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.     

Artificial Synapses Emulated by an Electrolyte‐Gated Tungsten‐Oxide Transistor

Considering that the human brain uses ≈10¹⁵ synapses to operate, the development of effective artificial synapses is essential to build brain‐inspired computing systems. In biological synapses, the voltage‐gated ion channels are very important for regulating the action‐potential firing. Here, an electrolyte‐gated transistor using WO₃ with a unique tunnel structure, which can emulate the ionic modulation process of biological synapses, is proposed. The transistor successfully realizes synaptic functions of both short‐term and long‐term plasticity. Short‐term plasticity is mimicked with the help of electrolyte ion dynamics under low electrical bias, whereas the long‐term plasticity is realized using proton insertion in WO₃ under high electrical bias. This is a new working approach to control the transition from short‐term memory to long‐term memory using different gate voltage amplitude for artificial synapses. Other essential synaptic behaviors, such as paired pulse facilitation, the depression and potentiation of synaptic weight, as well as spike‐timing‐dependent plasticity are also implemented in this artificial synapse. These results provide a new recipe for designing synaptic electrolyte‐gated transistors through the electrostatic and electrochemical effects.     

Biological Spiking Synapse Constructed from Solution Processed Bimetal Core–Shell Nanoparticle Based Composites

Inspired by the highly parallel processing power and low energy consumption of the biological nervous system, the development of a neuromorphic computing paradigm to mimic brain‐like behaviors with electronic components based artificial synapses may play key roles to eliminate the von Neumann bottleneck. Random resistive access memory (RRAM) is suitable for artificial synapse due to its tunable bidirectional switching behavior. In this work, a biological spiking synapse is developed with solution processed Au@Ag core–shell nanoparticle (NP)‐based RRAM. The device shows highly controllable bistable resistive switching behavior due to the favorable Ag ions migration and filament formation in the composite film, and the good charge trapping and transport property of Au@Ag NPs. Moreover, comprehensive synaptic functions of biosynapse including paired‐pulse depression, paired‐pulse facilitation, post‐tetanic potentiation, spike‐time‐dependent plasticity, and the transformation from short‐term plasticity to long‐term plasticity are emulated. This work demonstrates that the solution processed bimetal core–shell nanoparticle‐based biological spiking synapse provides great potential for the further creation of a neuromorphic computing system.     

Mediating Short‐Term Plasticity in an Artificial Memristive Synapse by the Orientation of Silica Mesopores

Memristive synapses based on resistive switching are promising electronic devices that emulate the synaptic plasticity in neural systems. Short‐term plasticity (STP), reflecting a temporal strengthening of the synaptic connection, allows artificial synapses to perform critical computational functions, such as fast response and information filtering. To mediate this fundamental property in memristive electronic devices, the regulation of the dynamic resistive change is necessary for an artificial synapse. Here, it is demonstrated that the orientation of mesopores in the dielectric silica layer can be used to modulate the STP of an artificial memristive synapse. The dielectric silica layer with vertical mesopores can facilitate the formation of a conductive pathway, which underlies a lower set voltage (≈1.0 V) compared to these with parallel mesopores (≈1.2 V) and dense amorphous silica (≈2.0 V). Also, the artificial memristive synapses with vertical mesopores exhibit the fastest current increase by successive voltage pulses. Finally, oriented silica mesopores are designed for varying the relaxation time of memory, and thus the successful mediation of STP is achieved. The implementation of mesoporous orientation provides a new perspective for engineering artificial synapses with multilevel learning and forgetting capability, which is essential for neuromorphic computing.     

