Gaussian Process Regression for Mapping Free EnergyLandscape of Mg<sup>2+</sup>-Cl<sup>−</sup> Ion Pairing in Aqueous Solution: Molecular Insights and Computational Efficiency

Gaussian Process Regression for Mapping Free EnergyLandscape of Mg<sup>2+</sup>-Cl<sup>−</sup> Ion Pairing in Aqueous Solution: Molecular Insights and Computational Efficiency

Free energy landscapes are pivotal for understanding molecular interactions in solution, yet their reconstruction in complex systems remains computationally demanding. In this study, we integrated Gaussian process regression (GPR) with well-tempered metadynamics (WT-MTD) to efficiently map the free...

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Bibliographic Details
Main Author: Wasut Pornpatcharapong
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Molecules
Subjects:
machine learning
GPR
molecular dynamics
free energy
metadynamics
enhanced sampling
Online Access:https://www.mdpi.com/1420-3049/30/12/2595
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