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| 1 | Constraining the stepwise migration of the eastern Tibetan Plateau margin by apatite fission track thermochronology显示文摘Granites sampled from Garzê-Litang thrust, Longmen Shan thrust, Garzê and Litang strike-slip faults in the eastern Tibetan Plateau have been analyzed with apatite fission track thermochronological method in this study. The measured fission track apparent ages, combined with the simulated annealing mod- eling of the thermal history, have been used to reconstruct the thermal evolutionary histories of the samples and interpret the active history of the thrusts and faults in these areas. Thermal history mod- eling shows that earlier tectonic cooling occurred in the Garzê-Litang thrust in Miocene (~20―16 Ma) whereas the later cooling occurred mainly in the Longmen Shan thrust since ~5 Ma. Our study sug- gests that the margin of eastern Tibetan Plateau was extended by stages: through strike-slip faults deformations and related thrusts, the upper crust formed the Garzê-Litang margin in the Miocene epoch and then moved to the Longmen Shan margin since ~5 Ma. During this process, the deformations of different phases in the eastern Tibetan Plateau were absorbed by the thrusts within them and conse- quently the tectonic events of long-distance slip and extrusion up to hundreds of kilometers have not been found. | LAI QingZhou DING Lin WANG HongWei YUE YaHui CAI FuLong | 2007 | Science China Earth Sciences2007，50，2： | 24 |
| 2 | A review:Photonics devices,architectures,and algorithms for optical neural computing显示文摘The explosive growth of data and information has motivated various emerging non-von Neumann computational approaches in the More-than-Moore era.Photonics neuromorphic computing has attracted lots of attention due to the fascinating advantages such as high speed,wide bandwidth,and massive parallelism.Here,we offer a review on the optical neural computing in our research groups at the device and system levels.The photonics neuron and photonics synapse plasticity are presented.In addition,we introduce several optical neural computing architectures and algorithms including photonic spiking neural network,photonic convolutional neural network,photonic matrix computation,photonic reservoir computing,and photonic reinforcement learning.Finally,we summarize the major challenges faced by photonic neuromorphic computing,and propose promising solutions and perspectives. | Shuiying Xiang Yanan Han Ziwei Song Xingxing Guo Yahui Zhang Zhenxing Ren Suhong Wang Yuanting Ma Weiwen Zou Bowen Ma Shaofu Xu Jianji Dong Hailong Zhou Quansheng Ren Tao Deng Yan Liu Genquan Han Yue Hao | 2021 | Journal of Semiconductors2021，42，2： | 7 |
| 3 | Characterization of individual fly ash particles in surface snow at Urumqi Glacier No. 1, Eastern Tianshan显示文摘This research aimed to identify and characterize individual spherical fly ash particles extracted from surface snow at Urumqi Glacier No.1 (UG1), Eastern Tien Shan, central Asia. Characterization of the spherical particles (i.e. morphology, chemical composition and genesis) was obtained by scanning electron microscopy coupled with energy dispersive X-ray spectrometer (SEM-EDX). This method enabled the characterization of submicroscopic spherical particles, which were present in very small quantities. Spherical particles and agglomerates were identified according to their morphology in five snow samples. Prevalent particle types in all samples were granular spherical particles, hollow spherical particles, irregularly shaped carbonaceous particles and agglomerates. The vast majority of spherical particles in our samples had mostly smooth and glossy surfaces, although these particles varied in diameter and elemental composition. The diameter of fly ash particles ranged from 0.76 to 16.7 m, with an average of 3.79 m (median: 3.21 m). Individual particle analyses of elemental composition showed that particles formed in combustion were mainly composed of carbon, silicon, aluminum and trace elements (e.g. Na, K, Ca, Fe). Some spherical fly ash particles contained toxic heavy metals (e.g. Pb, Cr, As, Zn), and indicated that fly ash particles acted as the main possible carriers of toxic heavy metals deposited in snow and ice of glaciers in high altitudes of central Asia. On the basis of chemical information obtained from EDX, the fly ash particles deposited in the snow could be classified into four types. Namely, Si-dominant particles, with average diameters of 3.24 m were formed by industrial coal combustion via high temperature processes in typical coal-fired heating stations and thermal power plants. Moreover, Fe-dominant particles, with average diameters of 3.82 m, and Ti-dominant spherical particles formed by lower temperature processes in foundry and iron or steel plants. In addition, C-dominant particles, with average diameters of 8.43 m, formed from unburned coal. Fe-dominant particles had larger average diameters than Sidominant particles, indicating that the former were easier to form and developed earlier in the furnace because of their differential melting points of compositional oxide. Backward air mass trajectory analysis suggests that the developed urban regions of central Asia contributed the primary fly ash particles from industrial combustion to the study site through the high-level westerlies jet steam. | ZHANG XueLei WU GuangJian YAO TanDong ZHANG ChengLong YUE YaHui | 2011 | Chinese Science Bulletin2011，56，32： | 7 |
