Maximum Entropy-Mediated Liquid-to-Solid Nucleation and Transition

Molecular dynamics (MD) simulations are a powerful tool for studying matter at the atomic scale. However, to simulate solids, an initial atomic structure is crucial for the successful execution of MD simulations but can be difficult to prepare due to insufficient atomistic information. At the same time, wide-angle X-ray scattering (WAXS) measurements can determine the radial distribution function (RDF) of atomic structures. However, the interpretation of RDFs is often challenging. Here, we present an algorithm that can bias MD simulations with RDFs by combining the information on the MD atomic interaction potential and the RDF under the principle of maximum relative entropy. We show that this algorithm can be used to adjust the RDF of one liquid model, e.g., the TIP3P water model, to reproduce the RDF and improve the angular distribution function (ADF) of another model, such as the TIP4P/2005 water model. In addition, we demonstrate that the algorithm can initiate crystallization in liquid systems, leading to both stable and metastable crystalline states defined by the RDF, e.g., crystallization of water to ice and liquid TiO2 to rutile or anatase. Finally, we discuss how this method can be useful for improving interaction models, studying crystallization processes, interpreting measured RDFs, or training machine-learned potentials.

DDC Class

530.4: States of Matter

541.3: Physical Chemistry

006.3: Artificial Intelligence

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https://creativecommons.org/licenses/by/4.0/

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dammann-et-al-2025-maximum-entropy-mediated-liquid-to-solid-nucleation-and-transition.pdf

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Main Article

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5.52 MB

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Maximum Entropy-Mediated Liquid-to-Solid Nucleation and Transition