Optoelectronic Synapses Based on MXene/Violet Phosphorus van der Waals Heterojunctions for Visual‑Olfactory Crossmodal Perception

The crossmodal interaction of different senses,which is an important basis for learning and memory in the human brain,is highly desired to be mimicked at the device level for developing neuromorphic crossmodal perception,but related researches are scarce.Here,we demonstrate an optoelectronic synapse for vision-olfactory crossmodal perception based on MXene/violet phosphorus(VP)van der Waals heterojunctions.Benefiting from the efficient separation and transport of photogenerated carriers facilitated by conductive MXene,the photoelectric responsivity of VP is dramatically enhanced by 7 orders of magnitude,reaching up to 7.7 A W^(−1).Excited by ultraviolet light,multiple synaptic functions,including excitatory postsynaptic currents,pairedpulse facilitation,short/long-term plasticity and“learning-experience”behavior,were demonstrated with a low power consumption.Furthermore,the proposed optoelectronic synapse exhibits distinct synaptic behaviors in different gas environments,enabling it to simulate the interaction of visual and olfactory information for crossmodal perception.This work demonstrates the great potential of VP in optoelectronics and provides a promising platform for applications such as virtual reality and neurorobotics.

Organic Optoelectronic Synapses for Sound Perception

The neuromorphic systems for sound perception is under highly demanding for the future bioinspired electronics and humanoid robots.However,the sound perception based on volume,tone and timbre remains unknown.Herein,organic optoelectronic synapses(OOSs)are constructed for unprecedented sound recognition.The volume,tone and timbre of sound can be regulated appropriately by the input signal of voltages,frequencies and light intensities of OOSs,according to the amplitude,frequency,and waveform of the sound.The quantitative relation between recognition factor(ζ)and postsynaptic current(I=I_(light)−I_(dark))is established to achieve sound perception.Interestingly,the bell sound for University of Chinese Academy of Sciences is recognized with an accuracy of 99.8%.The mechanism studies reveal that the impedance of the interfacial layers play a critical role in the synaptic performances.This contribution presents unprecedented artificial synapses for sound perception at hardware levels.

Amorphous gallium oxide homojunction-based optoelectronic synapse for multi-functional signal processing

In the era of accelerated development in artificial intelligence as well as explosive growth of information and data throughput,underlying hardware devices that can integrate perception and memory while simultaneously offering the bene-fits of low power consumption and high transmission rates are particularly valuable.Neuromorphic devices inspired by the human brain are considered to be one of the most promising successors to the efficient in-sensory process.In this paper,a homojunction-based multi-functional optoelectronic synapse(MFOS)is proposed and testified.It enables a series of basic electri-cal synaptic plasticity,including paired-pulse facilitation/depression(PPF/PPD)and long-term promotion/depression(LTP/LTD).In addition,the synaptic behaviors induced by electrical signals could be instead achieved through optical signals,where its sen-sitivity to optical frequency allows the MFOS to simulate high-pass filtering applications in situ and the perception capability integrated into memory endows it with the information acquisition and processing functions as a visual system.Meanwhile,the MFOS exhibits its performances of associative learning and logic gates following the illumination with two different wave-lengths.As a result,the proposed MFOS offers a solution for the realization of intelligent visual system and bionic electronic eye,and will provide more diverse application scenarios for future neuromorphic computing.

2D-materials-based optoelectronic synapses for neuromorphic applications

Optoelectronic artificial synapses(OEASs)are essential for realizing artificial neural networks(ANNs)in nextgeneration information processing that has high transmission speed,high bandwidth,and low power consumption.Two-dimensional(2D)materials endowed with strong light-matter interactions and atomically thin dangling-bond-free surfaces are candidates for achieving versatile optoelectronics.Developing 2D OEASs for future neuromorphic applications is significant to break the bottleneck of von Neumann architecture and achieve future artificial intelligence systems.This review primarily focuses on recent developments in advanced 2D OEASs,discussing their working mechanism as well as potential applications.Common materials,device structures,and their synthesis and construction methods are also summarized.Finally,the prospects for future 2D OEASs from the perspectives of materials,performance,and applications are briefly described.

Gate-tunable large-scale flexible monolayer MoS_(2)devices for photodetectors and optoelectronic synapses

Photodetectors and optoelectronic synapses are vital for construction of artificial visual perception system.However,the hardware implementations of optoelectronic-neuromorphic devices based on conventional architecture usually suffer from poor scalability,light response range,and limited functionalities.Here,large-scale flexible monolayer MoS_(2)devices integrating photodetectors and optoelectronic synapses over the entire visible spectrum in one device have been realized,which can be used in photodetection,optical communication,artificial visual perception system,and optical artificial neural network.By modulating gate voltages,we enable MoS_(2)-based devices to be photodetectors and also optoelectronic synapses.Importantly,the MoS_(2)-based optoelectronic synapses could implement many synaptic functions and neuromorphic characteristics,such as short-term memory(STM),long-term memory(LTM),paired-pulse facilitation(PPF),long-term potentiation(LTP)/long-term depression(LTD),and“learning-experience”behavior.Furthermore,an associative learning behavior(the classical conditioning Pavlov’s dog experiment)was emulated using paired stimulation of optical and voltage pulses.These results facilitate the development of MoS_(2)-based multifunctional optoelectronic devices with a simple device structure,showing great potential for photodetection,optoelectronic neuromorphic computing,human visual systems mimicking,as well as wearable and implantable electronics.

