Maximum Entropy-Mediated Liquid-to-Solid Nucleation and Transition
Lars Dammann, Richard Kohns, Patrick Huber, Robert H. Meißner
TL;DR
This paper introduces a new algorithm that uses maximum entropy to adjust molecular dynamics simulations, enabling better modeling of liquid-to-solid transitions and improving atomic structure predictions.
Contribution
A novel algorithm that biases molecular dynamics simulations using radial distribution functions under maximum entropy principles to guide nucleation and transitions.
Findings
The algorithm successfully adjusts the radial distribution function of liquid models to match target models.
It can initiate crystallization in liquids, forming stable and metastable crystalline states.
The method is useful for improving interaction models and interpreting experimental data.
Abstract
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…
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Taxonomy
TopicsMaterial Dynamics and Properties · nanoparticles nucleation surface interactions · Phase Equilibria and Thermodynamics