A Ferrite Synaptic Transistor with Topotactic Transformation

Hardware implementation of artificial synaptic devices that emulate the functions of biological synapses is inspired by the biological neuromorphic system and has drawn considerable interest. Here, a three‐terminal ferrite synaptic device based on a topotactic phase transition between crystalline phases is presented. The electrolyte‐gating‐controlled topotactic phase transformation between brownmillerite SrFeO_2.5 and perovskite SrFeO_3?δ is confirmed from the examination of the crystal and electronic structure. A synaptic transistor with electrolyte‐gated ferrite films by harnessing gate‐controllable multilevel conduction states, which originate from many distinct oxygen‐deficient perovskite structures of SrFeO_x induced by topotactic phase transformation, is successfully constructed. This three‐terminal artificial synapse can mimic important synaptic functions, such as synaptic plasticity and spike‐timing‐dependent plasticity. Simulations of a neural network consisting of ferrite synaptic transistors indicate that the system offers high classification accuracy. These results provide insight into the potential application of advanced topotactic phase transformation materials for designing artificial synapses with high performance.     

A MoS2/PTCDA Hybrid Heterojunction Synapse with Efficient Photoelectric Dual Modulation and Versatility

Just as biological synapses provide basic functions for the nervous system, artificial synaptic devices serve as the fundamental building blocks of neuromorphic networks; thus, developing novel artificial synapses is essential for neuromorphic computing. By exploiting the band alignment between 2D inorganic and organic semiconductors, the first multi‐functional synaptic transistor based on a molybdenum disulfide (MoS₂)/perylene‐3,4,9,10‐tetracarboxylic dianhydride (PTCDA) hybrid heterojunction, with remarkable short‐term plasticity (STP) and long‐term plasticity (LTP), is reported. Owing to the elaborate design of the energy band structure, both robust electrical and optical modulation are achieved through carriers transfer at the interface of the heterostructure, which is still a challenging task to this day. In electrical modulation, synaptic inhibition and excitation can be achieved simultaneously in the same device by gate voltage tuning. Notably, a minimum inhibition of 3% and maximum facilitation of 500% can be obtained by increasing the electrical number, and the response to different frequency signals indicates a dynamic filtering characteristic. It exhibits flexible tunability of both STP and LTP and synaptic weight changes of up to 60, far superior to previous work in optical modulation. The fully 2D MoS₂/PTCDA hybrid heterojunction artificial synapse opens up a whole new path for the urgent need for neuromorphic computation devices.     

Photonic Potentiation and Electric Habituation in Ultrathin Memristive Synapses Based on Monolayer MoS2

Monolayer of 2D transition metal dichalcogenides, with a thickness of less than 1 nm, paves a feasible path to the development of ultrathin memristive synapses, to fulfill the requirements for constructing large‐scale high density 3D stacking neuromorphic chips. Herein, memristive devices based on monolayer n‐MoS₂ on p‐Si substrate with a large self‐rectification ratio, exhibiting photonic potentiation and electric habituation, are successfully fabricated. Versatile synaptic neuromorphic functions, such as potentiation/habituation, short‐term/long‐term plasticity, and paired‐pulse facilitation, are successfully mimicked based on the inherent persistent photoconductivity performance and the volatile resistive switching behavior. These findings demonstrate the potential applications of ultrathin transition metal dichalcogenides for memristive synapses. These memristive synapses with the combination of photonic and electric neuromorphic functions have prospective in the applications of synthetic retinas and optoelectronic interfaces for integrated photonic circuits based on mixed‐mode electro‐optical operation.     

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.     

A Synaptic Transistor based on Quasi‐2D Molybdenum Oxide

Biological synapses store and process information simultaneously by tuning the connection between two neighboring neurons. Such functionality inspires the task of hardware implementation of neuromorphic computing systems. Ionic/electronic hybrid three‐terminal memristive devices, in which the channel conductance can be modulated according to the history of applied voltage and current, provide a more promising way of emulating synapses by a substantial reduction in complexity and energy consumption. 2D van der Waals materials with single or few layers of crystal unit cells have been a widespread innovation in three‐terminal electronic devices. However, less attention has been paid to 2D transition‐metal oxides, which have good stability and technique compatibility. Here, nanoscale three‐terminal memristive transistors based on quasi‐2D α‐phase molybdenum oxide (α‐MoO₃) to emulate biological synapses are presented. The essential synaptic behaviors, such as excitatory postsynaptic current, depression and potentiation of synaptic weight, and paired‐pulse facilitation, as well as the transition of short‐term plasticity to long‐term potentiation, are demonstrated in the three‐terminal devices. These results provide an insight into the potential application of 2D transition‐metal oxides for synaptic devices with high scaling ability, low energy consumption, and high processing efficiency.     

