Modeling Porous Liquids with Machine-Learning-Assisted Molecular Dynamics

Modeling Porous Liquids with Machine-Learning-Assisted Molecular Dynamics

<p dir="ltr">Diverse applications benefit from porous materials, such as molecular separations and catalysis, enabling the efficient capture of greenhouse gases (CO<sub>2</sub> and CH<sub>4</sub>) and valuable noble gases (Xe, Ar, and Kr). Xenon, widely used i...

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Bibliographic Details
Main Author: Ouail Zakary (19740229) (author)
Other Authors: Perttu Lantto (19740246) (author)
Published: 2024
Subjects:
Computational chemistry
Theoretical quantum chemistry
Deep learning
Neural networks
Xenon NMR
Graph Neural Networks (GNNs)
Density Functional Theory B 3LYP method
Molecular Dynamics Simulations
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