Neuro-Receptor Mediated Synapse Device Based on Crumpled MXene Ti3C2Tx Nanosheets

Artificial synapse devices can simulate the neuro-transmission in a completely electronic way, but the neuro-biochemical responses are still a challenge for them. Here, a novel three-terminal (3T) neuro-receptor-mediated (acetylcholine receptor (AChR) as a proof-of-concept) synapse device (NR-S) based on the solution–MXene interface is presented. It is demonstrated that the synaptic plasticity behavior triggered by neuro-transmitter (ACh) and the pathogenic autoantibody (AChR-ab) induced neuronal damage that can be detected and recorded. The improved sensitivities, including the linear responses to ACh in an extremely wide range (1 am to 1 µm ) and ultra-low (1 am ) limit of detection, are obtained using crumpled MXene. Furthermore, the ability of the proposed NR-S to determine the tiny neuronal injury caused by only 10 ng mL⁻¹ AChR-ab is conceptually proven. Collectively, the novel 3T NR-S has good application prospects in the field of the neuromorphic chip for not only realizing the bionic simulation of the chemically modulated or injured neuro-transmission but also offering an efficient experimental platform for neuro-biochemistry studies.     

硫系非晶态半导体人工神经突触的可塑性

模拟大脑中的神经突触是实现下一代计算机——类脑神经形态计算的关键一步。为了利用光子模拟神经突触的可塑性进而发展全光人工神经突触器件,文章开展了基于可控光诱导抑制效应的硫系非晶态半导体人工神经突触的实验研究。分析了材料化学组分和抽运光功率对该人工神经突触的调控作用,描述了该人工神经突触的可塑性。结果表明掺入不同杂质的硫系非晶态半导体平面波导具有不同的可控光诱导抑制过程,且抑制深度受控于抽运光功率的变化。基于这些特性,该人工神经突触展现出了配对脉冲易化功能、短程抑制功能、长程抑制功能,具有良好的可塑性。     

Dual-Modal Optoelectronic Synaptic Devices with Versatile Synaptic Plasticity

Optoelectronic synaptic devices that mimic biological synapses are critical building blocks of artificial neural networks (ANN) based on optoelectronic integration. Here it is shown that an optoelectronic synaptic device based on the hybrid structure of silicon nanocrystals (Si NCs) and poly(3-hexylthiophene) (P3HT) can work with dual modes, exhibiting versatile synaptic plasticity. In the three-terminal mode, the device is a synaptic transistor, which has wavelength-selective synaptic plasticity due to potential wells enabled by the Si NCs/P3HT hybrid structure. In the two-terminal mode, it is a synaptic metal-oxide-semiconductor (MOS) device, which is capable of mimicking spike-rate-dependent plasticity (SRDP) and metaplasticity with optical stimulation. Based on the wavelength-selective synaptic plasticity a light-stimulated ANN is proposed to recognize handwritten digits with an accuracy of around 90.4%. In addition, the SRDP and metaplasticity may be well used for the simulation of edge detection of images, facilitating real-time image processing.     

Piezotronic Graphene Artificial Sensory Synapse

The human somatosensory system, consisting of receptors, transmitters, and synapses, functions as the medium for external mechanical stimuli perception and sensing signal delivery/processing. Developing sophisticated artificial sensory synapses with a high performance, uncomplicated fabrication process, and low power consumption is still a great challenge. Here, a piezotronic graphene artificial sensory synapse developed by integrating piezoelectric nanogenerator (PENG) with an ion gel–gated transistor is demonstrated. The piezopotential originating from PENG can efficiently power the synaptic device due to the formation of electrical double layers at the interface of the ion gel/electrode and ion gel/graphene. Meanwhile, the piezopotential coupling is capable of linking the spatiotemporal strain information (strain amplitude and duration) with the postsynaptic current. The synaptic weights can be readily modulated by the strain pulses. Typical properties of a synapse including excitation/inhibition, synaptic plasticity, and paired pulse facilitation are successfully demonstrated. The dynamic modulation of a sensory synapse is also achieved based on dual perceptual presynaptic PENGs coupling to a single postsynaptic transistor. This work provides a new insight into developing piezotronic synaptic devices in neuromorphic computing, which is of great significance in future self‐powered electronic skin with artificial intelligence, a neuromorphic interface for neurorobotics, human–robot interaction, an intelligent piezotronic transistor, etc.     

