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Theoretical and Computational Chemistry

Working Paper

Transferable Machine Learning Interatomic Potential for Bond Dissociation Energy Prediction of Drug-like Molecules

Elena Gelžinytė, Mario Öeren, Matthew D. Segall, Gábor Csányi

Version 2 posted 13 December 2023

493

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Theoretical and Computational Chemistry

Working Paper

Efficient molecular dynamics simulations of deep eutectic solvents with first-principles accuracy using machine learning interatomic potentials

Omid Shayestehpour, Stefan Zahn

Version 1 posted 24 August 2023

408

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Theoretical and Computational Chemistry

Working Paper

Accurate Free Energy Calculation via Multiscale Simulations Driven by Hybrid Machine Learning and Molecular Mechanics Potentials

Xujian Wang, Junmei Wang, Xiongwu Wu, Bernard Brooks

Version 1 posted 08 November 2024

293

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Materials Chemistry

Working Paper

Simulations enabled by machine learning potentials predict sulfide solid electrolyte with covalent network structure and glassy behavior

Gavin Winter, Nathan Walemba, Rafael Gómez-Bombarelli

Version 1 posted 16 July 2024

204

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Energy

Working Paper

Computational Design of Double-Layer Cathode Coatings in All-Solid-State Batteries

Chuhong Wang, Koutarou Aoyagi, Tim Mueller

Version 2 posted 29 September 2021

1,130

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Materials Science

Working Paper

Nature of the amorphous-amorphous interfaces in solid-state batteries revealed using machine-learned interatomic potentials

Chuhong Wang, Muratahan Aykol, Tim Mueller

Version 2 posted 17 July 2023

666

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1

Citations

Nanoscience

Working Paper

Accelerated Prediction of Atomically Precise Cluster Structures Using On-the-fly Machine Learning

Yunzhe Wang, Shanping Liu, Peter Lile, Sam Norwood, Alberto Hernandez, Sukriti Manna, Tim Mueller

Version 1 posted 20 August 2021

555

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Theoretical and Computational Chemistry

Working Paper

Accurate Ring Strain Energy Predictions with Machine Learning and Application in Strain-Promoted Reactions

Zhen Liu, Jessica Vinskus, Yue Fu, Peng Liu, Kevin Noonan, Olexandr Isayev

Version 1 posted 19 November 2024

80

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8 results in Machine Learning Interatomic Potential in Keywords: Machine Learning Interatomic Potential

Transferable Machine Learning Interatomic Potential for Bond Dissociation Energy Prediction of Drug-like Molecules

Efficient molecular dynamics simulations of deep eutectic solvents with first-principles accuracy using machine learning interatomic potentials

Accurate Free Energy Calculation via Multiscale Simulations Driven by Hybrid Machine Learning and Molecular Mechanics Potentials

Simulations enabled by machine learning potentials predict sulfide solid electrolyte with covalent network structure and glassy behavior

Computational Design of Double-Layer Cathode Coatings in All-Solid-State Batteries

Nature of the amorphous-amorphous interfaces in solid-state batteries revealed using machine-learned interatomic potentials

Accelerated Prediction of Atomically Precise Cluster Structures Using On-the-fly Machine Learning

Accurate Ring Strain Energy Predictions with Machine Learning and Application in Strain-Promoted Reactions

8 results in Keywords: Machine Learning Interatomic Potential