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Progress in manipulating spin polarization for solar hydrogen production

Materials Reports(Energy) 2024年第1期4卷 43-57页

作者： Qian Yang Xin Tong Zhiming Wang Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of ChinaChengdu 610054PR China Yangtze Delta Region Institute(Huzhou) University of Electronic Science and Technology of ChinaHuzhou 313001PR China Institute for Advanced Study Chengdu UniversityChengdu 610106PR China

Photocatalytic and photoelectrochemical water splitting using semiconductor materials are effective approaches for converting solar energy into hydrogen *** the past few years,a series of photocatalysts/photoelectrocatalysts have been developed and optimized to achieve efficient solar hydrogen *** various optimization strategies,the regulation of spin polarization can tailor the intrinsic optoelectronic properties for retarding charge recombination and enhancing surface reactions,thus improving the solar-to-hydrogen(STH)*** review presents recent advances in the regulation of spin polarization to enhance spin polarized-dependent solar hydrogen evolution ***,spin polarization manipulation strategies of several typical photocatalysts/photoelectrocatalysts(e.g.,metallic oxides,metallic sulfides,non-metallic semiconductors,ferroelectric materials,and chiral molecules)are *** the end,the critical challenges and perspectives of spin polarization regulation towards future solar energy conversion are briefly provided.

关键词： Spin polarization Solar energy conversion Photocatalytic hydrogen production Photoelectrochemical water splitting

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Boring holes in Au nanoplates by active surface etching

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Nano Research 2024年第9期17卷 8610-8617页

作者： Haiyang Hu Yuntao Wang Qian Wang Xudong Peng An Su Hong Wang Hongyu Chen Institute of Advanced Synthesis(IAS)and School of Chemistry and Molecular Engineering Jiangsu National Synergetic Innovation Centre for Advanced MaterialsNanjing Tech UniversityNanjing 211816China Department of Environmental Science and Engineering University of Science and Technology of ChinaHefei 230026China Department of Chemistry School of Science and Key Laboratory for Quantum Materials of Zhejiang ProvinceResearch Center for Industries of the FutureWestlake UniversityHangzhou 310030China Institute of Natural Sciences Westlake Institute for Advanced StudyHangzhou 310024China

In contrast to the conventional etching that makes nanoparticles rounder and our previous sharpening etching mode that causes serrated edges,here,we developed a new boring etching mode that targets the faces of Au nanoplates to make *** critical factors are the pre-incubation step with the ligand 2-mercapto-5-benzimidazolecarboxylic acid(MBIA)and the subsequent removal of excess ligands in the ***,etching is focused onto the few sites with initial loss of ligands,which cannot be quickly *** choice of ligand MBIA is also of importance,as it carries negative charge and repels each *** inability of forming a dense layer probably plays a critical role in the site-selectivity for faces,because ligands at the higher curvature edges and corners are expected to have less *** etching results from the comproportionation reaction between Au3+and Au0 in the nanoplates,where Br-coordination to Au and the extra stabilization from cetyltrimethylammonium bromide(CTAB)are *** believe that the ability of boring holes is an important tool for future synthetic designs.

关键词： Au nanoplates active surface etching boring etching mode cetyltrimethylammonium bromide(CTAB)passivation holes

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A Three-dimensional Electromagnetic Scattering Simulation Tool

A Three-dimensional Electromagnetic Scattering Simulation To...

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2024 Photonics and Electromagnetics Research Symposium, PIERS 2024

作者： Liu, H. Xu, L. Liu, B.Q. University of Electronic Science and Technology of China Chengdu China Shenzhen Institute for Advanced Study Uestc Shenzhen China

ISBN: (纸本)9798350375909

Electromagnetic scattering analysis plays a pivotal role in radar, communication, and various other fields. This paper presents a highly efficient three-dimensional electromagnetic scattering simulation tool based on the method of moments (MoM). To enhance the computational efficiency of MoM for solving electromagnetic scattering problems, we have implemented the multilevel fast multipole algorithm (MLFMA) to accelerate the matrix-vector multiplication during iterative solving. Furthermore, we have parallelized the tool using MPI/OpenMP technology to further expedite its computational efficiency. Numerical examples verify the accuracy and efficiency of the electromagnetic scattering simulation tool. © 2024 IEEE.

