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Heterostructured Mn_(3)O_(4)-MnS Multi-Shelled Hollow Spheres for Enhanced Polysulfide Regulation in Lithium-Sulfur Batteries

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Energy & Environmental Materials 2023年第6期6卷 436-444页

作者： Bin Qin Qun Wang Weiqi Yao Yifei Cai Yuhan Chen Pengcheng Wang Yongchun Zou Xiaohang Zheng Jian Cao Junlei Qi Wei Cai State Key Laboratory of Advanced Welding and Joining Harbin Institute of TechnologyHarbin 150001China College of Chemistry and Chemical Engineering Taiyuan University of TechnologyTaiyuan 030024China State Key Laboratory of Chemical Engineering East China University of Science and TechnologyShanghai 200237China Department of Mechanical Engineering City University of Hong KongHong KongChina Center of Analysis Measurement and Computing Harbin Institute of TechnologyHarbin 150001China School of Materials Science and Engineering Harbin Institute of Technology Harbin 150001China

Constructing heterojunctions and hollow multi-shelled structures can render materials with fascinating physicochemical properties,and have been regarded as two promising strategies to overcome the severe shuttling and sluggish kinetics of polysulfide in lithium-sulfur(Li-S)***,a single strategy can only take limited *** catalytic hosts with synergistic effects are urgently ***,Mn_(3)O_(4)-MnS heterogeneous multi-shelled hollow spheres are meticulously designed by controlled sulfuration of Mn2O3 hollow spheres,and then applied as advanced encapsulation hosts for Li-S *** from the separated spatial confinement by hollow multi-shelled structure,ample exposed active sites and built-in electric field by heterogeneous interface,and synergistic effects between Mn_(3)O_(4)(strong adsorption)and MnS(fast conversion)components,the assembled battery achieves prominent rate capability and decent cyclability(0.016%decay per cycle at 2 C,1000 cycles).More crucially,satisfactory areal capacity reaches up to 7.1 mAh cm^(-2)even with high sulfur loading(8.0 mg cm^(-2))and lean electrolyte(E/S=4.0 pL mg^(-1))*** work will provide inspiration for the rational design of hollow multi-shelled heterostructure for various electrocatalysis applications.

关键词： electrocatalyst heterojunction host hollow multi-shelled structure Li-S battery Mn_(3)O_(4)-MnS

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One-step implementation of a nonadiabatic geometric fSim gate in superconducting circuits

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Physical Review A 2024年第2期110卷 022608-022608页

作者： M.-R. Yun Zheng Shan L.-L. Sun L.-L. Yan Y. Jia Shi-Lei Su Gang Chen School of Physics and Laboratory of Zhongyuan Light Key Laboratory of Materials Physics of Ministry of Education State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou 450001 Henan China College of Physics Institute of Quantum Materials and Physics Key Laboratory for Special Functional Materials of Ministry of Education and School of Materials and Engineering

Due to their significant application in reducing algorithm depth, fSim gates have attracted a lot of attention. However, during the implementation of quantum gates, fluctuations in control parameters and decoherence caused by the environment may lead to a decrease in the fidelity of the gate. Implementing an fSim gate that is robust to these factors in one step remains an unresolved issue. In this paper, we propose a one-step implementation of a nonadiabatic geometric fSim gate composed of a nonadiabatic holonomic controlled-phase (cp) gate and a nonadiabatic noncyclic geometric iswap gate with parallel paths in a tunable superconducting circuit. Compared to the composite nonadiabatic geometric fSim gate composed of a nonadiabatic holonomic cp gate and a nonadiabatic geometric iswap gate, our scheme takes only half the time and demonstrates robustness to parameter fluctuations, as well as to environmental impacts. Moreover, the scheme does not require complex controls, making it very easy to implement in experiments, and can be achieved in various circuit structures. Our scheme may provide a promising path toward quantum computation and simulation.

