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RESEARCH PAPER · Physical Review A · 2019

Classifying superheavy elements by machine learning

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42 direct citing works

Classifying superheavy elements by machine learningOriginalChemical Bonding and Bonding Models of Main-Group Compounds374Predicting charge density distribution of materials using a local-environment-based graph convolutional network65Machine learning reveals the importance of the formation enthalpy and atom-size difference in forming phases of high entropy alloys135Understanding Periodic and Non-periodic Chemistry in Periodic Tables43Local volume dimension: A novel approach for important nodes identification in complex networks8Screening Topological Quantum Materials for Na-Ion Battery Cathode25Phase and Microstructural Selection in High Entropy Materials1Phase Prediction in High Entropy Alloys by Various Machine Learning Modules Using Thermodynamic and Configurational Parameters71Materials genome engineering-based hydrogen storage materialsdatabase and its applications6Calibrating DFT Formation Enthalpy Calculations by Multifidelity Machine Learning43Machine learning classification of speckle patterns for roughness measurements9Predicting the ET(30) parameter of organic solvents via machine learning16

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  1. Chemical Bonding and Bonding Models of Main-Group Compounds

    Chemical Reviews · 2019-06-28

    Lili Zhao, Sudip Pan, Nicole Holzmann, Peter Schwerdtfeger, Gernot Frenking

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  2. Predicting charge density distribution of materials using a local-environment-based graph convolutional network

    Physical review. B./Physical review. B · 2019-11-07

    Sheng Rong Gong, Tian Xie, Taishan Zhu, Shuo Wang, Eric Fadel, Yawei Li, Jeffrey C. Grossman

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  3. Machine learning reveals the importance of the formation enthalpy and atom-size difference in forming phases of high entropy alloys

    Materials & Design · 2020-05-30

    Lei Zhang, Hongmei Chen, Xiaoma Tao, Hongguo Cai, Jingneng Liu, Yifang Ouyang, Qing Peng, Yong Du

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  4. Understanding Periodic and Non-periodic Chemistry in Periodic Tables

    Frontiers in Chemistry · 2021-01-06

    Changsu Cao, René E. Vernon, W. H. Eugen Schwarz, Jun Li

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  5. Local volume dimension: A novel approach for important nodes identification in complex networks

    International Journal of Modern Physics B · 2021-02-19

    Hanwen Li, Yong Sheng Deng

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  6. Screening Topological Quantum Materials for Na-Ion Battery Cathode

    ACS Materials Letters · 2021-12-17

    Wei Wu, Qiang Sun

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  7. Phase and Microstructural Selection in High Entropy Materials

    Materials horizons · 2022-01-01

    Krishanu Biswas, Nilesh Prakash Gurao, Tanmoy Maiti, Rajiv Sharan Mishra

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  8. Phase Prediction in High Entropy Alloys by Various Machine Learning Modules Using Thermodynamic and Configurational Parameters

    Metals and Materials International · 2022-06-09

    Pritam Mandal, Amitava Choudhury, Amitava Basu Mallick, Manojit Ghosh

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  9. Materials genome engineering-based hydrogen storage materialsdatabase and its applications

    Scientia Sinica Chimica · 2022-09-07

    Pengru Huang, Dan Cai, Huaizhou Lin, Jiaxi Liu, Ziyuan Li, Bin Li, Yongjin Zou, Hailiang Chu, Lixian Sun, Fen Xu

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  10. Calibrating DFT Formation Enthalpy Calculations by Multifidelity Machine Learning

    JACS Au · 2022-09-09

    Sheng Rong Gong, Shuo Wang, Tian Xie, Woo Hyun Chae, Runze Liu, Yang Shao‐Horn, Jeffrey C. Grossman

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  11. Machine learning classification of speckle patterns for roughness measurements

    Physics Letters A · 2023-03-07

    Vitória M. Castilho, W. F. Balthazar, Ladário da Silva, T.J.P. Penna, J. A. O. Huguenin

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  12. Predicting the ET(30) parameter of organic solvents via machine learning

    Chemical Physics Letters · 2023-06-15

    Vaneet Saini, Harsh Singh

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