Piezotronic neuromorphic devices:principle,manufacture,and applications

With the arrival of the era of artificial intelligence(AI)and big data,the explosive growth of data has raised higher demands on computer hardware and systems.Neuromorphic techniques inspired by biological nervous systems are expected to be one of the approaches to breaking the von Neumann bottleneck.Piezotronic neuromorphic devices modulate electrical transport characteristics by piezopotential and directly associate external mechanical motion with electrical output signals in an active manner,with the capability to sense/store/process information of external stimuli.In this review,we have presented the piezotronic neuromorphic devices(which are classified into strain-gated piezotronic transistors and piezoelectric nanogenerator-gated field effect transistors based on device structure)and discussed their operating mechanisms and related manufacture techniques.Secondly,we summarized the research progress of piezotronic neuromorphic devices in recent years and provided a detailed discussion on multifunctional applications,including bionic sensing,information storage,logic computing,and electrical/optical artificial synapses.Finally,in the context of future development,challenges,and perspectives,we have discussed how to modulate novel neuromorphic devices with piezotronic effects more effectively.It is believed that the piezotronic neuromorphic devices have great potential for the next generation of interactive sensation/memory/computation to facilitate the development of the Internet of Things,AI,biomedical engineering,etc.

CMOS-compatible neuromorphic devices for neuromorphic perception and computing: a review

Neuromorphic computing is a brain-inspired computing paradigm that aims to construct efficient,low-power,and adaptive computing systems by emulating the information processing mechanisms of biological neural systems.At the core of neuromorphic computing are neuromorphic devices that mimic the functions and dynamics of neurons and synapses,enabling the hardware implementation of artificial neural networks.Various types of neuromorphic devices have been proposed based on different physical mechanisms such as resistive switching devices and electric-double-layer transistors.These devices have demonstrated a range of neuromorphic functions such as multistate storage,spike-timing-dependent plasticity,dynamic filtering,etc.To achieve high performance neuromorphic computing systems,it is essential to fabricate neuromorphic devices compatible with the complementary metal oxide semiconductor(CMOS)manufacturing process.This improves the device’s reliability and stability and is favorable for achieving neuromorphic chips with higher integration density and low power consumption.This review summarizes CMOS-compatible neuromorphic devices and discusses their emulation of synaptic and neuronal functions as well as their applications in neuromorphic perception and computing.We highlight challenges and opportunities for further development of CMOS-compatible neuromorphic devices and systems.

Recent progress in optoelectronic neuromorphic devices

Rapid developments in artificial intelligence trigger demands for perception and learning of external environments through visual perception systems.Neuromorphic devices and integrated system with photosensing and response functions can be constructed to mimic complex biological visual sensing behaviors.Here,recent progresses on optoelectronic neuromorphic memristors and optoelectronic neuromorphic transistors are briefly reviewed.A variety of visual synaptic functions stimulated on optoelectronic neuromorphic devices are discussed,including light-triggered short-term plasticities,long-term plasticities,and neural facilitation.These optoelectronic neuromorphic devices can also mimic human visual perception,information processing,and cognition.The optoelectronic neuromorphic devices that simulate biological visual perception functions will have potential application prospects in areas such as bionic neurological optoelectronic systems and intelligent robots.

Temperature-controlled multisensory neuromorphic devices for artificial visual dynamic capture enhancement

Multi-sensory neuromorphic devices(MND)have broad potential in overcoming the structural bottleneck of von Neumann in the era of big data.However,the current multisensory artificial neuromorphic system is mainly based on unitary nonvolatile memory or volatile synaptic devices without intrinsic thermal sensitivity,which limits the range of biological multisensory perception and the flexibility and computational efficiency of the neural morphological computing system.Here,a temperature-dependent memory/synaptic hybrid artificial neuromorphic device based on floating gate phototransistors(FGT)is fabricated.The CsPbBr_(3)/TiO_(2)core–shell nanocrystals(NCs)prepared by in-situ pre-protection low-temperature solvothermal method were used as the photosensitive layer.The device exhibits remarkable multi-level visual memory with a large memory window of 59.6 V at room temperature.Surprisingly,when the temperature varies from 20 to 120℃back and forth,the device can switch between nonvolatile memory and volatile synaptic device with reconfigurable and reversible behaviors,which contributes to the efficient visual/thermal fusion perception.This work expands the sensory range of multisensory devices and promotes the development of memory and neuromorphic devices based on organic field-effect transistors(OFET).

