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Theoretical and Computational Chemistry

Working Paper

Machine-Learning-Driven Exploration of Surface Reconstructions of Reduced Rutile TiO2

Yonghyuk Lee, Xiaobo Chen, Sabrina Gericke, Meng Li, Dmitri Zakharov, Ashley Head, Judith Yang, Anastassia Alexandrova

Version 1 posted 20 December 2024

0

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Catalysis

Working Paper

An Automated Pynta-based Curriculum for ML-Accelerated Calculation of Transition States

Trevor Price, Saurabh Sivakumar, Matthew S. Johnson, Judit Zádor, Ambarish Kulkarni

Version 1 posted 25 November 2024

120

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Theoretical and Computational Chemistry

Working Paper

∆-Learning for Coarse-Grained Potentials

Aditi Khot, Brett Savoie

Version 1 posted 27 March 2023

521

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Theoretical and Computational Chemistry

Working Paper

Machine Learning Potentials for Metal-Organic Frameworks using an Incremental Learning Approach

Sander Vandenhaute, Maarten Cools-Ceuppens, Simon DeKeyser, Toon Verstraelen, Veronique Van Speybroeck

Version 1 posted 04 November 2022

833

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1

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Theoretical and Computational Chemistry

Working Paper

How Robust are Modern Graph Neural Network Potentials in Long and Hot Molecular Dynamics Simulations?

Sina Stocker, Johannes Gasteiger, Florian Becker, Stephan Günnemann, Johannes T. Margraf

Version 1 posted 01 April 2022

1,339

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1

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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

244

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Theoretical and Computational Chemistry

Working Paper

Active delta-learning for fast construction of interatomic potentials and stable molecular dynamics simulations

Yaohuang Huang, Yi-Fan Hou, Pavlo O. Dral

Version 1 posted 19 November 2024

163

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Theoretical and Computational Chemistry

Working Paper

Data-efficient modeling of catalytic reactions via enhanced sampling and on-the-fly learning of machine learning potentials

Simone Perego, Luigi Bonati

Version 2 posted 09 October 2024

1,217

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Theoretical and Computational Chemistry

Working Paper

Spatially resolved uncertainties for machine learning potentials

Esther Heid, Johannes Schörghuber, Ralf Wanzenböck, Georg. K. H. Madsen

Version 2 posted 02 August 2024

431

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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

751

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3

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Refine Search

22 results in Machine Learning Potentials in Keywords: Machine Learning Potentials

Machine-Learning-Driven Exploration of Surface Reconstructions of Reduced Rutile TiO2

An Automated Pynta-based Curriculum for ML-Accelerated Calculation of Transition States

∆-Learning for Coarse-Grained Potentials

Machine Learning Potentials for Metal-Organic Frameworks using an Incremental Learning Approach

How Robust are Modern Graph Neural Network Potentials in Long and Hot Molecular Dynamics Simulations?

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

Active delta-learning for fast construction of interatomic potentials and stable molecular dynamics simulations

Data-efficient modeling of catalytic reactions via enhanced sampling and on-the-fly learning of machine learning potentials

Spatially resolved uncertainties for machine learning potentials

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

22 results in Keywords: Machine Learning Potentials