| 4 | Recent progress of integrated circuits and optoelectronic chips显示文摘Integrated circuits(ICs)and optoelectronic chips are the foundation stones of the modern information society.The IC industry has been driven by the so-called'Moore's law'in the past 60 years,and now has entered the post Moore's law era.In this paper,we review the recent progress of ICs and optoelectronic chips.The research status,technical challenges and development trend of devices,chips and integrated technologies of typical IC and optoelectronic chips are focused on.The main contents include the development law of IC and optoelectronic chip technology,the IC design and processing technology,emerging memory and chip architecture,brain-like chip structure and its mechanism,heterogeneous integration,quantum chip technology,silicon photonics chip technology,integrated microwave photonic chip,and optoelectronic hybrid integrated chip. | Yue HAO Shuiying XIANG Genquan HAN Jincheng ZHANG Xiaohua MA Zhangming ZHU Xingxing GUO Yahui ZHANG Yanan HAN Ziwei SONG Yan LIU Ling YANG Hong ZHOU Jiangyi SHI Wei ZHANG Min XU Weisheng ZHAO Biao PAN Yangqi HUANG Qi LIU Yimao CAI Jian ZHU Xin OU Tiangui YOU Huaqiang WU Bin GAO Zhiyong ZHANG Guoping GUO Yonghua CHEN Yong LIU Xiangfei CHEN Chunlai XUE Xingjun WANG Lixia ZHAO Xihua ZOU Lianshan YAN Ming LI | 2021 | Science China(Information Sciences)2021，64，10： | 7 |
| 5 | Enhanced memory capacity of a neuromorphic reservoir computing system based on a VCSEL with double optical feedbacks显示文摘In this paper,a neuromorphic reservoir computing(RC)system with enhanced memory capacity(MC)based on a vertical-cavity surface-emitting laser(VCSEL)subject to double optical feedbacks(DOF)is proposed and investigated numerically.The aim of this study is to explore the MC of the proposed system.For the purpose of comparison,the MC of the VCSEL-based RC system with single optical feedback(SOF)is also taken into account.It is found that,compared with the VCSEL-based RC system subject to SOF,enhanced MC can be obtained for the VCSEL-based RC system with DOF.Besides,the effects of feedback strength,injected strength,frequency detuning as well as injection current on the MC of the VCSEL-based RC system with DOF are considered.Moreover,the influence of feedback delays is also carefully examined.Thus,such proposed VCSEL-based RC system with DOF provides a prospect for the further development of the neuromorphic photonic system based on RC. | Xingxing GUO Shuiying XIANG Yahui ZHANG Aijun WEN Yue HAO | 2020 | Science China(Information Sciences)2020，63，6： | 5 |
| 6 | Photonic integrated spiking neuron chip based on a self-pulsating DFB laser with a saturable absorber显示文摘We proposed and experimentally demonstrated a simple and novel photonic spiking neuron based on a distributed feedback(DFB)laser chip with an intracavity saturable absorber(SA).The DFB laser with an intracavity SA(DFBSA)contains a gain region and an SA region.The gain region is designed and fabricated by the asymmetric equivalentπ-phase shift based on the reconstruction-equivalent-chirp technique.Under properly injected current in the gain region and reversely biased voltage in the SA region,periodic self-pulsation was experimentally observed due to the Q-switching effect.The self-pulsation frequency increases with the increase of the bias current and is within the range of several gigahertz.When the bias current is below the self-pulsation threshold,neuronlike spiking responses appear when external optical stimulus pulses are injected.Experimental results show that the spike threshold,temporal integration,and refractory period can all be observed in the fabricated DFB-SA chip.To numerically verify the experimental findings,a time-dependent coupled-wave equation model was developed,which described the physics processes inside the gain and SA regions.The numerical results agree well with the experimental measurements.We further experimentally demonstrated that the weighted sum output can readily be encoded into the self-pulsation frequency of the DFB-SA neuron.We also benchmarked