Photonic Organolead Halide Perovskite Artificial Synapse Capable of Accelerated Learning at Low Power Inspired by Dopamine‐Facilitated Synaptic Activity

The ability of high‐order tuning of the synaptic plasticity in an artificial synapse can offer significant improvement in the processing time, low‐power recognition, and learning capability in a neuro‐inspired computing system. Inspired by light‐assisted dopamine‐facilitated synaptic activity, which achieves rapid learning and adaptation by lowering the threshold of the synaptic plasticity, a two‐terminal organolead halide perovskite (OHP)‐based photonic synapse is fabricated and designed in which the synaptic plasticity is modified by both electrical pulses and light illumination. Owing to the accelerated migration of the iodine vacancy inherently existing in the coated OHP film under light illumination, the OHP synaptic device exhibits light‐tunable synaptic functionalities with very low programming inputs (≈0.1 V). It is also demonstrated that the threshold of the long‐term potentiation decreases and synaptic weight further modulates when light illuminates the device, which is phenomenologically analogous to the dopamine‐assisted synaptic process. Notably, under light exposure, the OHP synaptic device achieves rapid pattern recognition with ≈81.8% accuracy after only 2000 learning phases (60 000 learning phases = one epoch) with a low‐power consumption (4.82 nW/the initial update for potentiation), which is ≈2.6 × 10³ times lower than when the synaptic weights are updated by only high electrical pulses.     

基于铁电材料的有机光电突触晶体管研究

模拟生物突触结构的设备是实现神经网络计算的可行方案之一,其中人工视网膜器件为机器视觉和图像识别的实现提供了有力支持。通过旋涂制备聚偏氟乙烯-三氟乙烯(P(VDF-TrFE))制备铁电栅层,热蒸发酞菁铜(CuPc)作为半导体层,探究该晶体管模拟突触功能的光电响应。实验结果表明,该光电晶体管在625 nm具有显著的光响应,其能够产生兴奋性突触后电流(EPSC)并实现短期可塑性到长期可塑性的转变以及高通滤波功能。利用剩余极化强度模拟了大脑学习过程中提前施加注意的行为。此外,以栅电压和光照作为独立输入逻辑信号,在单个晶体管中实现了“与”和“或”的布尔逻辑功能。上述结果表明,CuPc可以与铁电材料进行良好结合并制备出具有突触响应特点的光电晶体管,这为人工视网膜器件的开发提供了有机铁电器件的参考。     

Ligand Exchange Reaction Enables Digital-To-Analog Resistive Switching and Artificial Synapse within Metal Nanoparticles

The transition between digital and analog resistive switching in a single memristive device is beneficial for the reduction in power consumption and circuit complexity, the development of in-memory neuromorphic computing, and the discovery of new switching mechanisms. However, achieving such transition is a challenge due to the complex switching mechanisms and device designs. Here, it is shown that the digital-to-analog resistive switching can be realized by the ligand exchange reaction of metal nanoparticles. The field-injected copper cations migrate within carboxyl-functionalized gold nanoparticle (AuNP) layer that are subsequently reduced into metallic filaments, enabling an abrupt resistive switching. Importantly, when the carboxyl groups on the gold nanoparticle are replaced by amino-carboxyl ligands, the copper cations coordinate with the new ligands and create the conductance bridges to reduce the electron tunneling/hopping energy barriers, leading to continuous modulation in conductivity. This analog resistive switching allows to implement several important synaptic functions such as potentiation/depression, paired-pulse facilitation, learning behaviors including forgetting curves and spaced learning effect. In the end, due to the non-volatile characteristics, the gold nanoparticle synapse is used to build single layer perceptron for pattern classification with 100% accuracy.     