Environment‐Adaptable Artificial Visual Perception Behaviors Using a Light‐Adjustable Optoelectronic Neuromorphic Device Array

Emulating the biological visual perception system typically requires a complex architecture including the integration of an artificial retina and optic nerves with various synaptic behaviors. However, self‐adaptive synaptic behaviors, which are frequently translated into visual nerves to adjust environmental light intensities, have been one of the serious challenges for the artificial visual perception system. Here, an artificial optoelectronic neuromorphic device array to emulate the light‐adaptable synaptic functions (photopic and scotopic adaptation) of the biological visual perception system is presented. By employing an artificial visual perception circuit including a metal chalcogenide photoreceptor transistor and a metal oxide synaptic transistor, the optoelectronic neuromorphic device successfully demonstrates diverse visual synaptic functions such as phototriggered short‐term plasticity, long‐term potentiation, and neural facilitation. More importantly, the environment‐adaptable perception behaviors at various levels of the light illumination are well reproduced by adjusting load transistor in the circuit, exhibiting the acts of variable dynamic ranges of biological system. This development paves a new way to fabricate an environmental‐adaptable artificial visual perception system with profound implications for the field of future neuromorphic electronics.     

The Design of 3D‐Interface Architecture in an Ultralow‐Power,Electrospun Single‐Fiber Synaptic Transistor for Neuromorphic Computing

Synaptic electronics is a new technology for developing functional electronic devices that can mimic the structure and functions of biological counterparts. It has broad application prospects in wearable computing chips, human–machine interfaces, and neuron prostheses. These types of applications require synaptic devices with ultralow energy consumption as the effective energy supply for wearable electronics, which is still very difficult. Here, artificial synapse emulation is demonstrated by solid‐ion gated organic field‐effect transistors (OFETs) with a 3D‐interface conducting channel for ultralow‐power synaptic simulation. The basic features of the artificial synapse, excitatory postsynaptic current (EPSC), paired‐pulse facilitation (PPF), and high‐pass filtering, are successfully realized. Furthermore, the single‐fiber based artificial synapse can be operated by an ultralow presynaptic spike down to ?0.5 mV with an ultralow reading voltage at ?0.1 mV due to the large contact surface between the ionic electrolyte and fiber‐like semiconducting channel. Therefore, the ultralow energy consumption at one spike of the artificial synapse can be realized as low as ≈3.9 fJ, which provides great potential in a low‐power integrated synaptic circuit.     

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.     

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.     

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.     

Photonic Synapses Based on Inorganic Perovskite Quantum Dots for Neuromorphic Computing

Inspired by the biological neuromorphic system, which exhibits a high degree of connectivity to process huge amounts of information, photonic memory is expected to pave a way to overcome the von Neumann bottleneck for nonconventional computing. Here, a photonic flash memory based on all‐inorganic CsPbBr₃ perovskite quantum dots (QDs) is demonstrated. The heterostructure formed between the CsPbBr₃ QDs and semiconductor layer serves as a basis for optically programmable and electrically erasable characteristics of the memory device. Furthermore, synapse functions including short‐term plasticity, long‐term plasticity, and spike‐rate‐dependent plasticity are emulated at the device level. The photonic potentiation and electrical habituation are implemented and the synaptic weight exhibits multiple wavelength response from 365, 450, 520 to 660 nm. These results may locate the stage for further thrilling novel advances in perovskite‐based memories.     

Light‐Stimulated Synaptic Transistors Fabricated by a Facile Solution Process Based on Inorganic Perovskite Quantum Dots and Organic Semiconductors

Implementation of artificial intelligent systems with light‐stimulated synaptic emulators may enhance computational speed by providing devices with high bandwidth, low power computation requirements, and low crosstalk. One of the key challenges is to develop light‐stimulated devices that can response to light signals in a neuron‐/synapse‐like fashion. A simple and effective solution process to fabricate light‐stimulated synaptic transistors (LSSTs) based on inorganic halide perovskite quantum dots (IHP QDs) and organic semiconductors (OSCs) is reported. Blending IHP QDs and OSCs not only improves the charge separation efficiency of the photoexcited charges, but also induces delayed decay of the photocurrent in the IHP QDs/OSCs hybrid film. The enhanced charge separation efficiency results in high photoresponsivity, while the induced delayed decay of the photocurrent is critical to achieving light‐stimulating devices with a memory effect, which are important for achieving high synaptic performance. The LSSTs can respond to light signals in a highly neuron‐/synapse‐like fashion. Both short‐term and long‐term synaptic behaviors have been realized, which may lay the foundation for the future implementation of artificial intelligent systems that are enabled by light signals. More significantly, LSSTs are fabricated by a facile solution process which can be easily applied to large‐scale samples.     