关键词： Geometric & topological phases Quantum computation Quantum gates

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Minimizing transformer inference overhead using controlling element on Shenwei AI accelerator

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Frontiers of Information Technology & Electronic engineering 2025年第4期26卷 605-622页

作者： Yulong ZHAO Chunzhi WU Yizhuo WANG Lufei ZHANG Yaguang ZHANG Wenyuan SHEN Hao FAN Hankang FANG Yi QIN Xin LIU State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214000China School of Non-Commissioned Officer Space Engineering UniversityBeijing 100004China National Supercomputing Center in Wuxi Wuxi 214000China Zhejiang Lab Hangzhou 310000China National Research Centre of Parallel Computer Engineering and Technology Beijing 100081China

Transformer models have become a cornerstone of various natural language processing(NLP)***,the substantial computational overhead during the inference remains a significant challenge,limiting their deployment in practical *** this study,we address this challenge by minimizing the inference overhead in transformer models using the controlling element on artificial intelligence(AI)*** work is anchored by four key ***,we conduct a comprehensive analysis of the overhead composition within the transformer inference process,identifying the primary ***,we leverage the management processing element(MPE)of the Shenwei AI(SWAI)accelerator,implementing a three-tier scheduling framework that significantly reduces the number of host-device launches to approximately 1/10000 of the original PyTorch-GPU ***,we introduce a zero-copy memory management technique using segment-page fusion,which significantly reduces memory access latency and improves overall inference ***,we develop a fast model loading method that eliminates redundant computations during model verification and initialization,reducing the total loading time for large models from 22128.31 ms to 1041.72 *** contributions significantly enhance the optimization of transformer models,enabling more efficient and expedited inference processes on AI accelerators.

关键词： Transformer inference optimization Three-tier scheduling Zero-copy memory management Fast model loading

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The Causal Reasoning Ability of Open Large Language Model: A Comprehensive and Exemplary Functional Testing

The Causal Reasoning Ability of Open Large Language Model: A...

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IEEE International Conference on Software Quality, Reliability and Security (QRS)

作者： Shun-Hang Li Gang Zhou Zhi-Bo Li Ji-Cang Lu Ning-Bo Huang State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Information Engineering University Zhengzhou China

As the intelligent software, the development and application of large language models are extremely hot topics recently, bringing tremendous changes to general AI and software industry. Nonetheless, large language models, especially open source ones, incontrollably suffer from some potential software quality issues such as instability, inaccuracy, and insecurity, making software testing necessary. In this paper, we propose the first solution for functional testing of open large language models to check full-scene availability and conclude empirical principles for better steering large language models, particularly considering their black box and intelligence properties. Specifically, we focus on the model’s causal reasoning ability, which is the core of artificial intelligence but almost ignored by most previous work. First, for comprehensive evaluation, we deconstruct the causal reasoning capability into five dimensions and summary the forms of causal reasoning task as causality identification and causality matching. Then, rich datasets are introduced and further modified to generate test cases along with different ability dimensions and task forms to improve the testing integrity. Moreover, we explore the ability boundary of open large language models in two usage modes: prompting and lightweight fine-tuning. Our work conducts comprehensive functional testing on the causal reasoning ability of open large language models, establishes benchmarks, and derives empirical insights for practical usage. The proposed testing solution can be transferred to other similar evaluation tasks as a general framework for large language models or their derivations.

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LENSER: A Channel state Information Based Indoor Localization Scheme for Malicious Devices

LENSER: A Channel State Information Based Indoor Localizatio...

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IEEE Internatonal Conference on Mobile Adhoc and Sensor Systems (MASS)

作者： Yongqiang Ma Xiangyang Luo Ruixiang Li Shaoyong Du Wenyan Liu Key Laboratory of Cyberspace Situation Awareness of Henan Province State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

Rapid and accurate localization of illicit micro-recorders, cameras, and other wireless network devices is of great significance for ensuring public privacy and security. However, existing methods are susceptible to environmental noise, have low localization accuracy, high localization time overhead, and require extensive manual involvement. To address these issues, we propose LENSER, a channel state information based indoor localization scheme for illicit wireless network devices. First, we set detection points to capture signal amplitude distribution changes during the antenna array rotation process, thus determining whether there is a line-of-sight propagation relationship between the detection point and the malicious device. Next, we identify the room containing the malicious device based on the line-of-sight propagation relationship and calibrate the measured position and estimate the direction of the malicious device using existing methods within the room. Finally, we establish a linear space based on the direction of the malicious device and propose an iterative comparison method based on received signal strength indicator to localize malicious devices accessing public Wi-Fi networks within the room. We conducted 1200 experiments in four buildings with different layouts and building materials. The results show that LENSER’s average localization time is 12.5 minutes, and the average localization accuracy is 26.4 centimeters, an improvement of 11.1% to 86.1% in average localization accuracy and a reduction of 11.1% to 58.2% in average localization time compared to existing methods, such as Spotfi, Lumos, SCamF, SNOOPDOG, and Region Division.

