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Effective catalytic effects of Mo2C MXene on the hydrogen storage in magnesium hydride

Journal of Magnesium and Alloys 2025年

作者： Wang, Xiaojiao Yuan, Zhenluo Shi, Yang Li, Shangsheng Mi, Guofa Peng, Qiuming Han, Shumin Fan, Yanping Liu, Baozhong School of Materials Science and Engineering Henan Polytechnic University Jiaozuo454003 China College of Chemistry and Chemical Engineering Henan Polytechnic University Jiaozuo454003 China State Key Laboratory of Metastable Materials Science and Technology Yanshan University Qinhuangdao066004 China

Magnesium hydride (MgH2) has received widespread attention because of its high hydrogen capacity and low cost, but the sluggish kinetics limited its practical application. Herein, the two-dimensional Mo2C MXene was constructed to motivate the efficient hydrogen storage in MgH2 for the first time. After doping 10 wt% Mo2C MXene, the starting dehydriding temperature was lowered to 225 °C, presenting a 117 °C reduction compared with that of as-received MgH2. The 10 wt% Mo2C-containing MgH2 sample could rapidly release 6.7 wt% H2 in 13 min at 300 °C, and the product after hydrogen release could absorb 6.0 wt% H2 in 12 min at 200 °C, showing superior hydriding and dehydriding kinetics. Moreover, the activation energy (Ea) of MgH2–10 wt% Mo2C (107.58 ± 1.57 kJ/mol) was obviously lower than that of pure MgH2 (130.45 ± 1.97 kJ/mol), and the reduced activation energy explained the reduced dehydrogenation temperature and enhanced kinetics. Microstructure characterization revealed that Mo-species (Mo0 and Mo2+) formed during ball milling served as active species accelerated the hydriding/dehydriding reactions, and the uniformly distributed active species and the interaction between Mo and O jointly promoted the hydrogen storage properties of MgH2. © 2025

关键词： Activation energy

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LightGCN-LSC: Lightweight Graph Convolution Network for Learning Style Classification in Online Education

LightGCN-LSC: Lightweight Graph Convolution Network for Lear...

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International Conference on Networking and Network Applications (NaNA)

作者： Wanying Suo Bello Ahmad Muhammad Bo Liu Ministry of Education Key Laboratory of Modern Teaching Technology Xi’an China School of Computer Science Shaanxi Normal University Xi’an China School of Computer Science and Technology Henan Institute of Science and Technology Henan China

ISBN: (数字)9798350376777

ISBN: (纸本)9798350376784

How to understand learners have always been the core goal of educational information science and technology, and will greatly lead the practical process of future education. Learning style recognition can largely reflect the learning status and internal cognitive structure of learners, then achieve personalized guidance and precise recommendations. However, the existing collaborative or automatic methods are limited by a large amount of data and have poor portability due to being limited to specific platforms. In this paper, we propose lightGCN-LSC, a novel learning style classfication approach using lightweight graph neural network. First, we build different embedding technique to extract hidden features of S-M bipartite graph, then we employ the K-means clustering algorithm to cluster learners and obtain labels utilizing the FSLSM model. Finally, lightweight graph neural network suitable for S-M graph data size and structure is trained to classify student’s learning style. The superiority of our method was demonstrated through experiments on dataset KDD CUP 2015. Our proposed lightweight models achieved outstanding results (about $1.18-8.24 \%$ improvement) over Graph Convolutional Networks (GCN), and the best result with improvment values of $2.05 \%$ accuracy, $8.24 \%$ precision, $2.05 \%$ recall, and $4.05 \%$ F1 score.

关键词： Representation learning Information science Graph convolutional networks Education Clustering algorithms Lead Feature extraction

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AOCC-FL: Federated Learning with Aligned Overlapping via Calibrated Compensation 42

AOCC-FL: Federated Learning with Aligned Overlapping via Cal...