N:ZnO/MoS_(2)-heterostructured flexible synaptic devices enabling optoelectronic co-modulation for robust artificial visual systems

With the merits of non-contact,highly efficient,and parallel computing,optoelectronic synaptic devices combining sensing and memory in a single unit are promising for constructing neuromorphic computing and artificial visual chip.Based on this,a N:ZnO/MoS_(2)-heterostructured flexible optoelectronic synaptic device is developed in this work,and its capability in mimicking the synaptic behaviors is systemically investigated under the electrical and light signals.Versatile synaptic functions,including synaptic plasticity,long-term/short-term memory,and learning-forgetting-relearning property,have been achieved in this synaptic device.Further,an artificial visual memory system integrating sense and memory is emulated with the device array,and the visual memory behavior can be regulated by varying the light parameters.Moreover,the optoelectronic co-modulation behavior is verified by applying mixed electric and light signals to the array.In detail,a transient recovery property is discovered when the electric signals are applied in synergy during the decay of the light response,of which property facilitates the development of robust artificial visual systems.Furthermore,by superimposing electrical signals during the light response process,a differentiated response of the array is achieved,which can be used as a proof of concept for the color perception of the artificial visual system.

Progress of Materials and Devices for Neuromorphic Vision Sensors

The latest developments in bio-inspired neuromorphic vision sensors can be summarized in 3 keywords:smaller,faster,and smarter.(1)Smaller:Devices are becoming more compact by integrating previously separated components such as sensors,memory,and processing units.As a prime example,the transition from traditional sensory vision computing to in-sensor vision computing has shown clear benefits,such as simpler circuitry,lower power consumption,and less data redundancy.(2)Swifter:Owing to the nature of physics,smaller and more integrated devices can detect,process,and react to input more quickly.In addition,the methods for sensing and processing optical information using various materials(such as oxide semiconductors)are evolving.(3)Smarter:Owing to these two main research directions,we can expect advanced applications such as adaptive vision sensors,collision sensors,and nociceptive sensors.This review mainly focuses on the recent progress,working mechanisms,image pre-processing techniques,and advanced features of two types of neuromorphic vision sensors based on near-sensor and in-sensor vision computing methodologies.

Ultrasensitive solar-blind ultraviolet detection and optoelectronic neuromorphic computing using α-In_(2)Se_(3)phototransistors

Detection of solar-blind ultraviolet(SB-UV)light is important in applications like confidential communication,flame detection,and missile warning system.However,the existing SB-UV photodetectors still show low sensitivities.In this work,we demonstrate the extraordinary SB-UV detection performance of α-In_(2)Se_(3 )phototransistors.Benefiting from the coupled semiconductor and ferroelectricity property,the phototransistor has an ultraweak detectable power of 17.85 fW,an ultrahigh gain of 1.2×10^(6),a responsivity of 2.6×10^(5) A/W,a detectivity of 1.3×10^(16) Jones and an ultralow noise-equivalent-power of 4.2×10^(–20 )W/Hz1/2 for 275 nm light.Its performance exceeds most other UV detectors,even including commercial photomultiplier tubes and avalanche photodiodes.It can be also implemented as an optoelectronic synapse for neuromorphic computing.A 784×300×10 artificial neural network(ANN)based on this optoelectronic synapse is constructed and demonstrated with a high recognition accuracy and good noise-tolerance for the Fashion-MNIST dataset.These extraordinary features endow this phototransistor with the potential for constructing advanced SB-UV detectors and intelligent hardware.

Artificial visual-tactile perception array for enhanced memory and neuromorphic computations

The emulation of human multisensory functions to construct artificial perception systems is an intriguing challenge for developing humanoid robotics and cross-modal human–machine interfaces.Inspired by human multisensory signal generation and neuroplasticity-based signal processing,here,an artificial perceptual neuro array with visual-tactile sensing,processing,learning,and memory is demonstrated.The neuromorphic bimodal perception array compactly combines an artificial photoelectric synapse network and an integrated mechanoluminescent layer,endowing individual and synergistic plastic modulation of optical and mechanical information,including short-term memory,long-term memory,paired pulse facilitation,and“learning-experience”behavior.Sequential or superimposed visual and tactile stimuli inputs can efficiently simulate the associative learning process of“Pavlov's dog”.The fusion of visual and tactile modulation enables enhanced memory of the stimulation image during the learning process.A machine-learning algorithm is coupled with an artificial neural network for pattern recognition,achieving a recognition accuracy of 70%for bimodal training,which is higher than that obtained by unimodal training.In addition,the artificial perceptual neuron has a low energy consumption of~20 pJ.With its mechanical compliance and simple architecture,the neuromorphic bimodal perception array has promising applications in largescale cross-modal interactions and high-throughput intelligent perceptions.