the handwritten digit classification task with a simple single-layer fully connected neural network.By using the experimentally measured dependence of the self-pulsation frequency on the bias current in the gain region as an activation function,we can achieve a recognition accuracy of 92.2%,which bridges the gap between the continuous valued artificial neural networks and spike-based neuromorphic networks.To the best of our knowledge,this is the first experimental demonstration of a photonic integrated spiking neuron based on a DFB-SA,which shows great potential to realizing large-scale multiwavelength photonic spiking neural network chips. | YUECHUN SHI SHUIYING XIANG XINGXING GUO YAHUI ZHANG HONGJI WANG DIANZHUANG ZHENG YUNA ZHANG YANAN HAN YONG ZHAO XIAOJUN ZHU XIANGFEI CHEN XUN LI YUE HAO | 2023 | Photonics Research2023，11，8： | 2 |
| 7 | Experimental demonstration of pyramidal neuron-like dynamics dominated by dendritic action potentials based on a VCSEL for all-optical XOR classification task显示文摘We experimentally and numerically demonstrate an approach to optically reproduce a pyramidal neuron-like dynamics dominated by dendritic Ca^(2+) action potentials(dCaAPs)based on a vertical-cavity surface-emitting laser(VCSEL)for the first time.The biological pyramidal neural dynamics dominated by dCaAPs indicates that the dendritic electrode evoked somatic spikes with current near threshold but failed to evoke(or evoked less)somatic spikes for higher current intensity.The emulating neuron-like dynamics is performed optically based on the injection locking,spiking dynamics,and damped oscillations in the optically injected VCSEL.In addition,the exclusive OR(XOR)classification task is examined in the VCSEL neuron equipped with the pyramidal neuronlike dynamics dominated by dCaAPs.Furthermore,a single spike or multiple periodic spikes are suggested to express the result of the XOR classification task for enhancing the processing rate or accuracy.The experimental and numerical results show that the XOR classification task is achieved successfully in the VCSEL neuron enabled to mimic the pyramidal neuron-like dynamics dominated by dCaAPs.This work reveals valuable pyramidal neuron-like dynamics in a VCSEL and offers a novel approach to solve XOR classification task with a fast and simple all-optical spiking neural network,and hence shows great potentials for future photonic spiking neural networks and photonic neuromorphic computing. | YAHUI ZHANG SHUIYING XIANG XINGYU CAO SHIHAO ZHAO XINGXING GUO AIJUN WEN YUE HAO | 2021 | Photonics Research2021，9，6： | 2 |
| 8 | Experimental demonstration of coherent photonic neural computing based on a Fabry–Perot laser with a saturable absorber显示文摘As Moore’s law has reached its limits,it is becoming increasingly difficult for traditional computing architectures to meet the demands of continued growth in computing power.Photonic neural computing has become a promising approach to overcome the von Neuman bottleneck.However,while photonic neural networks are good at linear computing,it is difficult to achieve nonlinear computing.Here,we propose and experimentally demonstrate a coherent photonic spiking neural network consisting of Mach–Zehnder modulators(MZMs)as the synapse and an integrated quantum-well Fabry–Perot laser with a saturable absorber(FP-SA)as the photonic spiking neuron.Both linear computation and nonlinear computation are realized in the experiment.In such a coherent architecture,two presynaptic signals are modulated and weighted with two intensity modulation MZMs through the same optical carrier.The nonlinear neuron-like dynamics including temporal integration,threshold,and refractory period are successfully demonstrated.Besides,the effects of frequency detuning on the nonlinear neuron-like dynamics are also explored,and the frequency detuning condition is revealed.The proposed hardware architecture plays a foundational role in constructing a large-scale coherent photonic spiking neural network. | DIANZHUANG ZHENG SHUIYING XIANG XINGXING GUO YAHUI ZHANG BILING GU HONGJI WANG ZHENZHEN XU XIAOJUN ZHU YUECHUN SHI YUE HAO | 2023 | Photonics Research2023，11，1： | 2 |
| 9 | Pattern recognition in multi-synaptic photonic spiking neural networks based on a DFB-SA chip显示文摘Spiking neural networks(SNNs)utilize brain-like spatiotemporal spike encoding for simulating brain functions.Photonic SNN offers an ultrahigh speed and power efficiency platform for implementing high-performance neuromorphic computing.Here,we proposed a multi-synaptic photonic SNN,combining the modified remote supervised learning with delayweight co-training to achieve pattern classification.The impact of multi-synaptic connections and the robustness of the network were investigated through numerical simulations.In addition,the collaborative computing of algorithm and hardware was demonstrated based on a fabricated integrated distributed feedback laser with a saturable absorber(DFB-SA),where 10 different noisy digital patterns were successfully classified.A functional photonic SNN that far exceeds the scale limit of hardware integration was achieved based on time-division multiplexing,demonstrating the capability of hardware-algorithm co-computation. | Yanan Han Shuiying Xiang Ziwei Song Shuang Gao Xingxing Guo Yahui Zhang Yuechun Shi Xiangfei Chen Yue Hao | 2023 | Opto-Electronic Science2023，2，9： | 1 |
