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Theoretical and Computational Chemistry

Working Paper

Modeling Chemical Processes in Explicit Solvents with Machine Learning Potentials

Hanwen Zhang, Veronika Juraskova, Fernanda Duarte

Version 2 posted 08 July 2024

1,521

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1

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Theoretical and Computational Chemistry

Working Paper

emle-engine: a flexible electrostatic machine learning embedding package for multiscale molecular dynamics simulations

Kirill Zinovjev, Lester Hedges, Rubén Montagud Andreu, Christopher Woods, Iñaki Tuñón, Marc W. van der Kamp

Version 2 posted 27 February 2024

682

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Theoretical and Computational Chemistry

Working Paper

Modelling ligand exchange in metal complexes with machine learning potentials

Veronika Juraskova, Gers Tusha, Hanwen Zhang, Lars Schäfer, Fernanda Duarte

Version 1 posted 28 June 2024

455

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Theoretical and Computational Chemistry

Working Paper

The interplay of solvation and polarization effects on ion pairing in nanoconfined electrolytes

Kara Fong, Barbara Sumic, Niamh O'Neill, Christoph Schran, Clare Grey, Angelos Michaelides

Version 1 posted 21 February 2024

779

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Materials Science

Working Paper

Germanium Distributions in Zeolites Derived from Neural Network Potentials.

Indranil Saha, Andreas Erlebach, Petr Nachtigall, Christopher J. Heard, Lukáš Grajciar

Version 1 posted 19 June 2024

148

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Organometallic Chemistry

Working Paper

Morphology of Lithium Halides in Tetrahydrofuran from Molecular Dynamics with Machine Learning Potentials

Marinella de Giovanetti, Sondre H. Hopen Eliasson, Sigbjørn Løland Bore, Odile Eisenstein, Michele Cascella

Version 2 posted 08 November 2024

205

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Theoretical and Computational Chemistry

Working Paper

Active learning meets metadynamics: Automated workflow for reactive machine learning potentials

Valdas Vitartas, Hanwen Zhang, Veronika Juraskova, Tristan Johnston-Wood, Fernanda Duarte

Version 1 posted 01 November 2024

550

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Materials Science

Working Paper

Machine Learning Committee Neural Network Potential Energy Surfaces for Two-Dimensional Metal-Organic Frameworks

Yuliang Shi, Farnaz A. Shakib

Version 1 posted 08 November 2024

113

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Materials Science

Working Paper

Quantifying the effect of Si/Al ratio on proton solvation and water diffusion in H-FAU using reactive neural network potential.

Indranil Saha, Andreas Erlebach, Petr Nachtigall, Christopher J. Heard, Lukáš Grajciar

Version 3 posted 12 July 2023

716

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3

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Materials Science

Working Paper

Gaussian Approximation Potentials for Accurate Thermal Properties of Two-Dimensional Materials

Tuğbey Kocabaş, Murat Keceli, Álvaro Vázquez-Mayagoitia, Cem Sevik

Version 1 posted 25 January 2023

540

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20 results in Machine learning potentials in Keywords: Machine learning potentials

Modeling Chemical Processes in Explicit Solvents with Machine Learning Potentials

emle-engine: a flexible electrostatic machine learning embedding package for multiscale molecular dynamics simulations

Modelling ligand exchange in metal complexes with machine learning potentials

The interplay of solvation and polarization effects on ion pairing in nanoconfined electrolytes

Germanium Distributions in Zeolites Derived from Neural Network Potentials.

Morphology of Lithium Halides in Tetrahydrofuran from Molecular Dynamics with Machine Learning Potentials

Active learning meets metadynamics: Automated workflow for reactive machine learning potentials

Machine Learning Committee Neural Network Potential Energy Surfaces for Two-Dimensional Metal-Organic Frameworks

Quantifying the effect of Si/Al ratio on proton solvation and water diffusion in H-FAU using reactive neural network potential.

Gaussian Approximation Potentials for Accurate Thermal Properties of Two-Dimensional Materials

20 results in Keywords: Machine learning potentials