Ion Gated Synaptic Transistors Based on 2D van der Waals Crystals with Tunable Diffusive Dynamics

Neuromorphic computing represents an innovative technology that can perform intelligent and energy‐efficient computation, whereas construction of neuromorphic systems requires biorealistic synaptic elements with rich dynamics that can be tuned based on a robust mechanism. Here, an ionic‐gating‐modulated synaptic transistor based on layered crystals of transitional metal dichalcogenides and phosphorus trichalcogenides is demonstrated, which produce a diversity of short‐term and long‐term plasticity including excitatory postsynaptic current, paired pulse facilitation, spiking‐rate‐dependent plasticity, dynamic filtering, etc., with remarkable linearity and ultralow energy consumption of ≈30 fJ per spike. Detailed transmission electron microscopy characterization and ab initio calculation reveal two‐stage ionic gating effects, namely, surface adsorption and internal intercalation in the channel medium, causing different poststimulation diffusive dynamics and thus accounting for the observed short‐term and long‐term plasticity, respectively. The synaptic activity can therefore be effectively manipulated by tailoring the ionic gating and consequent diffusion dynamics with varied thickness and structure of the van der Waals material as well as the number, duration, rate, and polarity of gate stimulations, making the present synaptic transistors intriguing candidates for low‐power neuromorphic systems.     

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.     

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.     

Near‐Infrared Annihilation of Conductive Filaments in Quasiplane MoSe2/Bi2Se3 Nanosheets for Mimicking Heterosynaptic Plasticity

It is desirable to imitate synaptic functionality to break through the memory wall in traditional von Neumann architecture. Modulating heterosynaptic plasticity between pre‐ and postneurons by another modulatory interneuron ensures the computing system to display more complicated functions. Optoelectronic devices facilitate the inspiration for high‐performance artificial heterosynaptic systems. Nevertheless, the utilization of near‐infrared (NIR) irradiation to act as a modulatory terminal for heterosynaptic plasticity emulation has not yet been realized. Here, an NIR resistive random access memory (RRAM) is reported, based on quasiplane MoSe₂/Bi₂Se₃ heterostructure in which the anomalous NIR threshold switching and NIR reset operation are realized. Furthermore, it is shown that such an NIR irradiation can be employed as a modulatory terminal to emulate heterosynaptic plasticity. The reconfigurable 2D image recognition is also demonstrated by an RRAM crossbar array. NIR annihilation effect in quasiplane MoSe₂/Bi₂Se₃ nanosheets may open a path toward optical‐modulated in‐memory computing and artificial retinal prostheses.     

Ultrasensitive Memristive Synapses Based on Lightly Oxidized Sulfide Films

For biological synapses, high sensitivity is crucial for transmitting information quickly and accurately. Compared to biological synapses, memristive ones show a much lower sensitivity to electrical stimuli since much higher voltages are needed to induce synaptic plasticity. Yet, little attention has been paid to enhancing the sensitivity of synaptic devices. Here, electrochemical metallization memory cells based on lightly oxidized ZnS films are found to show highly controllable memristive switching with an ultralow SET voltage of several millivolts, which likely originates from a two‐layer structure of ZnS films, i.e., the lightly oxidized and unoxidized layers, where the filament rupture/rejuvenation is confined to the two‐layer interface region several nanometers in thickness due to different ion transport rates in these two layers. Based on such devices, an ultrasensitive memristive synapse is realized where the synaptic functions of both short‐term plasticity and long‐term potentiation are emulated by applying electrical stimuli several millivolts in amplitude, whose sensitivity greatly surpasses that of biological synapses. The dynamic processes of memorizing and forgetting are mimicked through a 5 × 5 memristive synapse array. In addition, the ultralow operating voltage provides another effective solution to the relatively high energy consumption of synaptic devices besides reducing the operating current and pulse width.     

