A5100421744- Advanced Memory and Neural Computing
- Ferroelectric and Negative Capacitance Devices
- Neuroscience and Neural Engineering
- Photoreceptor and optogenetics research
- Neural dynamics and brain function
- CCD and CMOS Imaging Sensors
- Neural Networks and Reservoir Computing
- Semiconductor materials and devices
- Transition Metal Oxide Nanomaterials
- Machine Learning and ELM
- Phase-change materials and chalcogenides
- Electronic Packaging and Soldering Technologies
- Smart Grid and Power Systems
- High voltage insulation and dielectric phenomena
- Advanced optical system design
- Gas Sensing Nanomaterials and Sensors
- Photonic and Optical Devices
- Power Transformer Diagnostics and Insulation
- High-Voltage Power Transmission Systems
- Neural Networks and Applications
- Lightning and Electromagnetic Phenomena
- Power Systems and Technologies
- Molecular Junctions and Nanostructures
- Optical Coatings and Gratings
- Advanced Electrical Measurement Techniques
Huazhong University of Science and Technology
2016-2025
Wuhan National Laboratory for Optoelectronics
2015-2025
Institute of Microelectronics
2017-2025
Chinese Academy of Sciences
2022-2025
University of Hong Kong
2024-2025
Zunyi Medical University
2025
State Key Laboratory on Integrated Optoelectronics
2025
Jilin University
2008-2025
Shanghai University
2019-2024
University of Chinese Academy of Sciences
2022-2024
In conventional consumer electronics such as cell phones, lead-containing interconnects provide the conductive path between different circuit elements. Environmental concerns have led to a search for lead-free alternatives. their Perspective, Li et al. review these efforts, which focused on alloys and electrically adhesives. Both of approaches are showing promise, but no one interconnect material can serve substitute tin-lead solder in all devices.
Compact and power-efficient plastic electronic synapses are of fundamental importance to overcoming the bottlenecks developing a neuromorphic chip. Memristor is strong contender among various in existence today. However, speeds synaptic events relatively slow most attempts at emulating due material-related mechanism. Here we revealed intrinsic memristance stoichiometric crystalline Ge2Sb2Te5 that originates from charge trapping releasing by defects. The device resistance states, representing...
Nanoscale inorganic electronic synapses or synaptic devices, which are capable of emulating the functions biological brain neuronal systems, regarded as basic building blocks for beyond-Von Neumann computing architecture, combining information storage and processing. Here, we demonstrate a Ag/AgInSbTe/Ag structure chalcogenide memristor-based synapses. The memristive characteristics with reproducible gradual resistance tuning utilised to mimic activity-dependent plasticity that serves basis...
Abstract Traditional von Neumann computing architecture with separated computation and storage units has already impeded the data processing performance energy efficiency, calling for emerging neuromorphic electronic optical devices systems which can mimic human brain to shift this paradigm. Material‐level innovation become key component revolution of information technology. Chalcogenide phase‐change material (PCM) as a well‐acknowledged data‐storage medium is promising candidate tackle...
Reward-modulated spike-timing-dependent plasticity (R-STDP) is a brain-inspired reinforcement learning (RL) rule, exhibiting potential for decision-making tasks and artificial general intelligence. However, the hardware implementation of reward-modulation process in R-STDP usually requires complicated Si complementary metal-oxide-semiconductor (CMOS) circuit design that causes high power consumption large footprint. Here, with two synaptic transistors (2T) connected parallel structure...
Abstract Recent years have witnessed a surge of interest in learning representations graph-structured data, with applications from social networks to drug discovery. However, graph neural networks, the machine models for handling face significant challenges when running on conventional digital hardware, including slowdown Moore’s law due transistor scaling limits and von Neumann bottleneck incurred by physically separated memory processing units, as well high training cost. Here we present...
Abstract Due to its non‐invasive nature, ultrasound has been widely used for neuromodulation in biological systems, where application influences the synaptic weights and process of neurotransmitter delivery. However, such modulation not emulated physical devices. Memristors are ideal electrical components artificial synapses, but up till now they hardly reported respond signals. Here we design fabricate a HfO x ‐based memristor on 64°Y‐X LiNbO 3 single crystal substrate, successfully realize...
As a promising alternative for next-generation memory, memristors provide several useful features such as high density, nonvolatility, low power, and good scalability compared with conventional CMOS-based memories. In this brief, voltage-controlled threshold memristive model is proposed, which based on experimental data of devices. Moreover, the more suitable design memristor-based synaptic circuits other models. The effects memristance variations are considered in proposed to evaluate...
By exploiting novel transport phenomena such as ion selectivity at the nanoscale, it has been shown that nanochannel systems can exhibit electrically controllable conductance, suggesting their potential use in neuromorphic devices. However, several critical features of biological synapses, particularly conductance modulation, which is both memorable and gradual, have rarely reported these types due to fast flow property typical inorganic electrolytes. In this work, we demonstrate...