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42nd IEEE International Conference on computer Communications, INFOCOM 2023

作者： Wang, Haozhao Xu, Wenchao Fan, Yunfeng Li, Ruixuan Zhou, Pan Huazhong University of Science and Technology School of Computer Science and Technology Wuhan China The Hong Kong Polytechnic University Department of Computing Hong Kong Huazhong University of Science and Technology Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Wuhan China

ISBN: (纸本)9798350334142

Federated Learning enables collaboratively model training among a number of distributed devices with the coordination of a centralized server, where each device alternatively performs local gradient computation and communication to the server. FL suffers from significant performance degradation due to the excessive communication delay between the server and devices, especially when the network bandwidth of these devices is limited, which is common in edge environments. Existing methods overlap the gradient computation and communication to hide the communication latency to accelerate the FL training. However, the overlapping can also lead to an inevitable gap between the local model in each device and the global model in the server that seriously restricts the convergence rate of learning process. To address this problem, we propose a new overlapping method for FL, AOCC-FL, which aligns the local model with the global model via calibrated compensation such that the communication delay can be hidden without deteriorating the convergence performance. Theoretically, we prove that AOCC-FL admits the same convergence rate as the non-overlapping method. On both simulated and testbed experiments, we show that AOCC-FL achieves a comparable convergence rate relative to the non-overlapping method while outperforming the state-of-the-art overlapping methods. © 2023 IEEE.

关键词： Learning systems

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The Immense Impact of Reverse Edges on Large Hierarchical Networks

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Engineering 2024年第5期36卷 240-249页

作者： Haosen Cao Bin-Bin Hu Xiaoyu Mo Duxin Chen Jianxi Gao Ye Yuan Guanrong Chen Tamás Vicsek Xiaohong Guan Hai-Tao Zhang MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems State Key Laboratory of Intelligent Manufacturing Equipment and TechnologySchool of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore 639798Singapore Jiangsu Key Laboratory of Networked Collective Intelligence School of MathematicsSoutheast UniversityNanjing 210096China Department of Computer Science Rensselaer Polytechnic InstituteTroyNY 12180USA Department of Electronic Engineering City University of Hong KongHong Kong 999077China Department of Biological Physics Eötvös UniversityBudapest 1117Hungary MOE Key Laboratory for Intelligent Networks and Network Security School of Automation Science and EngineeringXi’an Jiaotong UniversityXi’an 710049China

Hierarchical networks are frequently encountered in animal groups,gene networks,and artificial engineering systems such as multiple robots,unmanned vehicle systems,smart grids,wind farm networks,and so *** structure of a large directed hierarchical network is often strongly influenced by reverse edges from lower-to higher-level nodes,such as lagging birds’howl in a flock or the opinions of lowerlevel individuals feeding back to higher-level ones in a social *** study reveals that,for most large-scale real hierarchical networks,the majority of the reverse edges do not affect the synchronization process of the entire network;the synchronization process is influenced only by a small part of these reverse edges along specific *** surprisingly,a single effective reverse edge can slow down the synchronization of a huge hierarchical network by over 60%.The effect of such edges depends not on the network size but only on the average in-degree of the involved *** overwhelming majority of active reverse edges turn out to have some kind of“bunching”effect on the information flows of hierarchical networks,which slows down synchronization *** finding refines the current understanding of the role of reverse edges in many natural,social,and engineering hierarchical networks,which might be beneficial for precisely tuning the synchronization rhythms of these *** study also proposes an effective way to attack a hierarchical network by adding a malicious reverse edge to it and provides some guidance for protecting a network by screening out the specific small proportion of vulnerable nodes.

关键词： Synchronizability Large hierarchical networks Reverse edges Information flows Complex networks

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Achieving Distributed and Privacy-Preserving Cross-Chain Transactions in Account-Model Blockchain Systems

Achieving Distributed and Privacy-Preserving Cross-Chain Tra...

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2023 IEEE International Conference on Metaverse Computing, Networking and Applications, MetaCom 2023

作者： Zhang, Chuan Wang, Weijie Zhang, Weiting Nie, Jiangtian Liang, Jinwen Zhu, Liehuang Beijing Institute of Technology School of Cyberspace Science and Technology Beijing China Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies Guangdong China Beijing Institute of Technology School of Computer Science & Technology Beijing China Beijing Jiaotong University School of Electronic and Information Engineering Beijing China Nanyang Technological University School of Computer Science and Engineering Singapore Hong Kong Polytechnic University Department of Computing Hong Kong

