A5100395778- Advanced Memory and Neural Computing
- Ferroelectric and Negative Capacitance Devices
- Photoreceptor and optogenetics research
- Neural dynamics and brain function
- Neuroscience and Neural Engineering
- Semiconductor materials and devices
- CCD and CMOS Imaging Sensors
- Electrocatalysts for Energy Conversion
- Photonic and Optical Devices
- Low-power high-performance VLSI design
- Advanced Fiber Optic Sensors
- Advancements in Battery Materials
- Conducting polymers and applications
- Power Systems and Renewable Energy
- Neural Networks and Reservoir Computing
- Advanced Battery Technologies Research
- Integrated Energy Systems Optimization
- Psychosomatic Disorders and Their Treatments
- Metal Extraction and Bioleaching
- Human Mobility and Location-Based Analysis
- Urban Transport and Accessibility
- Advancements in Semiconductor Devices and Circuit Design
- Wireless Communication Security Techniques
- CO2 Reduction Techniques and Catalysts
- Perovskite Materials and Applications
University of Electronic Science and Technology of China
2015-2024
National Engineering Research Center of Electromagnetic Radiation Control Materials
2015-2024
State Key Laboratory of Electronic Thin Films and Integrated Devices
2024
New Jersey Institute of Technology
2024
University of Hong Kong
2024
China National Nuclear Corporation
2024
Shenzhen University
2018-2023
Central South University
2013-2023
Chang'an University
2023
Zhengzhou University
2022-2023
Although synaptic behaviours of memristors have been widely demonstrated, implementation an even simple artificial neural network is still a great challenge. In this work, we demonstrate the associative memory on basis memristive Hopfield network. Different patterns can be stored into by tuning resistance memristors, and pre-stored successfully retrieved directly or through some intermediate states, being analogous to behaviour. Both single-associative multi-associative memories realized...
Abstract Phototunable biomaterial‐based resistive memory devices and understanding of their underlying switching mechanisms may pave a way toward new paradigm smart green electronics. Here, behavior photonic biomemory based on novel structure metal anode/carbon dots (CDs)‐silk protein/indium tin oxide is systematically investigated, with Al, Au, Ag anodes as case studies. The charge trapping/detrapping filaments formation/rupture are observed by in situ Kelvin probe force microscopy...
Abstract Get in-depth understanding of each part visual pathway yields insights to conquer the challenges that classic computer vision is facing. Here, we first report bioinspired striate cortex with binocular and orientation selective receptive field based on crossbar array self-powered memristors which solution-processed monolithic all-perovskite system cross-point containing one CsFAPbI 3 solar cell directly stacking CsPbBr 2 I memristor. The plasticity memristor can be modulated by...
The oxygen reduction reaction (ORR) electrocatalytic activity of Pt-based catalysts can be significantly improved by supporting Pt and its alloy nanoparticles (NPs) on a porous carbon support with large surface area. However, such are often obtained constructing followed depositing NPs inside the pores, in which migration agglomeration inevitable under harsh operating conditions owing to relatively weak interaction between support. Here we develop facile electrospinning strategy in-situ...
Reservoir computing (RC) is a computational architecture capable of efficiently processing temporal information, which allows low-cost hardware implementation. However, the previously reported memristor-based RC mostly utilized binarized data sets to reduce difficulty signal memristor, inevitably induces distortion certain extent, leading poor network performance. Here, we report on system in fully memristive based solution-processed perovskite memristors. The memristor exhibits 10000...
Abstract The essential step for developing neuromorphic systems is to construct more biorealistic elementary devices with rich spatiotemporal dynamics exhibit highly separable responses in dynamic environmental circumstances. Unlike transistor‐based and circuits zeroth‐order complexity, memristors intrinsically express some simple biomimetic functions. However, only two‐terminal structure, precise control of operation principles ensure large space, improved linearity symmetry, multimodal as...
