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RESEARCH PAPER · Chinese Journal of Chemical Physics · 2021

Crystallographic groups prediction from chemical composition via deep learning

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Crystallographic groups prediction from chemical composition via deep learningOriginalBand-Edge Prediction of 2D Covalent Organic Frameworks from Molecular Precursor via Machine Learning27Crystal system and space group prediction of two-dimensional materials from chemical formula via deep neural networks6Chemistry for Space Group Symmetry beyond Crystals2Machine learning prediction of materials properties from chemical composition: Status and prospects29Space group informed transformer for crystalline materials generation28

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  1. Band-Edge Prediction of 2D Covalent Organic Frameworks from Molecular Precursor via Machine Learning

    The Journal of Physical Chemistry Letters · 2023-07-21

    Dayong Wang, Haifeng Lv, Yangyang Wan, Xiaojun Wu, Jinlong Yang

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  2. Crystal system and space group prediction of two-dimensional materials from chemical formula via deep neural networks

    Materials Today Chemistry · 2023-08-08

    Yixuan Che, Dan Wang, Haifeng Lv, Xiaojun Wu

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  3. Chemistry for Space Group Symmetry beyond Crystals

    Symmetry · 2024-03-07

    Takashiro Akitsu, Yuya Higashi, Rin Tsuchiya, Taiga Imae, Keishiro Komatsu, Daisuke Nakane, Dohyun Moon

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  4. Machine learning prediction of materials properties from chemical composition: Status and prospects

    Chemical Physics Reviews · 2024-12-01

    Mohammed Alghadeer, Nufida D. Aisyah, Mahmoud Hezam, Saad M. Alqahtani, Ahmer A.B. Baloch, Fahhad H. Alharbi

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  5. Space group informed transformer for crystalline materials generation

    中国科学通报:英文版 · 2025-09-25

    Zhendong Cao, Xiaoshan Luo, Jian Lv, Lei Wang

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