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On the Cycle Structure of Some Nonlinear Feedback Shift Registers

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Chinese Journal of Electronics 2025年第4期23卷 801-804页

作者： Zhongxiao Wang Hong Xu Wenfeng Qi State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Information Science and Technology Institute Zhengzhou China Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China

In this paper, we partly determine the cycle structure of two types of Nonlinear feedback shift registers (NFSRs). Based on these results, the cycle structure of a class of NFSRs with symmetric feedback functions can be completely characterized. Furthermore, an alternative proof of Kjeldsen's results is presented. Compared with the original proof based on abstract algebra theory, ours is straightforward and easy to understand.

关键词： Abstract algebra Shift registers Cryptography

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A Riemannian Exponential Augmented Lagrangian Method for computing the Projection Robust Wasserstein Distance 37

A Riemannian Exponential Augmented Lagrangian Method for Com...

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37th Conference on Neural Information Processing Systems, NeurIPS 2023

作者： Jiang, Bo Liu, Ya-Feng Ministry of Education Key Laboratory of NSLSCS School of Mathematical Sciences Nanjing Normal University Nanjing210023 China State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9781713899921

Projection robust Wasserstein (PRW) distance is recently proposed to efficiently mitigate the curse of dimensionality in the classical Wasserstein distance. In this paper, by equivalently reformulating the computation of the PRW distance as an optimization problem over the Cartesian product of the Stiefel manifold and the Euclidean space with additional nonlinear inequality constraints, we propose a Riemannian exponential augmented Lagrangian method (REALM) for solving this problem. Compared with the existing Riemannian exponential penalty-based approaches, REALM can potentially avoid too small penalty parameters and exhibit more stable numerical performance. To solve the subproblems in REALM efficiently, we design an inexact Riemannian Barzilai-Borwein method with Sinkhorn iteration (iRBBS), which selects the stepsizes adaptively rather than tuning the stepsizes in efforts as done in the existing methods. We show that iRBBS can return an Ε-stationary point of the original PRW distance problem within O(Ε-3) iterations, which matches the best known iteration complexity result. Extensive numerical results demonstrate that our proposed methods outperform the state-of-the-art solvers for computing the PRW distance. © 2023 Neural information processing systems foundation. All rights reserved.

关键词： Constrained optimization

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Polytopic Attack on Round-Reduced Simon32/64 Using Deep Learning 16th

Polytopic Attack on Round-Reduced Simon32/64 Using Deep Lear...

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16th International Conference on Information Security and Cryptology, Inscrypt 2020

作者： Su, Heng-Chuan Zhu, Xuan-Yong Ming, Duan State Key Laboratory of Mathematical Engineering and Advanced Computing Information Engineering University Zhengzhou450001 China

ISBN: (纸本)9783030718510

In CRYPTO 2019, Gohr uses the residual network technology of artificial intelligence to build a differential distinguisher, and attacks the reduced-round Speck32/64. We tried this method to recover the keys for ten-round Simon32/64. In this paper, we have three innovations. First, we construct polytope neural network distinguisher. On eight-round Simon32/64, polytope neural network distinguisher could increase the success rate of three neural network distinguishers with 0.76 success rate to 0.92. Second, we propose an attack on Simon32/64 based on the combination of the probability of differential path and polytope neural network distinguisher. This method can only increase the computational complexity of the chosen data as the number of rounds increases. Nine-round polytope neural network distinguisher is used to filter out data, whether it is what we want. Eight-round neural distinguisher is used to recover the final round key. The computational complexity of key recovery on the final key of eleven-round Simon32/64 is 233.4. Third, we propose an attack called Bayesian key Research with Error. With this attack, the computational complexity of key recovery on the final key of eleven-round Simon32/64 is 230.9. In our paper, the main idea is combining polytope differences with neural networks. By constructing polytope differential neural network distinguisher, we make a key recovery attack. In order to increase the number of rounds, we first used brute force attack and then proposed Bayesian key Research with Error. We think this idea can be applied to many cryptographic algorithms. © 2021, Springer Nature Switzerland AG.

