed A-ZnO microtubes. The 4-fold and 20-fold enhancement dependent on the light pulse duration time and energy density have been achieved in the 600 °C annealed A-ZnO microtube, respectively. Furthermore, the device exhibited a PPF index of up to 238% and achieved four cycles of "learning-forgetting" process, proving its capability for optical information storage. The free exciton (FX) and donor-acceptor pair (DAP) concentrations significantly influenced the persistent photoconductivity (PPC) behavior of A-ZnO microtubes. Therefore, the LTM response can be controlled by the adjustment of numbers, powers, and interval time of the optical stimulation. This work outlines a strategy to improve the EPSC response through defect control, representing a step towards applications in the field of optoelectronic synaptic device.

Multicolor vision perception of flexible optoelectronic synapse with high sensitivity for skin sunburn warning

The development of flexible synaptic devices with multicolor signal response is important to exploit advanced artificial visual perception systems. The Sn vacancy-dominant memory and narrow gap characteristics of PEA2SnI4 make it suitable as a functional layer in ultraviolet-visible (UV-Vis) light-stimulated synaptic devices. However, such device tends to have high dark current and poor sensitivity, which is not conducive to subsequent information processing. Here, we proposed a self-powered flexible optoelectronic synapse based on PEA2SnI4 films. By introducing the electron transport layer (ETL), the dark current of the device is decreased by 5 orders of magnitude as compared to the Au/PEA2SnI4/ITO device, and the sensitivity is increased from 10.3% to 99.2% at 1.25 mW cm-2 light illumination (520 nm), indicating the vital role of the introduced ETL in promoting the separation of excitons in the interface and inhibiting the free carrier transfer. On this basis, the optoelectronic synaptic functions with integrated sensing, recognition, and memory features were realized. The array device exhibits UV-Vis light sensitivity and tunable synaptic plasticity, enabling its application for multicolor visual sensing and skin sunburn warning. This work provides an effective strategy for fabricating multicolor intelligent sensors and artificial vision systems, which facilitate the practical application of artificial optoelectronic synapses.

Opto-Electrochemical Synaptic Memory in Supramolecularly Engineered Janus 2D MoS2

Artificial synapses combining multiple yet independent signal processing strategies in a single device are key enabler to achieve high-density of integration, energy efficiency, and fast data manipulation in brain-like computing. By taming functional complexity, the use of hybrids comprising multiple materials as active components in synaptic devices represents a powerful route to encode both short-term potentiation (STP) and long-term potentiation (LTP) in synaptic circuitries. To meet such a grand challenge, herein a novel Janus 2D material is developed by dressing asymmetrically the two surfaces of 2D molybdenum disulfide (MoS2 ) with an electrochemically-switchable ferrocene (Fc)/ ferrocenium (Fc+ ) redox couple and an optically-responsive photochromic azobenzene (Azo). Upon varying the magnitude of the electrochemical stimulus, it is possible to steer the transition between STP and LTP, thereby either triggering electrochemical doping of Fc/Fc+  pair on MoS2  or controlling an adsorption/desorption process of such redox species on MoS2 . In addition, a lower magnitude LTP is recorded by activating the photoisomerization of azobenzene chemisorbed molecules and therefore modulating the dipole-induced doping of the 2D semiconductor. Significantly, the interplay of electrochemical and optical stimuli makes it possible to construct artificial synapses where LTP can be boosted to 4-bit (16 memory states) while simultaneously functioning as STP.

High-Density Artificial Synapse Array Consisting of Homogeneous Electrolyte-Gated Transistors

The artificial synapse array with an electrolyte-gated transistor (EGT) as an array unit presents considerable potential for neuromorphic computation. However, the integration of EGTs faces the drawback of the conflict between the polymer electrolytes and photo-lithography. This study presents a scheme based on a lateral-gate structure to realize high-density integration of EGTs and proposes the integration of 100 × 100 EGTs into a 2.5 × 2.5 cm2 glass, with a unit density of up to 1600 devices cm-2 . Furthermore, an electrolyte framework is developed to enhance the array performance, with ionic conductivity of up to 2.87 × 10-3  S cm-1 owing to the porosity of zeolitic imidazolate frameworks-67. The artificial synapse array realizes image processing functions, and exhibits high performance and homogeneity. The handwriting recognition accuracy of a representative device reaches 92.80%, with the standard deviation of all the devices being limited to 9.69%. The integrated array and its high performance demonstrate the feasibility of the scheme and provide a solid reference for the integration of EGTs.

Temperature-Dependent Phonon Scattering and Photoluminescence in Vertical MoS2/WSe2 Heterostructures

Transition metal dichalcogenide (TMD) monolayers and their heterostructures have attracted considerable attention due to their distinct properties. In this work, we performed a systematic investigation of MoS2/WSe2 heterostructures, focusing on their temperature-dependent Raman and photoluminescence (PL) characteristics in the range of 79 to 473 K. Our Raman analysis revealed that both the longitudinal and transverse modes of the heterostructure exhibit linear shifts towards low frequencies with increasing temperatures. The peak position and intensity of PL spectra also showed pronounced temperature dependency. The activation energy of thermal-quenching-induced PL emissions was estimated as 61.5 meV and 82.6 meV for WSe2 and MoS2, respectively. Additionally, we observed that the spectral full width at half maximum (FWHM) of Raman and PL peaks increases as the temperature increases, and these broadenings can be attributed to the phonon interaction and the expansion of the heterostructure's thermal coefficients. This work provides valuable insights into the interlayer coupling of van der Waals heterostructures, which is essential for understanding their potential applications in extreme temperatures.