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Theoretical and Computational Chemistry

Working Paper

Heterogeneous Catalysts in Grammar School

Johannes T. Margraf, Zachary W. Ulissi, Yousung Jung, Karsten Reuter

Version 1 posted 13 December 2021

578

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Theoretical and Computational Chemistry

Working Paper

Size-Extensive Molecular Machine Learning with Global Descriptors

Hyunwook Jung, Sina Stocker, Christian Kunkel, Harald Oberhofer, Byungchan Han, Karsten Reuter, Johannes T. Margraf

Version 1 posted 22 October 2019

841

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1

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Theoretical and Computational Chemistry

Working Paper

Machine-Learning Coupled Cluster Properties through a Density Tensor Representation

Benjamin Peyton, Connor Briggs, Ruhee D'Cunha, Johannes T. Margraf, Thomas Crawford

Version 1 posted 02 April 2020

686

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Theoretical and Computational Chemistry

Working Paper

Towards Density Functional Approximations from Coupled Cluster Correlation Energy Densities

Johannes T. Margraf, Christian Kunkel, Karsten Reuter

Version 2 posted 30 April 2019

1,185

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Theoretical and Computational Chemistry

Working Paper

Learning to Use the Force: Fitting Repulsive Potentials in Density-Functional Tight-Binding with Gaussian Process Regression

Chiara Panosetti, Artur Engelmann, Lydia Nemec, Karsten Reuter, Johannes T. Margraf

Version 1 posted 02 October 2019

1,115

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Theoretical and Computational Chemistry

Working Paper

Small Basis Set Density Functional Theory Method for Cost-efficient, Large-scale Condensed Matter Simulations

Elisabeth Keller, Jack Morgenstein, Karsten Reuter, Johannes T. Margraf

Version 1 posted 20 June 2024

187

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Theoretical and Computational Chemistry

Working Paper

Obtaining Robust Density Functional Tight Binding Parameters for Solids Across the Periodic Table

Mengnan Cui, Karsten Reuter, Johannes T. Margraf

Version 1 posted 23 February 2024

418

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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

1,304

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Theoretical and Computational Chemistry

Working Paper

Physics-Inspired Machine Learning of Localized Intensive Properties

Ke Chen, Christian Kunkel, Bingqing Cheng, Karsten Reuter, Johannes T. Margraf

Version 1 posted 21 February 2023

465

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Theoretical and Computational Chemistry

Working Paper

Estimating Free Energy Barriers for Heterogeneous Catalytic Reactions with Machine Learning Potentials and Umbrella Integration

Sina Stocker, Hyunwook Jung, Gábor Csányi, C. Franklin Goldsmith, Karsten Reuter, Johannes T. Margraf

Version 1 posted 30 May 2023

684

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Refine Search

23 results in Johannes T. Margraf in Authors: Johannes T. Margraf

Heterogeneous Catalysts in Grammar School

Size-Extensive Molecular Machine Learning with Global Descriptors

Machine-Learning Coupled Cluster Properties through a Density Tensor Representation

Towards Density Functional Approximations from Coupled Cluster Correlation Energy Densities

Learning to Use the Force: Fitting Repulsive Potentials in Density-Functional Tight-Binding with Gaussian Process Regression

Small Basis Set Density Functional Theory Method for Cost-efficient, Large-scale Condensed Matter Simulations

Obtaining Robust Density Functional Tight Binding Parameters for Solids Across the Periodic Table

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

Physics-Inspired Machine Learning of Localized Intensive Properties

Estimating Free Energy Barriers for Heterogeneous Catalytic Reactions with Machine Learning Potentials and Umbrella Integration

23 results in Authors: Johannes T. Margraf