关键词： Computational complexity

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Ultra-low power MoS2 optoelectronic synapse with wavelength sensitivity for color target recognition

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Science China(Information Sciences) 2025年第4期68卷 187-196页

作者： Bo WEI Yabo CHEN Xiaotong HAN Yan KANG Bujia LIANG Cheng LI Xiaokuo YANG Liang FANG Yuanxi PENG Institute for Quantum Information & State Key Laboratory of High Performance Computing College of ComputerNational University of Defense Technology Fundamentals Department Air Force Engineering University College of Advanced Interdisciplinary Studies National University of Defense Technology Institute of Quantum Information Science and Technology College of ScienceNational University of Defense Technology College of Computer National University of Defense Technology

Optoelectronic synapses that integrate visual perception and pre-processing hold significant potential for neuromorphic vision systems（NVSs）. However, due to a lack of wavelength sensitivity, existing NVS mainly focuses on gray-scale image processing, making it challenging to recognize color images. Additionally, the high power consumption of optoelectronic synapses, compared to the 10 fJ energy consumption of biological synapses, limits their broader application. To address these challenges, an energy-efficient NVS capable of color target recognition in a noisy environment was developed,utilizing a MoS2optoelectronic synapse with wavelength sensitivity. Benefiting from the distinct photon capture capabilities of 450, 535, and 650 nm light, the optoelectronic synapse exhibits wavelength-dependent synaptic plasticity, including excitatory postsynaptic current（EPSC）, paired-pulse facilitation（PPF）, and long-term plasticity（LTP）. These properties can effectively mimic the visual memory and color discrimination functions of the human vision system. Results demonstrate that the NVS, based on MoS2optoelectronic synapses, can eliminate the color noise at the sensor level, increasing color image recognition accuracy from 50% to 90%. Importantly, the optoelectronic synapse operates at a low voltage spike of0.0005 V, consuming only 0.075 fJ per spike, surpassing the energy efficiency of both existing optoelectronic and biological synapses. This ultra-low power, color-sensitive device eliminates the need for color filters and offers great promise for future deployment in filter-free NVS.

关键词： optoelectronic synapse neuromorphic vision system color recognition 2D materials image pre-processing

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Boosting cationic and anionic redox activity of Li-rich layered oxide cathodes via Li/Ni disordered regulation

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Journal of Energy Chemistry 2025年第1期100卷 533-543页

作者： Zewen Liu Zhen Wu Hao Wang Xudong Zhang Yuanzhen Chen Yongning Liu Shengwu Guo Shenghua Chen Yanli Nan Yan Liu State Key Laboratory for Mechanical Behavior of Materials Xi’an Jiaotong UniversityXi’an 710049ShaanxiChina School of Materials Science and Engineering Xi’an University of Architecture and TechnologyXi’an 710055ShaanxiChina Hefei Advanced Computing Center Operation Management Corp Ltd Hefei 230088AnhuiChina Network Information Center Xi’an Jiaotong UniversityXi’an 710049ShaanxiChina

Lithium-rich layered oxides (LLOs) are increasingly recognized as promising cathode materials for nextgeneration high-energy-density lithium-ion batteries (LIBs).However,they suffer from voltage decay and low initial Coulombic efficiency (ICE) due to severe structural degradation caused by irreversible O ***,we introduce a three-in-one strategy of increasing Ni and Mn content,along with Li/Ni disordering and TM–O covalency regulation to boost cationic and anionic redox activity simultaneously and thus enhance the electrochemical activity of *** target material,Li_(1.2)Ni_(0.168)Mn_(0.558)Co_(0.074)O_(2)(L1),exhibits an improved ICE of 87.2%and specific capacity of 293.2 mA h g^(-1)and minimal voltage decay of less than 0.53 m V cycle-1over 300 cycles at 1C,compared to Li_(1.2)Ni_(0.13)Mn_(0.54)Co_(0.13)O_(2)(Ls)(274.4 mA h g^(-1)for initial capacity,73.8%for ICE and voltage decay of 0.84 mV/cycle over 300 cycles at 1C).Theoretical calculations reveal that the density of states (DOS) area near the Fermi energy level for L1 is larger than that of Ls,indicating higher anionic and cationic redox reactivity than ***,L1 exhibits increased O-vacancy formation energy due to higher Li/Ni disordering of 4.76%(quantified by X-ray diffraction Rietveld refinement) and enhanced TM–O covalency,making lattice O release more difficult and thus improving electrochemical *** increased Li/Ni disordering also leads to more Ni^(2+)presence in the Li layer,which acts as a pillar during Li+de-embedding,improving structural *** research not only presents a viable approach to designing low-Co LLOs with enhanced capacity and ICE but also contributes significantly to the fundamental understanding of structural regulation in high-performance LIB cathodes.

关键词： Low-Co Li-rich layered oxides Li/Ni disordering TM-O covalency Cationic and anionic redox activity

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