Researchers have developed a groundbreaking Helmholtz free energy equation of state (EoS) for modeling fluid and solid phases using artificial neural networks (ANNs). This approach bridges the gap between molecular simulations and macroscopic thermodynamic properties, providing a consistent framework to describe phase behavior across vapor, liquid, and solid states. By leveraging ANNs trained on molecular dynamics data, the model predicts key features like metastable regions, phase equilibria, and critical points without relying on predefined equations. Demonstrated for systems using the Mie potential, the method offers a significant step toward unified thermodynamic modeling, with potential applications in chemical engineering, materials science, and process design.
For more details, please continue reading the full article under the following link:
https://www.nature.com/articles/s42005-024-01892-3
In general, if you enjoy reading this kind of scientific news articles, I am always keen to connect with fellow researchers in materials science, including the possibility to discuss about any potential interest in the Materials Square cloud-based online platform ( www.matsq.com ), designed for streamlining the execution of materials and molecular modelling simulations!
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Many thanks for your interest and consideration,
Dr. Gabriele Mogni
Technical Consultant and EU Representative of Virtual Lab Inc., the parent company of the Materials Square platform
Website: Home | Virtual Lab Inc.
Email: gabriele@simulation.re.kr
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