Tuning a Binary Ferromagnet into a Multistate Synapse with Spin–Orbit‐Torque‐Induced Plasticity

Ferromagnets with binary states are limited for applications as artificial synapses for neuromorphic computing. Here, it is shown how synaptic plasticity of a perpendicular ferromagnetic layer (FM1) can be obtained when it is interlayer exchange‐coupled by another in‐plane ferromagnetic layer (FM2), where a magnetic field‐free current‐driven multistate magnetization switching of FM1 in the Pt/FM1/Ta/FM2 structure is induced by spin–orbit torque. Current pulses are used to set the perpendicular magnetization state, which acts as the synapse weight, and spintronic implementation of the excitatory/inhibitory postsynaptic potentials and spike timing‐dependent plasticity are demonstrated. This functionality is made possible by the action of the in‐plane interlayer exchange coupling field which leads to broadened, multistate magnetic reversal characteristics. Numerical simulations, combined with investigations of a reference sample with a single perpendicular magnetized Pt/FM1/Ta structure, reveal that the broadening is due to the in‐plane field component tuning the efficiency of the spin–orbit torque to drive domain walls across a landscape of varying pinning potentials. The conventionally binary FM1 inside the Pt/FM1/Ta/FM2 structure with an inherent in‐plane coupling field is therefore tuned into a multistate perpendicular ferromagnet and represents a synaptic emulator for neuromorphic computing, demonstrating a significant pathway toward a combination of spintronics and synaptic electronics.     

A Reliable All-2D Materials Artificial Synapse for High Energy-Efficient Neuromorphic Computing

High-performance artificial synaptic devices are indispensable for developing neuromorphic computing systems with high energy efficiency. However, the reliability and variability issues of existing devices such as nonlinear and asymmetric weight update are the major hurdles in their practical applications for energy-efficient neuromorphic computing. Here, a two-terminal floating-gate memory (2TFGM) based artificial synapse built from all-2D van der Waals materials is reported. The 2TFGM synaptic device exhibits excellent linear and symmetric weight update characteristics with high reliability and tunability. In particular, the high linearity and symmetric synaptic weight realized by simple programming with identical pulses can eliminate the additional latency and power consumption caused by the peripheral circuit design and achieve an ultralow energy consumption for the synapses in the neural network implementation. A large number of states up to ≈3000, high switching speed of 40 ns and low energy consumption of 18 fJ for a single pulse have been demonstrated experimentally. A high classification accuracy up to 97.7% (close to the software baseline of 98%) has been achieved in the Modified National Institute of Standards and Technology (MNIST) simulations based on the experimental data. These results demonstrate the potential of all-2D 2TFGM for high-speed and low-power neuromorphic computing.     

A Flexible and Biomimetic Olfactory Synapse with Gasotransmitter-Mediated Plasticity (Adv. Funct. Mater. 18/2023)

Neuromorphic electronics has demonstrated great promise in mimicking the sensory and memory functions of biological systems. However, synaptic devices with desirable sensitivity, selectivity, and operational voltage imitating the olfactory system have rarely been reported. Here, a flexible and biomimetic olfactory synapse based on an organic electrochemical transistor (OECT) coupled with a breath-figure derived porous solid polymer electrolyte (SPE) is proposed. The device demonstrates excellent sensitivity with a ppb-level response limit and desirable selectivity toward hydrogen sulfide (H₂S) over other gases, and successfully achieves wireless real-time detection of excessive concentration of H₂S from rotten eggs. H₂S-mediated synaptic plasticity is accomplished with the device and typical synaptic behaviors are realized, including short-term memory (STM), long-term memory (LTM), transition from STM to LTM, etc., enabling the imitation of potential cumulative damages upon H₂S exposure. The proposed device paves new ways toward next-generation olfactory systems capable of sensing and memorizing functionalities mimicking neurobiological systems, offering critical materials strategies to accomplish intelligent artificial sensory systems.     

Bio-Inspired Photoelectric Artificial Synapse based on Two-Dimensional Ti3C2Tx MXenes Floating Gate

The highly parallel artificial neural systems based on transistor-like devices have recently attracted widespread attention due to their high-efficiency computing potential and the ability to mimic biological neurobehavior. For the past decades, plenty of breakthroughs related to synaptic transistors have been investigated and reported. In this work, a kind of photoelectronic transistor that successfully mimics the behaviors of biological synapses has been proposed and systematically analyzed. For the individual device, MXenes and the self-assembled titanium dioxide on the nanosheet surface serve as floating gate and tunneling layers, respectively. As the unit electronics of the neural network, the typical synaptic behaviors and the reliable memory stability of the synaptic transistors have been demonstrated through the voltage test. Furthermore, for the first time, the UV-responsive synaptic properties of the MXenes floating gated transistor and its applications, including conditional reflex and supervised learning, have been measured and realized. These photoelectric synapse characteristics illustrate the great potential of the device in bio-imitation vision applications. Finally, through the simulation based on an artificial neural network algorithm, the device successfully realizes the recognition application of handwritten digital images. Thus, this article provides a highly feasible solution for applying artificial synaptic devices to hardware neuromorphic networks.     

