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Deep learning-driven evaluation and prediction of ion-doped NASICON materials for enhanced solid-state battery performance Journal article
Zhao, Zirui, Wang, Xiaoke, Wu, Si, Zhou, Pengfei, Zhao, Qian, Xu, Guanping, Sun, Kaitong, Li, Hai Feng. Deep learning-driven evaluation and prediction of ion-doped NASICON materials for enhanced solid-state battery performance[J]. AAPPS Bulletin, 2024, 34(1), 26.
Authors:  Zhao, Zirui;  Wang, Xiaoke;  Wu, Si;  Zhou, Pengfei;  Zhao, Qian; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0 | Submit date：2024/10/10
Deep Learning Model  Electrochemical Properties  Ion Doping  Nasicon  Solid-state Electrolyte  
FedGCS: A Generative Framework for Effcient Client Selection in Federated Learning via Gradient-based Optimization Conference paper
ZHIYUAN NING, CHUNLIN TIAN, MENG XIAO, WEI FAN, PENGYANG WANG, LI LI, PENGFEI WANG, YUANCHUN ZHOU. FedGCS: A Generative Framework for Effcient Client Selection in Federated Learning via Gradient-based Optimization[C], 2024.
Authors:  ZHIYUAN NING;  CHUNLIN TIAN;  MENG XIAO;  WEI FAN;  PENGYANG WANG; et al.
Favorite |  | Submit date：2024/08/28
Make Graph Neural Networks Great Again: A Generic Integration Paradigm of Topology-Free Patterns for Traffc Speed Prediction Conference paper
YICHENG ZHOU, PENGFEI WANG, HAO DONG, DENGHUI ZHANG, DINGQI YANG, YANJIE FU, WANG PENGYANG. Make Graph Neural Networks Great Again: A Generic Integration Paradigm of Topology-Free Patterns for Traffc Speed Prediction[C], 2024.
Authors:  YICHENG ZHOU;  PENGFEI WANG;  HAO DONG;  DENGHUI ZHANG;  DINGQI YANG; et al.
Favorite |  | Submit date：2024/08/28
FedGSC: A Generative Framework for Efficient Client Selection in Federated Learning Conference paper
Zhiyuan Ning, Chunlin Tian, Meng Xiao, Wei Fan, Pengyang Wang, Li Li, Pengfei Wang, Yuanchun Zhou. FedGSC: A Generative Framework for Efficient Client Selection in Federated Learning[C], 2024.
Authors:  Zhiyuan Ning;  Chunlin Tian;  Meng Xiao;  Wei Fan;  Pengyang Wang; et al.
Favorite |  | Submit date：2024/08/29
Triggering efficient reconstructions of Co/Fe dual-metal incorporated Ni hydroxide by phosphate additives for electrochemical hydrogen and oxygen evolutions Journal article
Feng, Jinxian, Qiao, Lulu, Liu, Chunfa, Zhou, Pengfei, Feng, Wenlin, Pan, Hui. Triggering efficient reconstructions of Co/Fe dual-metal incorporated Ni hydroxide by phosphate additives for electrochemical hydrogen and oxygen evolutions[J]. Journal of Colloid and Interface Science, 2024, 657, 705-715.
Authors:  Feng, Jinxian;  Qiao, Lulu;  Liu, Chunfa;  Zhou, Pengfei;  Feng, Wenlin; et al.
Favorite | TC[WOS]:2 TC[Scopus]:2  IF:9.4/8.2 | Submit date：2024/04/02
Alkali Water Electrolysis  Incorporated Ni Hydroxide  Phosphate Additives  Surface Reconstruction  
Temporal inductive path neural network for temporal knowledge graph reasoning Journal article
Dong, Hao, Wang, Pengyang, Xiao, Meng, Ning, Zhiyuan, Wang, Pengfei, Zhou, Yuanchun. Temporal inductive path neural network for temporal knowledge graph reasoning[J]. Artificial Intelligence, 2024, 329, 104085.
Authors:  ; et al.
Favorite | TC[WOS]:3 TC[Scopus]:6  IF:5.1/4.8 | Submit date：2024/05/02
Graph Neural Networks  Knowledge Graph Reasoning  Temporal Knowledge Graph  Temporal Reasoning  
In situ generated α-Co(OH)2/Co3Mo derived from Co-Mo-N for enhanced electrochemical hydrogen evolution reaction Journal article
Zhou, Pengfei, Liu, Xuncheng, Ge, Xiang, Feng, Jinxian. In situ generated α-Co(OH)2/Co3Mo derived from Co-Mo-N for enhanced electrochemical hydrogen evolution reaction[J]. Journal of Materials Chemistry A, 2024.
Authors:  Zhou, Pengfei;  Liu, Xuncheng;  Ge, Xiang;  Feng, Jinxian
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:10.7/10.8 | Submit date：2024/09/03
Make Graph Neural Networks Great Again: A Generic Integration Paradigm of Topology-Free Patterns for Traffic Speed Prediction Conference paper
Zhou, Yicheng, Wang, Pengfei, Dong, Hao, Zhang, Denghui, Yang, Dingqi, Fu, Yanjie, Wang, Pengyang. Make Graph Neural Networks Great Again: A Generic Integration Paradigm of Topology-Free Patterns for Traffic Speed Prediction[C]:International Joint Conferences on Artificial Intelligence, 2024, 2607-2615.
Authors:  Zhou, Yicheng;  Wang, Pengfei;  Dong, Hao;  Zhang, Denghui;  Yang, Dingqi; et al.
Favorite | TC[Scopus]:0 | Submit date：2024/10/10
Data Mining  
Nickel-facilitated in-situ surface reconstruction on spinel Co3O4 for enhanced electrochemical nitrate reduction to ammonia Journal article
Qiao, Lulu, Liu, Di, Zhu, Anquan, Feng, Jinxian, Zhou, Pengfei, Liu, Chunfa, Ng, Kar Wei, Pan, Hui. Nickel-facilitated in-situ surface reconstruction on spinel Co3O4 for enhanced electrochemical nitrate reduction to ammonia[J]. Applied Catalysis B: Environmental, 2024, 340, 123219.
Authors:  Qiao, Lulu;  Liu, Di;  Zhu, Anquan;  Feng, Jinxian;  Zhou, Pengfei; et al.
Favorite | TC[WOS]:26 TC[Scopus]:29  IF:20.2/18.9 | Submit date：2024/02/22
Electrochemical Nitrate Reduction Reaction (E-no3rr)  Ni-incorporation  Spinel Co3o4  Surface Reconstruction  
FedGCS: A Generative Framework for Efficient Client Selection in Federated Learning via Gradient-based Optimization Conference paper
Ning, Zhiyuan, Tian, Chunlin, Xiao, Meng, Fan, Wei, Wang, Pengyang, Li, Li, Wang, Pengfei, Zhou, Yuanchun. FedGCS: A Generative Framework for Efficient Client Selection in Federated Learning via Gradient-based Optimization[C]:International Joint Conferences on Artificial Intelligence, 2024, 4760-4768.
Authors:  Ning, Zhiyuan;  Tian, Chunlin;  Xiao, Meng;  Fan, Wei;  Wang, Pengyang; et al.
Favorite | TC[Scopus]:0 | Submit date：2024/10/10
Machine Learning  Data Mining