Neuromorphic circuits based on memristors: endowing robots with a human-like brain

Robots are widely used,providing significant convenience in daily life and production.With the rapid development of artificial intelligence and neuromorphic computing in recent years,the realization of more intelligent robots through a pro-found intersection of neuroscience and robotics has received much attention.Neuromorphic circuits based on memristors used to construct hardware neural networks have proved to be a promising solution of shattering traditional control limita-tions in the field of robot control,showcasing characteristics that enhance robot intelligence,speed,and energy efficiency.Start-ing with introducing the working mechanism of memristors and peripheral circuit design,this review gives a comprehensive analysis on the biomimetic information processing and biomimetic driving operations achieved through the utilization of neuro-morphic circuits in brain-like control.Four hardware neural network approaches,including digital-analog hybrid circuit design,novel device structure design,multi-regulation mechanism,and crossbar array,are summarized,which can well simulate the motor decision-making mechanism,multi-information integration and parallel control of brain at the hardware level.It will be definitely conductive to promote the application of memristor-based neuromorphic circuits in areas such as intelligent robotics,artificial intelligence,and neural computing.Finally,a conclusion and future prospects are discussed.

Advances in the Application of Perovskite Materials

Nowadays, the soar of photovoltaic performance of perovskite solar cells has set off a fever in the study of metal halide perovskite materials. The excellent optoelectronic properties and defect tolerance feature allow metal halide perovskite to be employed in a wide variety of applications. This article provides a holistic review over the current progress and future prospects of metal halide perovskite materials in representative promising applications, including traditional optoelectronic devices(solar cells, light-emitting diodes, photodetectors, lasers), and cutting-edge technologies in terms of neuromorphic devices(artificial synapses and memristors) and pressure-induced emission. This review highlights the fundamentals, the current progress and the remaining challenges for each application, aiming to provide a comprehensive overview of the development status and a navigation of future research for metal halide perovskite materials and devices.

Multi-terminal pectin/chitosan hybrid electrolyte gated oxide neuromorphic transistor with multi-mode cognitive activities

In order to fulfill the urgent requirements of functional products,circuit integration of different functional devices are commonly utilized.Thus,issues including production cycle,cost,and circuit crosstalk will get serious.Neuromorphic computing aims to break through the bottle neck of von Neumann architectures.Electronic devices with multi-operation modes,especially neuromorphic devices with multi-mode cognitive activities,would provide interesting solutions.Here,pectin/chitosan hybrid electrolyte gated oxide neuromorphic transistor was fabricated.With extremely strong proton related interfacial electric-double-layer coupling,the device can operate at low voltage of below 1 V.The device can also operate at multi-operation mode,including bottom gate mode,coplanar gate and pseudo-diode mode.Interestingly,the artificial synapse can work at low voltage of only 1 mV,exhibiting extremely low energy consumption of~7.8 fJ,good signal-to-noise ratio of~229.6 and sensitivity of~23.6 dB.Both inhibitory and excitatory synaptic responses were mimicked on the pseudo-diode,demonstrating spike rate dependent plasticity activities.Remarkably,a linear classifier is proposed on the oxide neuromorphic transistor under synaptic metaplasticity mechanism.These results suggest great potentials of the oxide neuromorphic devices with multi-mode cognitive activities in neuromorphic platform.