Stimuli‐Enabled Artificial Synapses for Neuromorphic Perception: Progress and Perspectives

Brain‐inspired neuromorphic computing is intended to provide effective emulation of the functionality of the human brain via the integration of electronic components. Recent studies of synaptic plasticity, which represents one of the most significant neurochemical bases of learning and memory, have enhanced the general comprehension of how the brain functions and have thereby eased the development of artificial neuromorphic devices. An understanding of the synaptic plasticity induced by various types of stimuli is essential for neuromorphic system construction. The realization of multiple stimuli‐enabled synapses will be important for future neuromorphic computing applications. In this Review, state‐of‐the‐art synaptic devices with particular emphasis on their synaptic behaviors under excitation by a variety of external stimuli are summarized, including electric fields, light, magnetic fields, pressure, and temperature. The switching mechanisms of these synaptic devices are discussed in detail, including ion migration, electron/hole transfer, phase transition, redox‐based resistive switching, and other mechanisms. This Review aims to provide a comprehensive understanding of the operating mechanisms of artificial synapses and thus provides the principles required for design of multifunctional neuromorphic systems with parallel processing capabilities.     

Optoelectronic artificial synapses based on copper (II) phthalocyanine with modulated neuroplasticity

Optoelectronic synapses have been attracting significant attention due to their important role in visual information processing. In this work, we fabricate an all-organic optoelectronic synaptic device with a double heterojunction structure of PEDOT:PSS/poly(vinylidene fluoridetrifluoroethylene) (P(VDF-TrFE))/copper (II) phthalocyanine (CuPc) by a simple preparation process. The introduction of a dielectric P(VDF-TrFE) layer between PEDOT:PSS and CuPc layers benefits the trapping of charge carriers and slows down the electron-hole recombination rate. This two-terminal optoelectronic device is successfully applied to simulate synaptic functions of biological synapses by using optical pulses of 660 nm, including paired-pulse facilitation, spike-duration dependent plasticity, spike-rate dependent plasticity, spike-number dependent plasticity, and learning-experience behavior. Furthermore, the key characteristics of a nociceptor and the optical logic function of the “AND” and “OR” operations are also emulated. This work illustrates the potential of such device for constructing neuromorphic computing systems at the physical level.

     

Bioinspired Multifunctional Organic Transistors Based on Natural Chlorophyll/Organic Semiconductors

Inspired by the photosynthesis process of natural plants, multifunctional transistors based on natural biomaterial chlorophyll and organic semiconductors (OSCs) are reported. Functions as photodetectors (PDs) and light-stimulated synaptic transistors (LSSTs) can be switched by gate voltage. As PDs, the devices exhibit ultrahigh photoresponsivity up to 2 × 10⁶ A W⁻¹, detectivity of 6 × 10¹⁵ Jones, and I_photo/I_dark ratio of 2.7 × 10⁶, which make them among the best reported organic PDs. As LSSTs, important synaptic functions similar to biological synapses are demonstrated, together with a dynamic learning and forgetting process and image-processing function. Significantly, benefiting from the ultrahigh photosensitivity of chlorophyll, the lowest operating voltage and energy consumption of the LSSTs can be 10⁻⁵ V and 0.25 fJ, respectively. The devices also exhibit high flexibility and long-term air stability. This work provides a new guide for developing organic electronics based on natural biomaterials.     

2D MoS2 Neuromorphic Devices for Brain‐Like Computational Systems

Hardware implementation of artificial synapses/neurons with 2D solid‐state devices is of great significance for nanoscale brain‐like computational systems. Here, 2D MoS₂ synaptic/neuronal transistors are fabricated by using poly(vinyl alcohol) as the laterally coupled, proton‐conducting electrolytes. Fundamental synaptic functions, such as an excitatory postsynaptic current, paired‐pulse facilitation, and a dynamic filter for information transmission of biological synapse, are successfully emulated. Most importantly, with multiple input gates and one modulatory gate, spiking‐dependent logic operation/modulation, multiplicative neural coding, and neuronal gain modulation are also experimentally demonstrated. The results indicate that the intriguing 2D MoS₂ transistors are also very promising for the next‐generation of nanoscale neuromorphic device applications.     