| 10 | Postcollisional calc-alkaline lavas and xenoliths from the southern Qiangtang terrane, central Tibet显示文摘 | Lin Ding Paul Kapp Yahui Yue Qingzhou Lai | 2006 | Earth and Planetary Science Letters2006，，1： | 1 |
| 11 | Photonic integrated neuro-synaptic core for convolutional spiking neural network显示文摘Neuromorphic photonic computing has emerged as a competitive computing paradigm to overcome the bottlenecks of the von-Neumann architecture.Linear weighting and nonlinear spike activation are two fundamental functions of a photonic spiking neural network(PSNN).However,they are separately implemented with different photonic materials and devices,hindering the large-scale integration of PSNN.Here,we propose,fabricate and experimentally demonstrate a photonic neuro-synaptic chip enabling the simultaneous implementation of linear weighting and nonlinear spike activation based on a distributed feedback(DFB)laser with a saturable absorber(DFB-SA).A prototypical system is experimentally constructed to demonstrate the parallel weighted function and nonlinear spike activation.Furthermore,a fourchannel DFB-SA laser array is fabricated for realizing matrix convolution of a spiking convolutional neural network,achieving a recognition accuracy of 87%for the MNIST dataset.The fabricated neuro-synaptic chip offers a fundamental building block to construct the large-scale integrated PSNN chip. | Shuiying Xiang Yuechun Shi Yahui Zhang Xingxing Guo Ling Zheng Yanan Han Yuna Zhang Ziwei Song Dianzhuang Zheng Tao Zhang Hailing Wang Xiaojun Zhu Xiangfei Chen Min Qiu Yichen Shen Wanhua Zheng Yue Hao | 2023 | Opto-Electronic Advances2023，6，11： | 1 |
| 12 | Carbon dots with two-photon fluorescence imaging for efficient synergistic trimodal therapy显示文摘Applying the fluorescent carbon dots as smart materials in anticancer therapy is of great interest.However,carbon dots for multimodal synergistic anticancer therapy,especially for the triple modality,is rarely reported.Herein,we successfully synthesized OCDs by citric acid and(1R,2S)-2-amino-1,2-diphenylethan-1-ol,which show aggregation-induced emission property and two-photon fluorescence imaging.Meanwhile,OCDs are ideal photosensitizers for photothermal therapy under 808 nm and TypeⅠphotodynamic therapy with white light.Hydroxyl radicals,generated by TypeⅠphotodynamic therapy based on OCDs can transform protumoral M2 macrophages into antitumoral M1 macrophages,which exhibited immunotherapy ability.The synergism trimodal of OCDs results in potent anticancer efficacy,showing great potential in cancer therapy. | Yahui Zhang Haoyu Xia Mengdie Yang Hairong Li Feishi Shan Yilong Chen Xue Yue Zhouyu Wang Xiaoqi Yu | 2023 | Chinese Chemical Letters2023，34，9： | 0 |
| 13 | Red/NIR emission carbonized polymer dots based on citric acid-benzoylurea and their application in lymph nodes imaging显示文摘Identification of lymph nodes(LNs)is critical for studies of the structure,the role in disease development,and the efficacy of disease treatment.Carbonized polymer dots(CPDs)are expected to be potential LNs-targeted imaging agents due to their excellent properties with special structure,better photoluminescence(PL)and great biocompatibility.Herein,a red/near infrared(NIR)emission CPDs(RCPDs)with one and two-photon bioimaging based on citric acid(CA)and benzoylurea(BU)are prepared.Notably,the RCPDs are capable of targeting LNs for imaging.Lymphocyte homing has been demonstrated to be the cellular mechanism of RCPDs target LNs imaging.This work has developed a new nanomaterial for targeted imaging of LNs,while the biological applications of CPDs have been expanded and deepened. | Feishi Shan Tingrui Zhang Chengshuang Liao Xue Yue Jing Zhang Li Yan Yanman Liu Zhixing Cao Min Wang Yahui Zhang Leyong Wang Zhouyu Wang Xiaoqi Yu | 2023 | Chinese Chemical Letters2023，34，11： | 0 |