WSe2 Homojunction Devices: Electrostatically Configurable as Diodes,MOSFETs, and Tunnel FETs for Reconfigurable Computing

In this paper, electrostatically configurable 2D tungsten diselenide (WSe₂) electronic devices are demonstrated. Utilizing a novel triple‐gate design, a WSe₂ device is able to operate as a tunneling field‐effect transistor (TFET), a metal–oxide–semiconductor field‐effect transistor (MOSFET) as well as a diode, by electrostatically tuning the channel doping to the desired profile. The implementation of scaled gate dielectric and gate electrode spacing enables higher band‐to‐band tunneling transmission with the best observed subthreshold swing (SS) among all reported homojunction TFETs on 2D materials. Self‐consistent full‐band atomistic quantum transport simulations quantitatively agree with electrical measurements of both the MOSFET and TFET and suggest that scaling gate oxide below 3 nm is necessary to achieve sub‐60 mV dec^?1 SS, while further improvement can be obtained by optimizing the spacers. Diode operation is also demonstrated with the best ideality factor of 1.5, owing to the enhanced electrostatic control compared to previous reports. This research sheds light on the potential of utilizing electrostatic doping scheme for low‐power electronics and opens a path toward novel designs of field programmable mixed analog/digital circuitry for reconfigurable computing.     

Short-term plasticity and long-term potentiation mimicked in single inorganic synapses

Memory is believed to occur in the human brain as a result of two types of synaptic plasticity: short-term plasticity (STP) and long-term potentiation (LTP; refs 1-4). In neuromorphic engineering, emulation of known neural behaviour has proven to be difficult to implement in software because of the highly complex interconnected nature of thought processes. Here we report the discovery of a Ag(2)S inorganic synapse, which emulates the synaptic functions of both STP and LTP characteristics through the use of input pulse repetition time. The structure known as an atomic switch, operating at critical voltages, stores information as STP with a spontaneous decay of conductance level in response to intermittent input stimuli, whereas frequent stimulation results in a transition to LTP. The Ag(2)S inorganic synapse has interesting characteristics with analogies to an individual biological synapse, and achieves dynamic memorization in a single device without the need of external preprogramming. A psychological model related to the process of memorizing and forgetting is also demonstrated using the inorganic synapses. Our Ag(2)S element indicates a breakthrough in mimicking synaptic behaviour essential for the further creation of artificial neural systems that emulate characteristics of human memory.     

Doping Modulated Carbon Nanotube Synapstors for a Spike Neuromorphic Module

A doping‐modulated carbon nanotube (CNT) electronic device, called a “synapstor,” emulates the function of a biological synapse. The CNT synapstor has a field‐effect transistor structure with a random CNT network as its channel. An aluminium oxide (Al₂O₃) film is deposited over half of the CNT channel in the synapstor, converting the covered part of the CNT from p‐type to n‐type, forming a p–n junction in the CNT channel and increasing the Schottky barrier between the n‐type CNT and its metal contact. This scheme significantly improves the postsynaptic current (PSC) from the synapstor, extends the tuning range of the plasticity, and reduces the power consumption of the CNT synapstor. A spike neuromorphic module is fabricated by integrating the CNT synapstors with a Si‐based “soma” circuit. Spike parallel processing, memory, and plasticity functions of the module are demonstrated. The module could potentially be integrated and scaled up to emulate a biological neural network with parallel high‐speed signal processing, low power consumption, memory, and learning capabilities.