Stretchable Transistor-Structured Artificial Synapses for Neuromorphic Electronics

Stretchable synaptic transistors, a core technology in neuromorphic electronics, have functions and structures similar to biological synapses and can concurrently transmit signals and learn. Stretchable synaptic transistors are usually soft and stretchy and can accommodate various mechanical deformations, which presents significant prospects in soft machines, electronic skin, human–brain interfaces, and wearable electronics. Considerable efforts have been devoted to developing stretchable synaptic transistors to implement electronic device neuromorphic functions, and remarkable advances have been achieved. Here, this review introduces the basic concept of artificial synaptic transistors and summarizes the recent progress in device structures, functional-layer materials, and fabrication processes. Classical stretchable synaptic transistors, including electric double-layer synaptic transistors, electrochemical synaptic transistors, and optoelectronic synaptic transistors, as well as the applications of stretchable synaptic transistors in light-sensory systems, tactile-sensory systems, and multisensory artificial-nerves systems, are discussed. Finally, the current challenges and potential directions of stretchable synaptic transistors are analyzed. This review presents a detailed introduction to the recent progress in stretchable synaptic transistors from basic concept to applications, providing a reference for the development of stretchable synaptic transistors in the future.     

Synergistic Improvement of Long-Term Plasticity in Photonic Synapses Using Ferroelectric Polarization in Hafnia-Based Oxide-Semiconductor Transistors

A number of synapse devices have been intensively studied for the neuromorphic system which is the next-generation energy-efficient computing method. Among these various types of synapse devices, photonic synapse devices recently attracted significant attention. In particular, the photonic synapse devices using persistent photoconductivity (PPC) phenomena in oxide semiconductors are receiving much attention due to the similarity between relaxation characteristics of PPC phenomena and Ca²⁺ dynamics of biological synapses. However, these devices have limitations in its controllability of the relaxation characteristics of PPC behaviors. To utilize the oxide semiconductor as photonic synapse devices, relaxation behavior needs to be accurately controlled. In this study, a photonic synapse device with controlled relaxation characteristics by using an oxide semiconductor and a ferroelectric layer is demonstrated. This device exploits the PPC characteristics to demonstrate synaptic functions including short-term plasticity, paired-pulse facilitation (PPF), and long-term plasticity (LTP). The relaxation properties are controlled by the polarization of the ferroelectric layer, and this polarization is used to control the amount by which the conductance levels increase during PPF operation and to enhance LTP characteristics. This study provides an important step toward the development of photonic synapses with tunable synaptic functions.     

Reproducible Ultrathin Ferroelectric Domain Switching for High-Performance Neuromorphic Computing

Neuromorphic computing consisting of artificial synapses and neural network algorithms provides a promising approach for overcoming the inherent limitations of current computing architecture. Developments in electronic devices that can accurately mimic the synaptic plasticity of biological synapses, have promoted the research boom of neuromorphic computing. It is reported that robust ferroelectric tunnel junctions can be employed to design high-performance electronic synapses. These devices show an excellent memristor function with many reproducible states (≈200) through gradual ferroelectric domain switching. Both short- and long-term plasticity can be emulated by finely tuning the applied pulse parameters in the electronic synapse. The analog conductance switching exhibits high linearity and symmetry with small switching variations. A simulated artificial neural network with supervised learning built from these synaptic devices exhibited high classification accuracy (96.4%) for the Mixed National Institute of Standards and Technology (MNIST) handwritten recognition data set.     

Flexible Ionic‐Electronic Hybrid Oxide Synaptic TFTs with Programmable Dynamic Plasticity for Brain‐Inspired Neuromorphic Computing

Emulation of biological synapses is necessary for future brain‐inspired neuromorphic computational systems that could look beyond the standard von Neuman architecture. Here, artificial synapses based on ionic‐electronic hybrid oxide‐based transistors on rigid and flexible substrates are demonstrated. The flexible transistors reported here depict a high field‐effect mobility of ≈9 cm² V^?1 s^?1 with good mechanical performance. Comprehensive learning abilities/synaptic rules like paired‐pulse facilitation, excitatory and inhibitory postsynaptic currents, spike‐time‐dependent plasticity, consolidation, superlinear amplification, and dynamic logic are successfully established depicting concurrent processing and memory functionalities with spatiotemporal correlation. The results present a fully solution processable approach to fabricate artificial synapses for next‐generation transparent neural circuits.     

