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Ab initio phase diagram and nucleation of gallium

Author

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  • Haiyang Niu

    (Northwestern Polytechnical University
    ETH Zurich c/o USI Campus
    Università della Svizzera italiana (USI))

  • Luigi Bonati

    (Università della Svizzera italiana (USI)
    ETH Zurich, c/o Università della Svizzera italiana)

  • Pablo M. Piaggi

    (ETH Zurich c/o USI Campus
    Università della Svizzera italiana (USI))

  • Michele Parrinello

    (ETH Zurich c/o USI Campus
    Università della Svizzera italiana (USI)
    Istituto Italiano di Tecnologia)

Abstract

Elemental gallium possesses several intriguing properties, such as a low melting point, a density anomaly and an electronic structure in which covalent and metallic features coexist. In order to simulate this complex system, we construct an ab initio quality interaction potential by training a neural network on a set of density functional theory calculations performed on configurations generated in multithermal–multibaric simulations. Here we show that the relative equilibrium between liquid gallium, α-Ga, β-Ga, and Ga-II is well described. The resulting phase diagram is in agreement with the experimental findings. The local structure of liquid gallium and its nucleation into α-Ga and β-Ga are studied. We find that the formation of metastable β-Ga is kinetically favored over the thermodinamically stable α-Ga. Finally, we provide insight into the experimental observations of extreme undercooling of liquid Ga.

Suggested Citation

  • Haiyang Niu & Luigi Bonati & Pablo M. Piaggi & Michele Parrinello, 2020. "Ab initio phase diagram and nucleation of gallium," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
  • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-16372-9
    DOI: 10.1038/s41467-020-16372-9
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    Cited by:

    1. Bo Lin & Jian Jiang & Xiao Cheng Zeng & Lei Li, 2023. "Temperature-pressure phase diagram of confined monolayer water/ice at first-principles accuracy with a machine-learning force field," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    2. Xingyuan San & Junwei Hu & Mingyi Chen & Haiyang Niu & Paul J. M. Smeets & Christos D. Malliakas & Jie Deng & Kunmo Koo & Roberto Reis & Vinayak P. Dravid & Xiaobing Hu, 2023. "Unlocking the mysterious polytypic features within vaterite CaCO3," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    3. Ang Gao & Richard C. Remsing, 2022. "Self-consistent determination of long-range electrostatics in neural network potentials," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    4. Mingfeng Liu & Jiantao Wang & Junwei Hu & Peitao Liu & Haiyang Niu & Xuexi Yan & Jiangxu Li & Haile Yan & Bo Yang & Yan Sun & Chunlin Chen & Georg Kresse & Liang Zuo & Xing-Qiu Chen, 2024. "Layer-by-layer phase transformation in Ti3O5 revealed by machine-learning molecular dynamics simulations," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    5. Jing Wu & E Zhou & An Huang & Hongbin Zhang & Ming Hu & Guangzhao Qin, 2024. "Deep-potential enabled multiscale simulation of gallium nitride devices on boron arsenide cooling substrates," Nature Communications, Nature, vol. 15(1), pages 1-9, December.

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