All Stories

  1. Developing a neural network machine learning interatomic potential for molecular dynamics simulations of La–Si–P systems

    Article • The Journal of Chemical Physics, August 2025, American Institute of Physics

    Weiyi Xia

  2. Accelerating the discovery of novel magnetic materials using machine learning–guided adaptive feedback

    Article • Proceedings of the National Academy of Sciences, November 2022, Proceedings of the National Academy of Sciences

    Weiyi Xia

  3. Molecular dynamics simulation of metallic Al–Ce liquids using a neural network machine learning interatomic potential

    Article • The Journal of Chemical Physics, November 2021, American Institute of Physics

    Weiyi Xia

  4. Theoretical prediction of a highly responsive material: Spin fluctuations and superconductivity in FeNiB2 system

    Article • Applied Physics Letters, October 2019, American Institute of Physics

    Yang Sun, Weiyi Xia

  5. Local structure origin of ultrafast crystallization driven by high-fidelity octahedral clusters in amorphous Sc0.2Sb2Te3

    Article • Applied Physics Letters, February 2019, American Institute of Physics

    Chong Qiao, Xiangshui MIAO, Weiyi Xia

  6. Temperature dependence of the solid-liquid interface free energy of Ni and Al from molecular dynamics simulation of nucleation

    Article • The Journal of Chemical Physics, November 2018, American Institute of Physics

    Yang Sun, Weiyi Xia

  7. Tuning Cd adsorption behaviours on graphene by introducing defects: a first-principles study

    Article • Materials Technology, March 2017, Taylor & Francis

    Weiyi Xia

  8. Metal intercalation-induced selective adatom mass transport on graphene

    Article • Nano Research, May 2016, Tsinghua University Press

    Weiyi Xia

  9. New stable Re–B phases for ultra-hard materials

    Article • Journal of Physics Condensed Matter, October 2014, Institute of Physics Publishing

    Weiyi Xia

  10. Structures and stabilities of alkaline earth metal peroxides XO2 (X = Ca, Be, Mg) studied by a genetic algorithm

    Article • RSC Advances, January 2013, Royal Society of Chemistry

    Weiyi Xia