A5100401317- Advanced Memory and Neural Computing
- Ferroelectric and Negative Capacitance Devices
- Semiconductor materials and devices
- Advancements in PLL and VCO Technologies
- Neuroscience and Neural Engineering
- CCD and CMOS Imaging Sensors
- Radio Frequency Integrated Circuit Design
- Transition Metal Oxide Nanomaterials
- Physical Unclonable Functions (PUFs) and Hardware Security
- VLSI and Analog Circuit Testing
- Analog and Mixed-Signal Circuit Design
- Integrated Circuits and Semiconductor Failure Analysis
- Embedded Systems Design Techniques
- Advanced Algorithms and Applications
- Semiconductor Lasers and Optical Devices
- Advancements in Semiconductor Devices and Circuit Design
- Parallel Computing and Optimization Techniques
- Optical measurement and interference techniques
- Optical Systems and Laser Technology
- Wireless Sensor Networks and IoT
- Energy Harvesting in Wireless Networks
- Low-power high-performance VLSI design
- Electromagnetic Compatibility and Noise Suppression
- Smart Grid and Power Systems
- Advanced Measurement and Metrology Techniques
Chinese Academy of Sciences
2016-2025
Institute of Microelectronics
2015-2025
Aerospace Information Research Institute
2025
Soochow University
2025
Computer Network Information Center
2024
University of Chinese Academy of Sciences
2004-2024
University of Science and Technology of China
2016-2024
Peng Cheng Laboratory
2023
Xiamen University of Technology
2023
First Affiliated Hospital of Jinan University
2023
A SWCNT/TiO2 nanocomposite ultrathin film that has superhydrophilic and underwater superoleophobic properties after UV-light irradiation is successfully prepared by coating TiO2 via the sol–gel process onto an SWCNT network film. The robust flexible films with a thickness pore size of tens nanometers can separate both surfactant-free surfactant-stabilized oil-in-water emulsions in ultrafast manner fluxes up to 30 000 L m–2 h–1 bar–1, which 2 orders magnitude higher than commercial filtration...
Artificial neurons and synapses are critical units for processing intricate information in neuromorphic systems. Memristors frequently engineered as artificial due to their simple structures, gradually changing conductance high-density integration. However, few studies have designed memristors neurons. In this letter, we demonstrate an integration-and-fire neuron based on a Ag/SiO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> /Au...
Abstract Non-volatile computing-in-memory macros that are based on two-dimensional arrays of memristors use in the development artificial intelligence edge devices. Scaling such systems to three-dimensional could provide higher parallelism, capacity and density for necessary vector–matrix multiplication operations. However, scaling three dimensions is challenging due manufacturing device variability issues. Here we report a two-kilobit non-volatile macro vertical resistive random-access...
Computing-in-memory (CIM) has shown high energy efficiency on low-precision integer multiply-accumulate (MAC) [1–3]. However, implementing floating-point (FP) operations using CIM not been thoroughly explored. Previous FP chips [4–5] require either complex in-memory logic or have lengthy alignment-cycle latencies arising from converting data having different exponents into data. The challenges for an energy-efficient and accurate processor are in Fig. 16.3.1. Firstly, aligning vector onto a...
Two-dimensional van der Waals (2D vdW) ferromagnets possess outstanding scalability, controllable ferromagnetism, and out-of-plane anisotropy, enabling the compact spintronics-based non-volatile in-memory computing (nv-IMC) that promises to tackle memory wall bottleneck issue. Here, by employing intriguing room-temperature ferromagnetic characteristics of emerging 2D Fe3GeTe2 with dissimilar electronic structure two spin-conducting channels, we report on a new type spin-orbit torque (SOT)...
Resistive memory (RRAM) provides an ideal platform to develop embedded non-volatile computing-in-memory (nvCIM). However, it faces several critical challenges ranging from device non-idealities, large DC currents, and small signal margins. To address these issues, we propose voltage-division (VD) based computing approach its circuit implementation in two-transistor-two-resistor (2T2R) RRAM cell arrays, which can realize energy-efficient, sign-aware, robust deep neural network (DNN)...