Carbon-based memristors for resistive random access memory and neuromorphic applications

As a typical representative of nanomaterials,carbon nanomaterials have attracted widespread attention in the construction of electronic devices owing to their unique physical and chemical properties,multi-dimensionality,multi-hybridization methods,and excellent electronic properties.Especially in the recent years,memristors based on carbon nanomaterials have flourished in the field of building non-volatile memory devices and neuromorphic applications.In the current work,the preparation methods and structural characteristics of carbon nanomaterials of different dimensions were systematically reviewed.Afterwards,in depth discussion on the structural characteristics and working mechanism of memristors based on carbon nanomaterials of different dimensions was conducted.Finally,the potential applications of carbon-based memristors in logic operations,neural network construction,artificial vision systems,artificial tactile systems,and multimodal perception systems were also introduced.It is believed that this paper will provide guidance for the future development of high-quality information storage,high-performance neuromorphic applications,and highsensitivity bionic sensing based on carbon-based memristors.

人工道德基础器件:模拟道德逻辑的晶体管

日益先进的人工智能在生活中的广泛应用,促进了人工道德问题的产生.机器人的人工伦理的建立和实施通常是通过被动程序指令解决的,而在硬件层面的主动实现仍然具有挑战性.在这里,受认知心理学和神经生理学的启发,我们展示了一种典型的人工道德器件.通过判断善恶和解决道德困境,器件实现了机器人三定律中的第一定律.器件展示了自我、本我和超我三种状态,以及绝对命令、本能漠视、本能冲动、道德义务论、功利主义和利己主义等六种人性.道德的起源在电子学方面得到了揭示,这是潜意识和意识之间的对抗性协作.这项工作为未来人工智能的意识产生和道德形成提供了一条可行的道路.

基于零维碳量子点/二维MoS2混合维异质结晶体管的视觉失忆脉冲光电治疗模拟

失忆症是一种临床常见的疾病,表现为近期记忆的丧失以及获得新记忆能力的全面受损,它严重影响了人类的正常生活.目前,虽然草药干预、蛋白质合成抑制和激素替代可以预防或逆转失忆行为,但这些疗法都相对昂贵且效率低下.本文利用一种先进的光电协同脉冲疗法,基于零维碳量子点/二维MoS_(2)混合维异质结晶体管对视觉失忆行为治疗进行了模拟.其中,光电脉冲可以诱导足够多的电子来填充陷阱态并聚集于零维/二维混合维界面.同时,该异质结晶体管成功实现了生物中可重构的记忆/失忆行为和可调节的视觉记忆巩固功能.更为重要的是,通过实验还证明了光电协同脉冲修复可能对视觉失忆进行有效治疗.这项工作为医学记忆诊断系统、人机实时交互等领域的发展提供了一个新契机.

Flexible multiterminal photoelectronic neurotransistors based on self‐assembled rubber semiconductors for spatiotemporal information processing

A significant step toward constructing high‐efficiency neuromorphic systems is the electronic emulation of advanced synaptic functions of the human brain.While previous studies have focused on mimicking the basic functions of synapses using single‐gate transistors,multigate transistors offer an opportunity to simulate more complex and advanced memory‐forming behaviors in biological synapses.In this study,a simple and general method is used to assemble rubber semiconductors into suspended two‐phase composite films that are transferred to the surface of the ion‐conducting membrane to fabricate flexible multiterminal photoelectronic neurotransistors.The suspended ion conductive film is used as the gate dielectrics and supporting substrate.The prepared devices exhibit excellent electrical stability and mechanical flexibility after being bent.Basic photoelectronic synaptic behavior and pulse‐dependent plasticity are emulated.Furthermore,the device realizes the spatiotemporally integrated electrical and optical stimuli to mimic spatiotemporal information processing.This study provides a promising direction for constructing more complex spiking neural networks and more powerful neuromorphic systems with brain‐like dynamic spatiotemporal processing functions.