Abstract The threshold switching (TS) phenomenon in memristors has drawn great attention for its versatile applications selectors, artificial neurons, true random number generators, and electronic integrations. transition between nonvolatile resistive volatile TS modes can be realized by doping, varying annealing voltage sweeping conditions, or imposing different compliance current. Here, a strategy is reported to achieve such the noninvasive UV light stimulus based on InP/ZnS quantum dot...
Abstract Current organic memristive devices have been suffering from unstable performance, ambiguous mechanism, and poor NIR response, thus restricting their commercial translation. Here, a near‐infrared‐sensitive (NIR) device with high stability based on solution‐processed copper phthalocyanine nanowires (N‐CuMe 2 Pc NWs) is first reported. Compared uneven thermal evaporated N‐CuMe film, the NWs film possesses uniform 3D mesh structure, which attribute to localized cationic migration,...
The prepared SA-Fe-3DOMC catalyst with rich pore structure and densely accessible Fe–N 4 active was demonstrated to boost ORR catalytic performance peak power density for Zn–air batteries.
A resonator integrated optic gyro (RIOG) employing trapezoidal phase modulation (TZPM) technique is proposed, analyzed, and demonstrated for the first time. This can provide more information about whole system without complicating light circuit structure, making it possible to compensate output in real The experimental results of RIOG prototype show that standard deviation greatly reduced after compensation, which proves viability effectiveness TZPM technique. bias stability 0.09 deg/s with...
Synaptic memristor has attracted much attention for its potential applications in artificial neural networks (ANNs). However useful real life with such memristor-based have seldom been reported. In this paper, an ANN based on memristors is designed to learn a multi-variable regression model back-propagation algorithm. A weight unit circuit memristor, which can be programed as excitatory synapse or inhibitory synapse, introduced. The of the electronic determined by conductance and current...
Although there is a huge progress in complementary-metal-oxide-semiconductor (CMOS) technology, construction of an artificial neural network using CMOS technology to realize the functionality comparable with that human cerebral cortex containing 10
Dual direction current modulation has been enabled in an asymmetric electrode configuration, which mediated by optoelectronic signals to emulate the important synaptic plasticity.
In this article, we present a spiking neural network (SNN) based on both SRAM processing-in-memory (PIM) macro and on-chip unsupervised learning with Spike-Time-Dependent Plasticity (STDP). Co-design of algorithm hardware for hardware-friendly SNN efficient STDP-based methodology is used to improve area energy efficiency. The proposed utilizes charge sharing capacitors perform fully parallel Reconfigurable Multi-bit PIM Multiply-Accumulate (RMPMA) operations. A thermometer-coded Programmable...
A method to suppress backreflection noise due facet reflection in a resonator integrated optic gyro (RIOG) is demonstrated using hybrid phase-modulation technology (HPMT). First, calculations are carried out evaluate the effect of backreflection. Although its amplitude has been remarkably decreased by angle polishing, residual still severe factor RIOGs. Next, eliminate constructed, and frequency spectra photodetector outputs before after adopting HPMT analyzed. Theoretical analysis shows...
Based on large-scale human mobility data collected in San Francisco and Boston, the morning peak urban rail transit (URT) ODs (origin-destination matrix) were estimated most vulnerable URT segments, those capable of causing largest service interruptions, identified. In both networks, a few highly segments observed. For this small group vital impact failure must be carefully evaluated. A bipartite usage network was developed used to determine inherent connections between transits their...
By virtue of energy efficiency, high speed, and parallelism, brain‐inspired neuromorphic computing is a promising technology to overcome the von Neumann bottleneck capable processing massive sophisticated tasks in background big data. The abilities perceiving reacting events artificial systems allow us build communicative electronic–biological interfaces get closer electronic life. Protein materials offer great application potentials such system due their sustainability, low cost,...
The key to the study of flexible neuromorphic computing is excellent weight update characteristic devices. Electric-double-layer transistors (EDLTs) include high transconductance, stability threshold voltage, linear updates, and repetitive ion-concentration-dependent switching properties. However, up now, there no report on a EDLT that provides all aforementioned performance characteristics. Here, planar floating-gate including an linear/symmetric update, large number (>800) conductance...