Traditional LC resonance circuit can continuously and efficiently accumulate energy from the harvester at optimal impedance matching. Due to electric-field frequency (50 Hz, in China) small equivalent capacitance (tens or hundreds of picofarads) capacitive harvester, it is difficult manufacture a huge transformer with large inductance (>10 000 H) optimally match harvester. An upconversion oscillation smaller size around high-voltage power line proposed achieve efficient harvesting this...
Electrocardiogram (ECG) heartbeat classification plays a vital role in early diagnosis and effective treatment, which provide opportunities for earlier prevention intervention. In an effort to continuously monitor detect abnormalities patients’ ECG signals on portable devices, this paper present lightweight method based spiking neural network (SNN), relatively shallow SNN model integrated with channel-wise attentional module. We further explore the best-optimized architecture, benefits from...
Non-volatile computing-in-memory (nvCIM) can potentially meet the ever-increasing demands on improving energy efficiency (EF) for intelligent edge devices. However, it still suffers from limited input parallelism due to parasitic effects, signal margin degradation device non-idealities, and large hardware cost analog readout. In this work, we present a two-transistor-one-resistor (2T1R) resistive memory (RRAM) nvCIM macro featuring: 1) structure with decoupled computing data paths; 2)...
Abstract Spinal cord injury (SCI) is a severe neurological condition that frequently leads to significant sensory, motor, and autonomic dysfunction. This study sought delineate the potential mechanistic underpinnings of extracellular vesicles (EVs) derived from ginsenoside Rg1‐pretreated neuronal cells (Rg1‐EVs) in ameliorating SCI. These results demonstrated treatment with Rg1‐EVs substantially improved motor function spinal cord‐injured mice. enhance microglial polarization toward M2...
Dendrobium nobile Lindl. alkaloids (DNLA), the active ingredients of a traditional Chinese medicine Dendrobium, have been shown to anti-oxidative effects, anti-inflammatory action, and protective effect on neurons against oxygen-glucose deprivation. However, it is not clear whether DNLA reduces amyloid-beta (Aβ)-induced neuronal injury. In this study, cortical were treated with at different concentrations (0.025, 0.25, 2.5 mg/L) for 24 hours, followed by administration Aβ25-35 (10 μM)....
This article presents a comprehensive assessment on the 6T static random access memory (SRAM) cell with 7-nm FinFET technology by implementing quantum physics-based device-circuit cooptimization. Seven key device design parameters and their multiple impacts SRAM are systematically evaluated, focusing materials band engineering, design, circuit tradeoff, variation control. The area of under same Fin quantization scheme remains constant in all evaluations. To best our knowledge, most...
In this paper, we present a fully reconfigurable resistive random access memory (RRAM) physical unclonable function (PUF) based on the truly dynamic entropy of ubiquitous jitter noise, which is intrinsically different from most previously demonstrated PUF implementations with semiconductor fabrication's process variation as static source. addition, proposed RRAM operated by configuring mainstream cells to either high resistance state (for `1') or low `0'), according customized ring...
In this brief, an ultracompact and highly reliable physical unclonable function (PUF) is presented based on the mainstream resistive random access memory (RRAM) devices. With entropy originating from switching voltage between high-resistance state (HRS) low-resistance (LRS), proposed RRAM PUF can be generated during RRAM's standard SET operation, leading to minimized design overhead. addition, different previous implementations where adopted cells are dedicated "PUF" function, fully...
Abstract Background Cancer-associated fibroblasts (CAFs) are essential stromal components in the tumor microenvironment of hepatocellular carcinoma (HCC). Hepatitis B virus (HBV) infection induces pathological changes such as liver fibrosis/cirrhosis and HCC. The aim this research was to explore novel mediators CAFs modulate HBV cirrhosis-HCC progression. Methods single-cell transcriptome data HCC were divided into subsets, significant subset related fibrotic cells, along with biological...
This study presents the first report on fundamental dosimetric characterization of a novel image-guided radiosurgery system &ndash; ZND-A Smart Knife (CNCI Co., Ltd, Xi&rsquo;an, China). The performance this was evaluated based key parameters, including positioning reference point deviation, nominal focal dose rate, focusing field size, gradient, and comprehensive error in calculation. employs &ldquo;triple rotating focusing&rdquo; technique, its characteristics were...