Large-area growth of synaptic heterostructure arrays for integrated neuromorphic visual perception chips

Two-dimensional metal chalcogenides have garnered significant attention as promising candidates for novel neuromorphic synaptic devices due to their exceptional structural and optoelectronic properties.However,achieving large-scale integration and practical applications of synaptic chips has proven to be challenging due to significant hurdles in materials preparation and the absence of effective nanofabrication techniques.In a recent breakthrough,we introduced a revolutionary allopatric defect-modulated Fe_(7)S_(8)@MoS_(2)synaptic heterostructure,which demonstrated remarkable optoelectronic synaptic response capabilities.Building upon this achievement,our current study takes a step further by presenting a sulfurization-seeding synergetic growth strategy,enabling the large-scale and arrayed preparation of Fe_(7)S_(8)@MoS_(2)heterostructures.Moreover,a three-dimensional vertical integration technique was developed for the fabrication of arrayed optoelectronic synaptic chips.Notably,we have successfully simulated the visual persistence function of the human eye with the adoption of the arrayed chip.Our synaptic devices exhibit a remarkable ability to replicate the preprocessing functions of the human visual system,resulting in significantly improved noise reduction and image recognition efficiency.This study might mark an important milestone in advancing the field of optoelectronic synaptic devices,which significantly prompts the development of mature integrated visual perception chips.

Programmable van-der-Waals heterostructure-enabled optoelectronic synaptic floating-gate transistors with ultra-low energy consumption

Van der Waals(vdW)heterostructures provide a unique opportunity to develop various electronic and optoelectronic devices with specific functions by designing novel device structures,especially for bioinspired neuromorphic optoelectronic devices,which require the integration of nonvolatile memory and excellent optical responses.Here,we demonstrate a programmable optoelectronic synaptic floating-gate transistor based on multilayer graphene/h-BN/MoS2 vdW heterostructures,where both plasticity emulation and modulation were successfully realized in a single device.The dynamic tunneling process of photogenerated carriers through the as-fabricated vdW heterostructures contributed to a large memory ratio(105)between program and erase states.Our device can work as a functional or silent synapse by applying a program/erase voltage spike as a modulatory signal to determine the response to light stimulation,leading to a programmable operation in optoelectronic synaptic transistors.Moreover,an ultra-low energy consumption per light spike event(~2.5 fJ)was obtained in the program state owing to a suppressed noise current by program operation in our floating-gate transistor.This study proposes a feasible strategy to improve the functions of optoelectronic synaptic devices with ultra-low energy consumption based on vdW heterostructures designed for highly efficient artificial neural networks.

Visible-light stimulated synaptic plasticity in amorphous indium−gallium−zinc oxide enabled by monocrystalline double perovskite for high-performance neuromorphic applications

Photoelectric synaptic devices have been considered as one of the key components in artificial neuromorphic systems due to their excellent capability to emulate the functions of visual neurons,such as light perception and image processing.Herein,we demonstrate an optically-stimulated artificial synapse with a clear photoresponse from ultraviolet to visible light,which is established on a novel heterostructure consisting of monocrystalline Cs2AgBiBr6 perovskite and indium–gallium–zinc oxide(IGZO)thin film.As compared with pure IGZO,the heterostructure significantly enhances the photoresponse and corresponding synaptic plasticity of the devices,which originate from the superior visible absorption of single-crystal Cs2AgBiBr6 and effective interfacial charge transfer from Cs2AgBiBr6 to IGZO.A variety of synaptic behaviors are realized on the fabricated thin-film transistors,including excitatory postsynaptic current,paired pulse facilitation,short-term,and long-term plasticity.Furthermore,an artificial neural network is simulated based on the photonic potentiation and electrical depression effects of synaptic devices,and an accuracy rate up to 83.8%±1.2%for pattern recognition is achieved.This finding promises a simple and efficient way to construct photoelectric synaptic devices with tunable spectrum for future neuromorphic applications.

Synthesis of wafer-scale graphdiyne/graphene heterostructure for scalable neuromorphic computing and artificial visual systems

Graphdiyne(GDY)is emerging as a promising material for various applications owing to its unique structure and fascinating properties.However,the application of GDY in electronics and optoelectronics are still in its infancy,primarily owing to the huge challenge in the synthesis of large-area and uniform GDY film for scalable applications.Here a modified van der Waals epitaxy strategy is proposed to synthesize wafer-scale GDY film with high uniformity and controllable thickness directly on graphene(Gr)surface,providing an ideal platform to construct large-scale GDY/Gr-based optoelectronic synapse array.Essential synaptic behaviors have been realized,and the linear and symmetric conductance-update characteristics facilitate the implementation of neuromorphic computing for image recognition with high accuracy and strong fault tolerance.Logic functions including“NAND”and“NOR”are integrated into the synapse which can be executed in an optical pathway.Moreover,a visible information sensing-memory-processing system is constructed to execute real-time image acquisition,in situ image memorization and distinction tasks,avoiding the time latency and energy consumption caused by data conversion and transmission in conventional visual systems.These results highlight the potential of GDY in applications of neuromorphic computing and artificial visual systems.