All-Optically Controlled Artificial Synapse Based on Full Oxides for Low-Power Visible Neural Network Computing

Artificial synapse devices are dedicated to overcoming the von Neumann bottleneck. Adopting light signals in visual information processing and computing is vital for developing next-generation artificial neuromorphic systems. A strategy to construct all-optically controlled artificial synaptic devices based on full oxides with amorphous ZnAlSnO/SnO heterojunction in a two-terminal planar configuration is proposed. All synaptic behaviors are operated in the visible optical pathway, with excitatory synapse under red (635 nm) light and inhibitory synapse under green (532 nm) and blue (405 nm) lights. Based on the different inhibitory effects, two modes of long-term depression (LTD) and RESET processes can be implemented through green and blue lights, respectively. The energy consumption of an event can be as low as 0.75 pJ. A three-layer perceptron model is designed to classify 28 × 28-pixel handwritten digital images and performed supervised learning using a backpropagation algorithm, demonstrating the bio-visually inspired neuromorphic computing with a training accuracy of 92.74%. The all-optically controlled artificial synapses with write/erasure behaviors in visible RGB region and rational microelectronic process, as presented in this work, are essential in developing future artificial neuromorphic systems and highlight the huge potential of next-generation computer systems.     

Ultrasensitive Freestanding and Mechanically Durable Artificial Synapse with Attojoule Power Based on Na-Salt Doped Polymer for Biocompatible Neuromorphic Interface

The human brain, with high energy-efficient and parallel processing ability, inspires to mitigate power issues perplexing von Neumann architecture. As one of the essential components constructing the human brain, the emulation of biological synapses exploiting electronic devices consuming power at a biological level lays the foundation for the implementation of energy-efficient neuromorphic computing. Besides, signal matching between biologically-related stimuli and the driving voltage of artificial synapses helps to realize intelligent neuromorphic interfaces and sustainable energy. Here, ultra-sensitive artificial synapse stimulated at 1 mV with energy consumption of 132 attojoule/synaptic event is demonstrated. Biological signal matching and low power application are realized simultaneously based on sodium acetate (NaAc) doped polyvinyl alcohol (PVA) electrolyte. The biphasic current, which comprises the electrical- and ion-mediation current component, contributes to enrich synaptic functions compared to monophasic synaptic behavior. Moreover, freestanding NaAc-doped PVA membrane functions as both dielectric layer and mechanical support and facilitates to achieve flexible, transferable artificial synapse, which maintains functional stability at an ultralow voltage and power even after bending tests. Thus, encompassing superior sensitivity, low energy, and multiple functionalities with flexible, self-supported, biocompatible property, takes a step to construct energetically-efficient, complex neuromorphic systems for wearable, implantable medicines as well as smart bio-electronic interfaces.     

HfO2-Based Memristor as an Artificial Synapse for Neuromorphic Computing with Tri-Layer HfO2/BiFeO3/HfO2 Design

Neuromorphic devices are among the most emerging electronic components to realize artificial neural systems and replace traditional complementary metal–oxide semiconductor devices in recent times. In this work, tri-layer HfO₂/BiFeO₃(BFO)/HfO₂ memristors are designed by inserting traditional ferroelectric BFO layers measuring ≈4 nm after thickness optimization. The novel designed memristor shows excellent resistive switching (RS) performance such as a storage window of 10⁴ and multi-level storage ability. Remarkably, essential synaptic functions can be successfully realized on the basis of the linearity of conductance modulation. The pattern recognition simulation based on neuromorphic network is conducted with 91.2% high recognition accuracy. To explore the RS performance enhancement and artificial synaptic behaviors, conductive filaments (CFs) composed of Hafnium (Hf) single crystal with a hexaganal lattice structure are observed using high-resolution transmission electron microscopy. It is reasonable to believe that the sufficient oxygen vacancies in the inserting BFO thin film play a crucial role in adjusting the morphology and growth of Hf CFs, which leads to the promising synaptic and enhanced RS behavior, thus demonstrating the potential of this memristor for use in neuromorphic computing.     