关键词： Iterative methods

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Combine deep learning and Bayesian analysis to separate overlapping gravitational wave signals

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science China(Physics,Mechanics & Astronomy) 2025年第5期68卷 205-219页

作者： Cunliang Ma Weiguang Zhou Zhoujian Cao Mingzhen Jia Jiangxi Provincial Key Laboratory of Multidimensional Intelligent Perception and Control Jiangxi University of Science and TechnologyGanzhou 341000China Institute of Applied Mathematics Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Fundamental Physics and Mathematical Sciences Hangzhou Institute for Advanced StudyUCASHangzhou 310024China

Future gravitational wave(GW)observatories,such as the Einstein Telescope,are anticipated to encounter overlapping GW signals,presenting considerable obstacles to GW data processing techniques,including signal identification and parameter *** this letter,we propose a scheme of combining deep learning and Bayesian analysis to disentangle overlapping GW *** deep learning part takes a data-driven approach that employs an encoder-separation-decoder framework which is powerful enough to extract the shape of the signal even when the GW signals completely *** Bayesian analysis part takes the matched filtering technique to extract the amplitude of the GW *** scheme can facilitate the utilization of existing GW detection and parameter estimation methods for future instances of overlapping *** methodology effectively reduces biases in parameter estimation when handling multiple intertwined ***,this marks the first known instance where deep learning has been successfully utilized to disentangle overlapping GW signals.

关键词： gravitational wave separation machine learning Einstein Telescope parameter estimation

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Enhancing Court View Generation with Knowledge Injection and Guidance 30

Enhancing Court View Generation with Knowledge Injection and...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Li, Ang Wu, Yiquan Liu, Yifei Wu, Fei Cai, Ming Kuang, Kun College of Computer Science and Technology Zhejiang University China Shanghai Institute for Advanced Study of Zhejiang University China

ISBN: (纸本)9782493814104

Court View Generation (CVG) is a challenging task in the field of Legal Artificial Intelligence (LegalAI), which aims to generate court views based on the plaintiff claims and the fact descriptions. While Pretrained Language Models (PLMs) have showcased their prowess in natural language generation, their application to the complex, knowledge-intensive domain of CVG often reveals inherent limitations. In this paper, we present a novel approach, named Knowledge Injection and Guidance (KIG), designed to bolster CVG using PLMs. To efficiently incorporate domain knowledge during the training stage, we introduce a knowledge-injected prompt encoder for prompt tuning, thereby reducing computational overhead. Moreover, to further enhance the model's ability to utilize domain knowledge, we employ a generating navigator, which dynamically guides the text generation process in the inference stage without altering the model's architecture, making it readily transferable. Comprehensive experiments on real-world data demonstrate the effectiveness of our approach compared to several established baselines, especially in the responsivity of claims, where it outperforms the best baseline by 11.87%. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Domain Knowledge

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CoIN: A Benchmark of Continual Instruction Tuning for Multimodal Large Language Models 38

CoIN: A Benchmark of Continual Instruction Tuning for Multim...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Chen, Cheng Zhu, Junchen Luo, Xu Shen, Heng Tao Song, Jingkuan Gao, Lianli Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China China University of Electronic Science and Technology of China China Tongji University China