Truly Concomitant and Independently Expressed Short‐ and Long‐Term Plasticity in a Bi2O2Se‐Based Three‐Terminal Memristor

Concomitance of diverse synaptic plasticity across different timescales produces complex cognitive processes. To achieve comparable cognitive complexity in memristive neuromorphic systems, devices that are capable of emulating short‐term (STP) and long‐term plasticity (LTP) concomitantly are essential. In existing memristors, however, STP and LTP can only be induced selectively because of the inability to be decoupled using different loci and mechanisms. In this work, the first demonstration of truly concomitant STP and LTP is reported in a three‐terminal memristor that uses independent physical phenomena to represent each form of plasticity. The emerging layered material Bi₂O₂Se is used for memristors for the first time, opening up the prospects for ultrathin, high‐speed, and low‐power neuromorphic devices. The concerted action of STP and LTP allows full‐range modulation of the transient synaptic efficacy, from depression to facilitation, by stimulus frequency or intensity, providing a versatile device platform for neuromorphic function implementation. A heuristic recurrent neural circuitry model is developed to simulate the intricate “sleep–wake cycle autoregulation” process, in which the concomitance of STP and LTP is posited as a key factor in enabling this neural homeostasis. This work sheds new light on the development of generic memristor platforms for highly dynamic neuromorphic computing.     

Gate‐Tunable and Multidirection‐Switchable Memristive Phenomena in a Van Der Waals Ferroelectric

Memristive devices have been extensively demonstrated for applications in nonvolatile memory, computer logic, and biological synapses. Precise control of the conducting paths associated with the resistance switching in memristive devices is critical for optimizing their performances including ON/OFF ratios. Here, gate tunability and multidirectional switching can be implemented in memristors for modulating the conducting paths using hexagonal α‐In₂Se₃, a semiconducting van der Waals ferroelectric material. The planar memristor based on in‐plane (IP) polarization of α‐In₂Se₃ exhibits a pronounced switchable photocurrent, as well as gate tunability of the channel conductance, ferroelectric polarization, and resistance‐switching ratio. The integration of vertical α‐In₂Se₃ memristors based on out‐of‐plane (OOP) polarization is demonstrated with a device density of 7.1 × 10⁹ in.^?2 and a resistance‐switching ratio of well over 10³. A multidirectionally operated α‐In₂Se₃ memristor is also proposed, enabling the control of the OOP (or IP) resistance state directly by an IP (or OOP) programming pulse, which has not been achieved in other reported memristors. The remarkable behavior and diverse functionalities of these ferroelectric α‐In₂Se₃ memristors suggest opportunities for future logic circuits and complex neuromorphic computing.     

Retina-Inspired Carbon Nitride-Based Photonic Synapses for Selective Detection of UV Light

Photonic synapses combine sensing and processing in a single device, so they are promising candidates to emulate visual perception of a biological retina. However, photonic synapses with wavelength selectivity, which is a key property for visual perception, have not been developed so far. Herein, organic photonic synapses that selectively detect UV rays and process various optical stimuli are presented. The photonic synapses use carbon nitride (C₃N₄) as an UV-responsive floating-gate layer in transistor geometry. C₃N₄ nanodots dominantly absorb UV light; this trait is the basis of UV selectivity in these photonic synapses. The presented devices consume only 18.06 fJ per synaptic event, which is comparable to the energy consumption of biological synapses. Furthermore, in situ modulation of exposure to UV light is demonstrated by integrating the devices with UV transmittance modulators. These smart systems can be further developed to combine detection and dose-calculation to determine how and when to decrease UV transmittance for preventive health care.     

