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A review of GEMC method and its improved algorithms

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Abstract

Gibbs Ensemble Monte Carlo (GEMC) is a molecular simulation method commonly used for simulating phase equilibrium. This method has been proposed since 1987 and applied in many fields, such as geology, planetary science, chemical engineering, material science, etc. GEMC method combines canonical (NVT), isobaric-isothermal (NPT), and grand canonical (μVT) Monte Carlo techniques in a single simulation. The GEMC method was developed on the fundamental law of phase equilibrium that chemical potentials of each phase all equal. Two key factors affect the rationality and reliability of GEMC simulations: 1. particles can be efficiently moved in/out from certain phase during simulation; 2. samplings can represent the whole system well, in other words, samplings hold good ergodicity. In addition, various parallel methods have been developed to improve the simulation efficiency. In this review, an introduction to the theoretical fundamentals, improvements on particle movement and sampling protocols, acceleration techniques and some applications of the GEMC method will be presented. This is the first integrated review introducing the fundamentals, improvements and applications of the GEMC simulation method.

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Acknowledgements

This work was supported by Chinese NSF projects (42130114) and the strategic priority research program (B) of CAS (XD841000000), pre research Project on Civil Aerospace Technologies No. D020202 funded by Chinese National Space Administration (CNSA).

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Authors and Affiliations

  1. International Research Center for Planetary Science, Chengdu University of Technology, Chengdu, 610059, China

    Liwen Zhang, Yuhong Yang, Kun Yin & Yun Liu

  2. State Key Laboratory of Ore Deposit Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang, 550081, China

    Yun Liu

  3. CAS Center for Excellence in Comparative Planetology, Hefei, 230026, China

    Yun Liu

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Zhang, L., Yang, Y., Yin, K. et al. A review of GEMC method and its improved algorithms. Acta Geochim 42, 409–434 (2023). https://doi.org/10.1007/s11631-023-00603-z

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