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RESEARCH PAPER · npj Computational Materials · 2023

A structure translation model for crystal compounds

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9 direct citing papers in this saved network. Explore the next layer with second-order citations.

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A structure translation model for crystal compoundsOriginalPACMAN: A Robust Partial Atomic Charge Predicter for Nanoporous Materials Based on Crystal Graph Convolution Networks48Scalable crystal structure relaxation using an iteration-free deep generative model with uncertainty quantification30Machine learning descriptors for crystal materials: applications in Ni-rich layered cathode and lithium anode materials for high-energy-density lithium batteries20Deep learning-assisted methods for accelerating the intelligent screening of novel 2D materials: New perspectives focusing on data collection and description6Accelerating structure relaxation in chemically disordered materials with a chemistry-driven model3Advanced strategies to boost sustainable high-rate Ni-rich cathodes toward durable LIBs14Traj2Relax: A Trajectory-Supervised Method for Robust Structure Relaxation0A Comprehensive Review of the Computational Approaches for Structure–Property Prediction of High Entropy Materials0DeGAT: A Dual-Expert Graph Attention Network for Partial Charge Prediction in Metal–Organic Frameworks0

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  1. PACMAN: A Robust Partial Atomic Charge Predicter for Nanoporous Materials Based on Crystal Graph Convolution Networks

    Journal of Chemical Theory and Computation · 2024-06-01

    Guobin Zhao, Yongchul G. Chung

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  2. Scalable crystal structure relaxation using an iteration-free deep generative model with uncertainty quantification

    Nature Communications · 2024-09-17

    Ziduo Yang, Yi-Ming Zhao, Xian Wang, Xiaoqing Liu, Xiuying Zhang, Yifan Li, Qiujie Lv, Calvin Yu‐Chian Chen, Lei Shen

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  3. Machine learning descriptors for crystal materials: applications in Ni-rich layered cathode and lithium anode materials for high-energy-density lithium batteries

    Journal of Materials Informatics · 2024-10-28

    Ruiqi Zhang, Fangchao Rong, Genming Lai, Guangfeng Wu, Yaokun Ye, Jiaxin Zheng

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  4. Deep learning-assisted methods for accelerating the intelligent screening of novel 2D materials: New perspectives focusing on data collection and description

    Coordination Chemistry Reviews · 2025-01-16

    Yuandong Lin, Ji Ma, Yong‐Guang Jia, Chongchong Yu, Jun‐Hu Cheng

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  5. Accelerating structure relaxation in chemically disordered materials with a chemistry-driven model

    npj Computational Materials · 2025-07-14

    Liying An, Huan Ma, Jinjia Liu, Wenping Guo, Xiaodong Wen

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  6. Advanced strategies to boost sustainable high-rate Ni-rich cathodes toward durable LIBs

    Progress in Materials Science · 2025-09-08

    Parnaz Asghari, Farshad Boorboor Ajdari, Fereshteh Abbasi, Sasan Rostami, Ali Asghar Sadeghi Ghazvini, Ali Molaei Aghdam

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  7. Traj2Relax: A Trajectory-Supervised Method for Robust Structure Relaxation

    Journal of Chemical Information and Modeling · 2026-01-30

    Zhiyuan Liu, Quan QIAN

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  8. A Comprehensive Review of the Computational Approaches for Structure–Property Prediction of High Entropy Materials

    High Entropy Alloys & Materials · 2026-03-01

    Suman Chabri, G. Anand

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  9. DeGAT: A Dual-Expert Graph Attention Network for Partial Charge Prediction in Metal–Organic Frameworks

    Journal of Chemical Theory and Computation · 2026-08-10

    Yanhui Sun, Zeheng Yu, Yuhua Dong, Ming Gong, Yongchao Hao, Shupeng Sun

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