| 14 | Spiking information processing in a single photonic spiking neuron chip with double integrated electronic dendrites显示文摘Dendrites,branches of neurons that transmit signals between synapses and soma,play a vital role in spiking information processing,such as nonlinear integration of excitatory and inhibitory stimuli.However,the investigation of nonlinear integration of dendrites in photonic neurons and the fabrication of photonic neurons including dendritic nonlinear integration in photonic spiking neural networks(SNNs)remain open problems.Here,we fabricate and integrate two dendrites and one soma in a single Fabry–Perot laser with an embedded saturable absorber(FP-SA)neuron to achieve nonlinear integration of excitatory and inhibitory stimuli.Note that the two intrinsic electrodes of the gain section and saturable absorber(SA)section in the FP-SA neuron are defined as two dendrites for two ports of stimuli reception,with one electronic dendrite receiving excitatory stimulus and the other receiving inhibitory stimulus.The stimuli received by two electronic dendrites are integrated non-linearly in a single FP-SA neuron,which generates spikes for photonic SNNs.The properties of frequency encoding and spatiotemporal encoding are investigated experimentally in a single FP-SA neuron with two electronic dendrites.For SNNs equipped with FP-SA neurons,the range of weights between presynaptic neurons and postsynaptic neurons is varied from negative to positive values by biasing the gain and SA sections of FP-SA neurons.Compared with SNN with all-positive weights realized by only biasing the gain section of photonic neurons,the recognition accuracy of Iris flower data is improved numerically in SNN consisting of FP-SA neurons.The results show great potential for multi-functional integrated photonic SNN chips. | YAHUI ZHANG SHUIYING XIANG XINGXING GUO YANAN HAN YUECHUN SHI XIANGFEI CHEN GENQUAN HAN YUE HAO | 2023 | Photonics Research2023，11，12： | 0 |
| 15 | A modified supervised learning rule for training a photonic spiking neural network to recognize digital patterns显示文摘A modified supervised learning rule which is suitable for training photonic spiking neural networks(SNN)is proposed for the first time.The proposed learning rule is independent of the time intervals between actual spike and desired spike or between presynaptic spike and postsynaptic spike.Based on the proposed supervised learning rule,10 digital images are learned in photonic neural network which consists of 30 presynaptic neurons and 10 postsynaptic neurons.Presynaptic and postsynaptic neurons are photonic neurons based on vertical-cavity surface-emitting lasers with an embedded saturable absorber(VCSEL-SA).The results show that 10 digital images are recognized correctly in photonic SNN after enough training.Additionally,the effects of learning rate,the jitters of learning rate,initial weights distribution of SNN and bias current of postsynaptic neurons(VCSELs-SA)on the recognized error are examined carefully based on the proposed learning rule.To the best of our knowledge,such modified supervised learning rule has not yet been reported,which would contribute to training photonic neural networks,and hence is interesting for neuromorphic photonic systems and pattern recognition. | Yahui ZHANG Shuiying XIANG Xingxing GUO Aijun WEN Yue HAO | 2021 | Science China(Information Sciences)2021，64，2： | 0 |
| 16 | Hierarchical porous yolk-shell Co-N-C nanocatalysts encaged in graphene nanopockets for high-performance Zn-air battery显示文摘The rational design and preparation of promising cathode electrocatalysts with excellent activity and strong stability for metal-air batteries is a huge challenge.In this work,we innovate an approach of combining solvothermal with high-temperature pyrolysis utilizing zeolitic imidazolate framework(ZIF)-8 and ZIF-67 as the template to synthesize a novel hybrid material of hierarchical porous yolk-shell Co-N-C polyhedron nanocatalysts engaged in graphene nanopocket(yolk-shell Co-N-C@GNP).The obtained catalyst exhibits prominent bifunctional electrocatalytic performance for oxygen reduction reaction(ORR)and oxygen evolution reaction(OER)in the alkaline condition,in which the half-wave potential is 0.86 V for ORR,and the over-potential for OER is 0.42 V at 10 mA·cm^(-2).The rechargeable aqueous Zn-air battery fabricated with yolk-shell Co-N-C@GNP cathode deliveries an open circuit voltage(OCV)of 1.60 V,a peak power density of 236.2 mW·cm^(-2),and excellent cycling stability over 94 h at 5 mA·cm^(-2).The quasi-solid-state Zn-air battery(ZAB)using yolk-shell Co-N-C@GNP displays a high OCV of 1.40 V and a small voltage gap of 0.88 V in continuous cycling tests at 2 mA·cm^(-2).This work provides a valuable thought to focus attention on the design of high-efficient bifunctional catalysts with hierarchical porous yolk-shell framework and high-density metal active sites for metal-air battery technologies. | Yisi Liu Zongxu Li Shizhu Wang Jinnan Xuan Dongbin Xiong Lina Zhou Jianqing Zhou Jun Wang Yahui Yang Yue Du | 2023 | Nano Research2023，16，7： | 0 |
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