Instruction tuning demonstrates impressive performance in adapting Multimodal Large Language Models (MLLMs) to follow task instructions and improve generalization ability. By extending tuning across diverse tasks, MLLMs can further enhance their understanding of world knowledge and instruction intent. However, continual instruction tuning has been largely overlooked and there are no public benchmarks available. In this paper, we present CoIN, a comprehensive benchmark tailored for assessing the behavior of existing MLLMs under continual instruction tuning. CoIN comprises 10 meticulously crafted datasets spanning 8 tasks, ensuring diversity and serving as a robust evaluation framework to assess crucial aspects of continual instruction tuning, such as task order, instruction diversity and volume. Additionally, apart from traditional evaluation, we design another LLM-based metric to assess the knowledge preserved within MLLMs for reasoning. Following an in-depth evaluation of several MLLMs, we demonstrate that they still suffer catastrophic forgetting, and the failure in instruction alignment assumes the main responsibility, instead of reasoning knowledge forgetting. To this end, we introduce MoELoRA which is effective in retaining the previous instruction alignment. Codes and datasets are publicly available https://***/zackschen/CoIN. © 2024 Neural information processing systems foundation. All rights reserved.

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Enhanced Federated Learning with Adaptive Block-wise Regularization and Knowledge Distillation 31

Enhanced Federated Learning with Adaptive Block-wise Regular...

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31st IEEE/ACM International Symposium on Quality of Service, IWQoS 2023

作者： Zeng, Qingmin Liu, Jianchun Xu, Hongli Wang, Zhiyuan Xu, Yang Zhao, Yangming School of Computer Science and Technology University of Science and Technology of China Suzhou Institute for Advanced Study University of Science and Technology of China China

ISBN: (纸本)9798350399738

Federated Learning (FL) has emerged as an efficient distributed model training framework that enables multiple clients cooperatively to train a global model without exposing their local data in edge computing (EC). However, FL usually faces statistical heterogeneity (e.g., non-IID data) and system heterogeneity (e.g., computing and communication capabilities), resulting in poor model training performance. To deal with the above two challenges, we propose an efficient FL framework, named FedBR, which integrates the idea of block-wise regularization and knowledge distillation (KD) into the pioneer FL algorithm FedAvg, for resource-constrained edge computing. Besides, we design a heuristic algorithm (GMBS) to determine the appropriate number of model blocks for clients according to their varied data distributions, computing, and communication capabilities. Extensive experimental results show that FedBR can reduce the time cost by 19.5% and the communication cost by 27% on average compared with the other three baselines when achieving the target testing accuracy under heterogeneous settings. © 2023 IEEE.

关键词： Distillation

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Energy Oriented Three-Tier Computation Offloading Scheme in Maritime Edge Computing Network

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IEEE Transactions on Vehicular technology 2025年第5期74卷 8126-8140页

作者： Zhang, Hongxia Xi, Shiyu Shang, Bodong Zhang, Peiying Wu, Sheng Jiang, Chunxiao Qingdao Institute of Software College of Computer Science and Technology Qingdao266580 China Eastern Institute of Technology Eastern Institute for Advanced Study Ningbo315200 China Beijing University of Posts and Telecommunications School of Information and Communication Engineering Beijing100876 China Tsinghua University Beijing National Research Center for Information Science and Technology Beijing100084 China

With the development of maritime continuing to grow, large-scale maritime wireless devices (MWDs) are being deployed for various maritime applications. The rapid development of maritime Internet of Things (IoT) and growing demand for these applications have led to an increasing number of computation-intensive and resource-sensitive tasks. Considering the limited computing capacity and energy of MWDs, it is challenging to transmit and process massive maritime computing tasks in an energy efficient manner. In this paper, we propose a three-tier maritime edge computing system in which low earth orbit (LEO) satellite and offshore base station (OBS) support to provide communication and computing services for MWDs. The system optimizes association variable, task partitioning, transmission power, and computing resource allocation to reduce system energy consumption under latency constraints. The optimization problem is formulated as a mixed integer non-linear programming (MINLP) optimization problem. We decompose the original problem into four subproblems and design algorithms to solve them. Firstly, the association variable optimization subproblem is solved by slack variable method. Then, we adopt quadratic transformation and design a difference of convex algorithm to solve transmission power optimization subproblem. Further, task partitioning subproblem is solved by obtaining upper and lower bounds of offloading task size by strict deduction, and then solved by the standard convex method. Finally, Lagrangian dual method is utilized to deal with joint computing resource optimization subproblem of LEO satellite and OBS. In simulation results, the proposed algorithm saves 39.3% of system energy consumption compared to benchmark schemes. © 1967-2012 IEEE.

