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| 1 | Darwin:a neuromorphic hardware co-processor based on Spiking Neural Networks显示文摘Broadly speaking, the goal of neuromorphic engineering is to build computer systems that mimic the brain. Spiking Neural Network(SNN) is a type of biologically-inspired neural networks that perform information processing based on discrete-time spikes, different from traditional Artificial Neural Network(ANN).Hardware implementation of SNNs is necessary for achieving high-performance and low-power. We present the Darwin Neural Processing Unit(NPU), a neuromorphic hardware co-processor based on SNN implemented with digitallogic, supporting a maximum of 2048 neurons, 20482= 4194304 synapses, and 15 possible synaptic delays.The Darwin NPU was fabricated by standard 180 nm CMOS technology with an area size of 5 × 5 mm2and70 MHz clock frequency at the worst case. It consumes 0.84 m W/MHz with 1.8 V power supply for typical applications. Two prototype applications are used to demonstrate the performance and efficiency of the hardware implementation. | Juncheng SHEN De MA Zonghua GU Ming ZHANG Xiaolei ZHU Xiaoqiang XU Qi XU Yangjing SHEN Gang PAN | 2016 | Science China(Information Sciences)2016，59，2： | 18 |
| 2 | A Survey of Neuromorphic Computing Based on Spiking Neural Networks显示文摘Neuromorphic computing aims to build digital or analog computer systems that emulate or simulate the biological brain, in order to achieve high performance and low power consumption for intelligent information processing applications. This article reviews on neuromorphic computing based on Spiking neural networks(SNNs), including its history of development, common neuron models, major research projects, neuromorphic sensors, and applications in brain-computer Interfaces. | ZHANG Ming GU Zonghua PAN Gang | 2018 | Chinese Journal of Electronics2018，27，4： | 2 |
| 3 | ROP/RAC GTPase:an old new master regulator for plant signaling显示文摘 | Ying Gu Zonghua Wang Zhenbiao Yang | 2004 | Current Opinion in Plant Biology2004，7，： | 1 |
| 4 | ROP/RAC GTPase:an old new master regulator for plant signaling显示文摘 | YING GU ZONGHUA WANG ZHENBIAO YANG | 2004 | Current Opinion in Plant Biology2004，7，： | 1 |
| 5 | Online optimization for scheduling preemptable tasks on IaaS cloud systems显示文摘 | Jiayin Li Meikang Qiu Zhong Ming Gang Quan Xiao Qin Zonghua Gu | 2012 | Journal of Parallel and Distributed Computing2012，，5： | 1 |
| 6 | An Efficient Algorithm for Online Soft Real-Time Task Placement on Reeonfigurable Hardware Devices 显示文摘 | Jin Cui Zonghua Gu | 2007 | Object and Component-Oriented Real-Time Distributed Computing2007，7，10： | 1 |
| 7 | Elucidating the electronic metal-support interaction enhanced hydrogen evolution activity on Ti_(3)C_(2)T_(x)MXene basal plane by scanning electrochemical microscopy显示文摘MXene,a family of two-dimensional(2D)transition metal carbides and nitrides,has intriguing electrochemical energy storage and electrocatalysis applications.Introducing the electronic metal-support interaction(EMSI)effect is one effective strategy to optimize the catalytic efficiency for MXene-based composites.However,most of the studies concentrate on optimizing the performance of metals rather than supported substrates by using this strategy.In this work,we mainly investigate the influence of an EMSI effect on the performance of the supported substrate(Ti_(3)C_(2)T_(x)MXene).Detailed scanning electrochemical microscopy and numerical simulations results reveal that the charge distribution on the Ti_(3)C_(2)T_(x)basal plane(approximate 100 nm-radius)surrounding Au nanoparticles(20 nm-radius)was significantly enhanced as a result of-O being the majority surface functional group on Ti_(3)C_(2)T_(x)that was attached to Au nanoparticle,and the related hydrogen evolution reaction(HER)activity was much better than that of the unaffected Ti_(3)C_(2)T_(x)basal plane,which even can be comparable to that of Au.This finding will be helpful for designing new strategies to enhance the overall catalytic performance of various MXene-based composites. | Sisi Jiang Tong Sun Chaoqun Gu Yingfei Ma Zhenyu Wang Dengchao Wang Zonghua Wang | 2023 | Nano Research2023，16，7： | 0 |
| 8 | Fast Scan mode of scanning electrochemical microscopy:In-situ characterization of phase transition and mapping the hydrogen evolution activity for MoS_(2)显示文摘Scanning electrochemical microscopy(SECM)is an attractive technology to in-situ characterize the structural evolution and catalytic performance for various electrocatalysts.However,spatial and temporal resolution coupling are still the obstacles that limit its wide applications.Herein,a new operation mode,Fast Scan mode,was developed by improving the dual-pass scan mode,designing novel hardware structure,and employing thermal drift calibration software to achieve a high spatial and temporal resolution simultaneously.The temporal speed can achieve 4 Hz for a high spatial resolution(less than 30 nm)image.This operation mode was employed to dynamically track the phase transition process of molybdenum disulfide(MoS_(2))over time and characterize the hydrogen evolution reaction(HER)catalytic activity on the edge of semiconducting MoS_(2)quantitatively while minimizing the diffusional broadening effect and total amount of catalytic products generated above the surface.This new approach should be useful for in-situ tracking dynamic electrochemical processes,establishing the structure-activity relationship for structural complex electrocatalysts,and offering a strategy for high-speed scanning with other electrochemical imaging techniques. | Zhenyu Wang Tong Sun Changan HuangFu Sisi Jiang Chaoqun Gu Liying Jiao Zonghua Wang | 2023 | Nano Research2023，16，7： | 0 |
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