Gaussian Process Regression for Mapping Free EnergyLandscape of Mg²⁺-Cl⁻ 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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Hlavní autor:	Wasut Pornpatcharapong
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2025-06-01
Edice:	Molecules
Témata:	machine learning GPR molecular dynamics free energy metadynamics enhanced sampling
On-line přístup:	https://www.mdpi.com/1420-3049/30/12/2595
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