Feedforward Photoadaptive Organic Neuromorphic Transistor with Mixed-Weight Plasticity for Augmenting Perception

Organic photoelectric neuromorphic devices that mimic the brain are widely explored for advanced perceptual computing. However, current individual neuromorphic synaptic devices mainly focus on utilizing linear models to process optoelectronic signals, which means that there is a lack of effective response to nonlinear structural information from the real world, severely limiting the computational efficiency and adaptability of networks to static and dynamic information. Here, a feedforward photoadaptive organic neuromorphic transistor with mixed-weight plasticity is reported. By introducing the potential of the space charge to couple gate potential, photoexcitation, and photoinhibition occur successively in the channel under the interference of constant light intensity, which enables the device to transform from a linear model to a nonlinear model. As a result, the device exhibits a dynamic range of over 100 dB, exceeding the currently reported similar neuromorphic synaptic devices. Further, the device achieves adaptive tone mapping within 5 s for static information and achieves over 90% robustness recognition accuracy for dynamic information. Therefore, this work provides a new strategy for developing advanced neuromorphic devices and has great potential in the fields of intelligent driving and brain-like computing.     

Electrospun Nanofiber-Based Synaptic Transistor with Tunable Plasticity for Neuromorphic Computing

Biological synapses are the operational connection of the neurons for signal transmission in neuromorphic networks and hardware implementation combined with electrospun 1D nanofibers have realized its functionality for complicated computing tasks in basic three-terminal field-effect transistors with gate-controlled channel conductance. However, it still lacks the fundamental understanding that how the technological parameters influence the signal intensity of the information processing in the neural systems for the nanofiber-based synaptic transistors. Here, by tuning the electrospinning parameters and introducing the channel surface doping, an electrospun ZnO nanofiber-based transistor with tunable plasticity is presented to emulate the changing synaptic functions. The underlying mechanism of influence of carrier concentration and mobility on the device's electrical and synaptic performance is revealed as well. Short-term plasticity behaviors including paired-pulse facilitation, spike duration-dependent plasticity, and dynamic filtering are tuned in this fiber-based device. Furthermore, Perovskite-doped devices with ultralow energy consumption down to ≈0.2554 fJ and their handwritten recognition application show the great potential of synaptic transistors based on a 1D nanostructure active layer for building next-generation neuromorphic networks.     

Pristine Titanium Carbide MXene Films with Environmentally Stable Conductivity and Superior Mechanical Strength

2D titanium carbide (Ti₃C₂T_x MXene) has potential application in flexible/transparent conductors because of its metallic conductivity and solution processability. However, solution‐processed Ti₃C₂T_x films suffer from poor hydration stability and mechanical performance that stem from the presence of intercalants, which are unavoidably introduced during the preparation of Ti₃C₂T_x suspension. A proton acid colloidal processing approach is developed to remove the extrinsic intercalants in Ti₃C₂T_x film materials, producing pristine Ti₃C₂T_x films with significantly enhanced conductivity, mechanical strength, and environmental stability. Typically, pristine Ti₃C₂T_x films show more than twofold higher conductivity (10 400 S cm^?1 vs 4620 S cm^?1) and up to 11‐ and 32‐times higher strength and strain energy at failure (112 MPa, 1,480 kJ m^?3, vs 10 MPa, 45 kJ m^?3) than films prepared without proton acid processing. Simultaneously, the conductivity and mechanical integrity of pristine films are also largely retained during the long‐term storage in H₂O/O₂ environment. The improvement in mechanical performance and conductivity is originated from the intrinsic strong interaction between Ti₃C₂T_x layers, and the absence of extrinsic intercalants makes pristine Ti₃C₂T_x films stable in humidity by blocking the intercalation of H₂O/O₂. This method makes the material more competitive for real‐world applications such as electromagnetic interference shielding.