关键词： Computation offloading

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Synergistic effect of silicon availability and salinity on metal adsorption in a common estuarine diatom

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Journal of Environmental sciences 2025年第2期148卷 364-374页

作者： Fengyuan Chen Jie Ma Ke Pan SZU-HKUST Joint PhD Program in Marine Environmental Science Shenzhen UniversityShenzhen 518060China Shenzhen Key Laboratory of Marine Microbiome Engineering Institute for Advanced StudyShenzhen UniversityShenzhen 518060China Department of Ocean Science The Hong Kong University of Science and TechnologyHong Kong 999077China

Increasing nitrogen and phosphorus discharge and decreasing sediment input have made silicon(Si)a limiting element for diatoms in *** in nutrient structure and salinity fluctuation can greatly affect metal uptake by estuarine ***,the combined effects of Si and salinity on metal accumulation in these diatoms have not been *** this study,we aimed to investigate how salinity and Si availability combine to influence the adsorption of metals by a widely distributed diatom Phaeodactylum *** data indicate that replete Si and low salinity in seawater can enhance cadmium and copper adsorption onto the diatom *** the single-cell level,surface potential was a dominant factor determining metal adsorption,while surface roughness also contributed to the highermetal loading capacity at lower *** a combination of noninvasive micro-test technology,atomic force microscopy,X-ray photoelectron spectroscopy,and Fourier transform infrared spectroscopy,we demonstrate that the diversity and abundance of the functional groups embedded in diatom cell walls vary with salinity and Si *** results in a change in the cell surface potential and transient metal *** study provides novel mechanisms to explain the highly variable metal adsorption capacity of a model estuarine diatom.

关键词： Diatom Metal adsorption Silicon Salinity Functional group Surface potential

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Digital twin empowered lightweight and efficient blockchain for dynamic internet of vehicles

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Digital Communications and Networks 2024年第6期10卷 1698-1707页

作者： Haoye Chai Supeng Leng Jianhua He Ke Zhang School of Information and Communication Engineering University of Electronic Science and Technology of China(UESTC)Chengdu611731China Shenzhen Institute for Advanced Study UESTCShenzhen518000China School of Computer Science and Electronic Engineering University of EssexColchesterCO43SQUK

The Internet of Vehicles(Io V)has great potential for Intelligent Transportation Systems(ITS),enabling interactive vehicle applications,such as advanced driving and *** is crucial to ensure the reliability during the vehicle-to-vehicle interaction *** the emerging blockchain has superiority in handling security-related issues,existing blockchain-based schemes show weakness in highly dynamic Io *** the transaction broadcast and consensus process require multiple rounds of communication throughout the whole network,while the high relative speed between vehicles and dynamic topology resulting in the intermittent connections will degrade the efficiency of *** this paper,we propose a Digital Twin(DT)-enabled blockchain framework for dynamic Io V,which aims to reduce both the communication cost and the operational latency of *** address the dynamic context,we propose a DT construction strategy that jointly considers the DT migration and blockchain computing ***,a communication-efficient Local Perceptual Multi-Agent Deep Deterministic Policy Gradient(LPMA-DDPG)algorithm is designed to execute the DT construction strategy among edge servers in a decentralized *** simulation results show that the proposed framework can greatly reduce the communication cost,while achieving good security *** dynamic DT construction strategy shows superiority in operation latency compared with benchmark *** decentralized LPMA-DDPG algorithm is helpful for implementing the optimal DT construction strategy in practical ITS.

关键词： Digital twin Blockchain Internet of vehicles Multi-agent DDPG

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