ISBN: (纸本)9798350333336

Cross-Chain is an emerging technology to enable transaction circulation across different blockchain systems, breaking down transaction isolation among decentralized ecosystems. Existing cross-chain solutions are often constructed based on centralized trusted third parties, which introduce additional threats to users' identities due to potentially compromised risks on the centralized third parties. To exclude the single-point compromised risk in centralized systems, this paper focuses on a fully decentralized scenario and develops a distributed cross-chain transaction scheme, which enables cross-chain transaction exchanges while ensuring the unlinkability between payees and payers. Specifically, we first propose a cross-chain cryptocurrency exchange scheme by leveraging Ethereum's smart contracts, which achieves transaction exchanges in decentralized settings. Then, we leverage zero-knowledge succinct non-interactive argument of knowledge (i.e., zk-SNARKs) to explore a privacy-preserving method for cross-chain transactions in account-model blockchain systems, such that the unlinkability between payees and payers and the privacy of cross-chain participants can be guaranteed. Security analysis and experimental evaluations demonstrate that the proposed scheme achieves the security goal at acceptable costs. © 2023 IEEE.

关键词： Smart contract

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Smart Cricket Ball: Solutions to Design and Deployment Challenges 6th

Smart Cricket Ball: Solutions to Design and Deployment Chall...

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6th International Conference on Innovative Computing and Communication, ICICC 2023

作者： Balbudhe, Pravin Sharma, Rika Solanki, Sachin Department of Computer Science and Engineering Amity School of Engineering and Technology Amity University Raipur Chhattisgarh Raipur India Directorate of Technical Education Government Polytechnic Campus Maharashtra Sadar Nagpur India

ISBN: (纸本)9789819940707

Cricket is the most played and accepted game in the Asian region of the world. In any game decision-making affecting the result plays a major role, which has to be accurate in every aspect to conclude the fair game. This matter is a live cricket match or even in training sessions. To date, decision-making was dependent on visual observation by the expert umpire. These manual observations of results may be inaccurate at some point and based on the experience and expertise of the umpire. With the rapid advancement and technological involvement in gaming industries, electronic gadgets are helping the player to enhance the performance and accuracy of results. This paper deals with the challenges and the possible solutions involved in designing and building a smart cricket ball, which will be capable to calculate and share the ball’s activity log. This log will involve the direction, speed, type, trajectory, spin, deviation angle, and impact triggers. It is difficult to get all information from a single type of sensor or module, this work suggests creating the fusion of multiple sensors and software algorithms for accurate measurements. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Decision making

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Design and construction of electronic transport layer based on organic small molecule for inverted perovskite solar cells

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Materials Research Bulletin 2025年 189卷

作者： Li, Qingbin Zhang, Cen Xue, Lingwei Wang, Binbin Lv, Yueyue Yan, Qingzhi School of Chemical and Environmental Engineering Pingdingshan University Henan Pingdingshan467000 China School of Materials Science and Engineering Henan Polytechnic University Henan Jiaozuo454000 China Institute of Nuclear Materials School of Materials Science and Engineering University of Science and Technology Beijing Beijing100083 China College of Material Science and Engineering Beijing University of Chemical Technology Beijing100029 China

An effective way to prepare efficient and stable organic electronic transport layer (ETL) to solve the problems such as interface charge recombination, electrons extraction and transport, and poor interface contact of perovskite solar cells (PSCs). Here, a small molecule, AQX-OCH2CF3, termed AQF, is designed, synthesized, and incorporated into [6,6]-Phenyl C61-butyric acid methyl ester (PCBM) as ETL for the fabrication of inverted PSCs. Multiple experimental tests confirm that AQF can effectively inhibit the charge recombination, optimize the electrons extraction and transport, and improve contact between ETL and perovskite layer. Consequently, the PSCs with PCBM: AQF as ETL attain a significant power conversion efficiency (PCE) of 18.61 %, accompanied by a small hysteresis effect. The devices retain >90 % of their initial PCEs after over 1000 h operating at maximum power point under one sun illumination in moist air atmosphere. This study provides a simple and effective method to improve efficiency and stability. © 2025 Elsevier Ltd

关键词： Perovskite solar cells

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Cross-modal representation flattening for multi-modal domain generalization 24

Cross-modal representation flattening for multi-modal domain...