Tuning the Structural and Optoelectronic Properties of Cs2AgBiBr6 Double-Perovskite Single Crystals through Alkali-Metal Substitution

Lead-free double perovskites have great potential as stable and nontoxic optoelectronic materials. Recently, Cs₂AgBiBr₆ has emerged as a promising material, with suboptimal photon-to-charge carrier conversion efficiency, yet well suited for high-energy photon-detection applications. Here, the optoelectronic and structural properties of pure Cs₂AgBiBr₆ and alkali-metal-substituted (Cs_1−xY_x)₂AgBiBr₆ (Y: Rb⁺, K⁺, Na⁺; x = 0.02) single crystals are investigated. Strikingly, alkali-substitution entails a tunability to the material system in its response to X-rays and structural properties that is most strongly revealed in Rb-substituted compounds whose X-ray sensitivity outperforms other double-perovskite-based devices reported. While the fundamental nature and magnitude of the bandgap remains unchanged, the alkali-substituted materials exhibit a threefold boost in their fundamental carrier recombination lifetime at room temperature. Moreover, an enhanced electron–acoustic phonon scattering is found compared to Cs₂AgBiBr₆. The study thus paves the way for employing cation substitution to tune the properties of double perovskites toward a new material platform for optoelectronics.     

Oxide-Based Electrolyte-Gated Transistors for Spatiotemporal Information Processing

Spiking neural networks (SNNs) sharing large similarity with biological nervous systems are promising to process spatiotemporal information and can provide highly time- and energy-efficient computational paradigms for the Internet-of-Things and edge computing. Nonvolatile electrolyte-gated transistors (EGTs) provide prominent analog switching performance, the most critical feature of synaptic element, and have been recently demonstrated as a promising synaptic device. However, high performance, large-scale EGT arrays, and EGT application for spatiotemporal information processing in an SNN are yet to be demonstrated. Here, an oxide-based EGT employing amorphous Nb₂O₅ and Li_xSiO₂ is introduced as the channel and electrolyte gate materials, respectively, and integrated into a 32 × 32 EGT array. The engineered EGTs show a quasi-linear update, good endurance (10⁶) and retention, a high switching speed of 100 ns, ultralow readout conductance ( < 100 nS), and ultralow areal switching energy density (20 fJ µ m⁻²). The prominent analog switching performance is leveraged for hardware implementation of an SNN with the capability of spatiotemporal information processing, where spike sequences with different timings are able to be efficiently learned and recognized by the EGT array. Finally, this EGT-based spatiotemporal information processing is deployed to detect moving orientation in a tactile sensing system. These results provide an insight into oxide-based EGT devices for energy-efficient neuromorphic computing to support edge application.     

Two‐Terminal Multibit Optical Memory via van der Waals Heterostructure

2D van der Waals (vdWs) heterostructures exhibit intriguing optoelectronic properties in photodetectors, solar cells, and light‐emitting diodes. In addition, these materials have the potential to be further extended to optical memories with promising broadband applications for image sensing, logic gates, and synaptic devices for neuromorphic computing. In particular, high programming voltage, high off‐power consumption, and circuital complexity in integration are primary concerns in the development of three‐terminal optical memory devices. This study describes a multilevel nonvolatile optical memory device with a two‐terminal floating‐gate field‐effect transistor with a MoS₂/hexagonal boron nitride/graphene heterostructure. The device exhibits an extremely low off‐current of ≈10^?14 A and high optical switching on/off current ratio of over ≈10⁶, allowing 18 distinct current levels corresponding to more than four‐bit information storage. Furthermore, it demonstrates an extended endurance of over ≈10⁴ program–erase cycles and a long retention time exceeding 3.6 × 10⁴ s with a low programming voltage of ?10 V. This device paves the way for miniaturization and high‐density integration of future optical memories with vdWs heterostructures.     

Recent Progress in Three‐Terminal Artificial Synapses: From Device to System

Synapses are essential to the transmission of nervous signals. Synaptic plasticity allows changes in synaptic strength that make a brain capable of learning from experience. During development of neuromorphic electronics, great efforts have been made to design and fabricate electronic devices that emulate synapses. Three‐terminal artificial synapses have the merits of concurrently transmitting signals and learning. Inorganic and organic electronic synapses have mimicked plasticity and learning. Optoelectronic synapses and photonic synapses have the prospective benefits of low electrical energy loss, high bandwidth, and mechanical robustness. These artificial synapses provide new opportunities for the development of neuromorphic systems that can use parallel processing to manipulate datasets in real time. Synaptic devices have also been used to build artificial sensory systems. Here, recent progress in the development and application of three‐terminal artificial synapses and artificial sensory systems is reviewed.