Nonvolatile stateful logic through RRAM is a promising route to build in-memory computing architecture. In this letter, methodology based on 1T1R structure has been proposed implement functionally complete Boolean logics. Arbitrary functions could be realized in two steps: initialization and writing. An additional read step required out the result, which situ stored nonvolatile resistive state of memory. Cascade problem building larger circuits also discussed. Our device operation method...
Homeothermic synaptic behaviors with a wide range of temperature were demonstrated in CMOS-compatible HfO<sub>x</sub>/AlO<sub>y</sub> memristors.
The memristor, a promising candidate for synaptic interconnections in artificial neural network, has gained significant attention application to neuromorphic systems. One common method is using two memristors as one synapse represent the positive and negative weights. In this paper, behavior of Ag/AgInSbTe/Ta (AIST)-based memristor experimentally demonstrated. addition, architecture AIST proposed, where both plus minus weights synapses are realized single memristive array. Moreover,...
Alkaline metals doping is one of the approaches for achieving high efficiency Cu(In,Ga)Se2 (CIGS) solar cell. Recently, potassium helps to break record CIGS cell doped with sodium. In this paper, we have investigated how incorporation can influence properties Cu2ZnSnS4 (CZTS) thin film and performance resulting Our results showed that K enhance (112) preferred orientation, increase grain size reduce second phase ZnS CZTS films. After doping, despite some drop Voc cells, Rs decreased Jsc...
Through oxygen profile engineering, we fabricated W/AlO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</sub> /Al xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> O xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> /Pt bilayer memristors with a 250-nm feature size. The AlOX by sputtering serves as an vacancy source, whereas the Al deposited atomic layer deposition acts dominant resistive switching (RS) layer. Our devices show forming-free...
Threshold switching (TS) devices are promising candidates to build highly compact and energy efficient artificial neurons. Here, we present a Pt/Ag/TiN/HfAlO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</sub> /Pt (PATHP) device with excellent TS characteristics, including large selectivity(10 <sup xmlns:xlink="http://www.w3.org/1999/xlink">10</sup> ), wide range of operation current from 10 nA 1 mA, an extremely steep slope (0.63 mV/dec)...
An electro-photo-sensitive synapse based on a highly reliable InGaZnO thin-film transistor is demonstrated to mimic synaptic functions and pattern-recognition functions.
Memristive logic device is a promising unit for beyond von Neumann computing systems and 2D materials are widely used because of their controllable interfacial properties. Most these memristive devices, however, made from semiconducting chalcogenides which fail to gate the off-state current. To this end, crossbar using HfSe2 fabricated, then top layers oxidized into "high-k" dielectric HfSex Oy via oxygen plasma treatment, so that cell resistance can be remarkably increased. This...
Abstract The hardware design of supervised learning (SL) in spiking neural network (SNN) prefers 3-terminal memristive synapses, where the third terminal is used to impose supervise signals. In this work we address demand by fabricating graphene transistor gated through organic ferroelectrics polyvinylidene fluoride. Through gate tuning not only nonvolatile and continuous change channel conductance demonstrated, but also transition between electron-dominated hole-dominated transport. By...
Abstract Memristors are now becoming a prominent candidate to serve as the building blocks of non-von Neumann in-memory computing architectures. By mapping analog numerical matrices into memristor crossbar arrays, efficient multiply accumulate operations can be performed in massively parallel fashion using physics mechanisms Ohm’s law and Kirchhoff’s law. In this brief review, we present recent progress two niche applications: neural network accelerators units, mainly focusing on advances...
Abstract The fully memristive neural network consisting of the threshold switching (TS) material‐based electronic neurons and resistive (RS) one‐based synapses shows potential for revolutionizing energy area efficiency in neuromorphic computing while being confronted with challenges such as reliability process compatibility between synaptic neuronal devices. Here, a spiking convolutional (SCNN) is constructed forming‐and‐annealing‐free V/VO x /HfWO /Pt Specifically, both highly reliable RS...
In this report, we present a photoredox/cobalt dual catalytic system for the synthesis of distally unsaturated ketones. Upon cooperative utilization an organo photoredox catalyst and cobaloxime catalyst, sequential ring-opening C–C bond scission dehydrogenation nonstrained tertiary cycloalkanols variable ring sizes are achieved under visible-light irradiation, producing wide range γ,δ-, δ,ε-, even more ketones in good yields, with hydrogen gas as sole byproduct. The produced versatile...
Memristor-enabled in-memory computing provides an unconventional paradigm to surpass the energy efficiency of von Neumann computers. Owing limitation mechanism, while crossbar structure is desirable for dense computation, system's and area degrade substantially in performing sparse computation tasks, such as scientific computing. In this work, we report a high-efficiency system based on self-rectifying memristor array. This originates from analog mechanism that motivated by device's nature,...