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Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Yunfeng Fan Wenchao Xu Haohao Wang Song Guo Department of Computing The Hong Kong Polytechnic University School of Computer Science and Technology Huazhong University of Science and Technology Hong Kong University of Science and Technology

ISBN: (纸本)9798331314385

Multi-modal domain generalization (MMDG) requires that models trained on multimodal source domains can generalize to unseen target distributions with the same modality set. Sharpness-aware minimization (SAM) is an effective technique for traditional uni-modal domain generalization (DG), however, with limited improvement in MMDG. In this paper, we identify that modality competition and discrepant uni-modal flatness are two main factors that restrict multi-modal generalization. To overcome these challenges, we propose to construct consistent flat loss regions and enhance knowledge exploitation for each modality via cross-modal knowledge transfer. Firstly, we turn to the optimization on representation-space loss landscapes instead of traditional parameter space, which allows us to build connections between modalities directly. Then, we introduce a novel method to flatten the high-loss region between minima from different modalities by interpolating mixed multi-modal representations. We implement this method by distilling and optimizing generalizable interpolated representations and assigning distinct weights for each modality considering their divergent generalization capabilities. Extensive experiments are performed on two benchmark datasets, EPIC-Kitchens and Human-Animal-Cartoon (HAC), with various modality combinations, demonstrating the effectiveness of our method under multi-source and single-source settings. Our code is open-sourced https://***/fanyunfeng-bit/Cross-modal-Representation-Flattening-for-MMDG.

关键词：

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A Review on AI-powered Advancements in Climate Finance and its Impact 18

A Review on AI-powered Advancements in Climate Finance and i...

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18th INDIAcom;11th International Conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Pandow, Bilal Ahmad Ganai, Khurshid Ali Hussain, Gousiya School of Business and Logistics Bahrain Polytechnic Manama Bahrain Higher Colleges of Technology Dept. of Business Dubai United Arab Emirates Mewar University Department of Computer Science Chittorgarh India

ISBN: (纸本)9789380544519

As humanity works progressively to address climate change, the combination of artificial intelligence (AI) and climate financing offers a hopeful path for significant progress. The objective of this project is to examine the strategic implementation of AI technology to improve many areas of climate financing. This research evaluates the capacity of AI algorithms to streamline and automate operations in climate financing organizations, resulting in improved operational efficiency and decreased administrative costs. Furthermore, we have examined the possible uses of AI-driven algorithmic trading in the realm of environmentally-friendly finance. We have assessed its influence on market behavior, the availability of funds, and the distribution of resources towards sustainable investments. In addition, we examine the ethical and regulatory factors related to the implementation of AI in this particular setting. The study examines the influence of algorithmic trading on green finance, with a focus on potential opportunities for collaboration between the public and private sectors. This research offers useful insights into utilizing AI technology to tackle climate-related concerns and promote sustainability in financial decision-making, with a specific emphasis on practical applications. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： Artificial Intelligence Climate Change Climate Finance sustainable investments

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Can Individuals be Repeatedly Selected for Mutation in Matrix-Based DE? A Comparative Study 11

Can Individuals be Repeatedly Selected for Mutation in Matri...

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11th International Conference on Machine Intelligence Theory and Applications, MiTA 2024

作者： Wei, Ling-Ling Sun, Bing Li, Jian-Yu Yang, Qiang Xu, Jing Tang, Fei-Yi South China Normal University School of Computer Science Guangzhou510631 China Nankai University College of Artificial Intelligence Tianjin300350 China Nanjing University of Information Science and Technology School of Artificial Intelligence Jiangsu China Guangzhou Panyu Polytechnic Pazhou Lab School of Information Engineering Guangdong China

ISBN: (纸本)9798350385670

Evolutionary Computation (EC) is a class of algorithms derived from the simulation of natural phenomena, which faces the challenges of long running times and high computing loads resulting from large-scale problems. For this reason, the matrix-based EC (MEC) has been presented as an extension of classic EC algorithms to address large-scale optimization. The MEC can be implemented directly on high-performance computing resources, thus accelerating the computation of evolutionary operators. However, MEC is still in its infancy and lacks deeper analysis. Hence, this paper analyzes and investigates matrix-based differential evolution (MDE) and advances the development of related research through theoretical analysis and experimental validation, which has two contributions. First, through the comprehensive comparison of MDE and DE in different problems, we compare the solution quality and computational speed of MDE and DE, and show that the solution quality of MDE is not significantly different from that of DE, but the computational speed of MDE is much faster than that of DE. Second, we also further analyze the mutation mechanism of MDE, focusing on the effect of the repeatability of individuals in the mutation process on the performance of the algorithms, which provides a basis for future research on MDE of MEC. © 2024 IEEE.

关键词： differential evolution Evolutionary computation matrix-based evolutionary computation parallel computing

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