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Theoretical and Computational Chemistry

Working Paper

Room-temperature stacking disorder in layered covalent-organic frameworks from machine-learning force fields

Ju Huang, Seung-Jae Shin, Kasper Tolborg, Alex Ganose, Gabriel Krenzer, Aron Walsh

Version 1 posted 24 March 2023

218

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Theoretical and Computational Chemistry

Working Paper

PairNet: Predicting Correlation Energies with Correlated Features

Zhihao Deng, Chang Liu, Haigang Lin, Yingsheng Zhang

Version 1 posted 03 April 2023

218

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Catalysis

Working Paper

Probing the role of acid site distribution on water structure in aluminosilicate zeolites: insights from molecular dynamics

Mingze Zheng, Brandon C. Bukowski

Version 3 posted 19 February 2024

396

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Theoretical and Computational Chemistry

Working Paper

Machine Learning Force Field Aided Cluster Expansion Approach to Configurationally Disordered Materials: Critical Assessment of Training Set Selection and Size Convergence

Jun-Zhong Xie, Xu-Yuan Zhou, Dong Luan, Hong Jiang

Version 1 posted 28 February 2022

383

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Physical Chemistry

Working Paper

Developing Differentiable Long-Range Force Field for Proteins with E(3) Neural Network Predicted Asymptotic Parameters

Zheng Cheng, Hangrui Bi, Siyuan Liu, Junmin Chen, Kuang Yu

Version 1 posted 11 March 2024

201

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Theoretical and Computational Chemistry

Working Paper

BAND NN: A Deep Learning Framework For Energy Prediction and Geometry Optimization of Organic Small Molecules

Siddhartha Laghuvarapu, Yashaswi Pathak, U. Deva Priyakumar

Version 1 posted 06 September 2019

1,218

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Theoretical and Computational Chemistry

Working Paper

Linear Atomic Cluster Expansion Force Fields for Organic Molecules: beyond RMSE

David Peter Kovacs, Cas van der Oord, Jiri Kucera, Alice Allen, Daniel Cole, Christoph Ortner, Gabor Csanyi

Version 4 posted 12 October 2021

1,731

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Physical Chemistry

Working Paper

Spatio-Temporal Characterization of Water Diffusion Anomalies in Saline Solutions Using Machine Learning Force Field

Ji Woong Yu, Sebin Kim, Jae Hyun Ryu, Won Bo Lee, Tae Jun Yoon

Version 1 posted 19 April 2024

78

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Theoretical and Computational Chemistry

Working Paper

Comparison of Machine-Learning and Classical Force Fields in Simulating the Solvation of Small Organic Molecules in Acetonitrile

Sangni Xun, Fang Liu

Version 2 posted 01 November 2023

473

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Materials Science

Working Paper

Predicting Structural Properties of Pure Silica Zeolites Using Deep Neural Network Potentials

Tyler Sours, Ambarish Kulkarni

Version 2 posted 23 December 2022

265

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Refine Search

10 results in machine learning force field in Keywords: machine learning force field

Room-temperature stacking disorder in layered covalent-organic frameworks from machine-learning force fields

PairNet: Predicting Correlation Energies with Correlated Features

Probing the role of acid site distribution on water structure in aluminosilicate zeolites: insights from molecular dynamics

Machine Learning Force Field Aided Cluster Expansion Approach to Configurationally Disordered Materials: Critical Assessment of Training Set Selection and Size Convergence

Developing Differentiable Long-Range Force Field for Proteins with E(3) Neural Network Predicted Asymptotic Parameters

BAND NN: A Deep Learning Framework For Energy Prediction and Geometry Optimization of Organic Small Molecules

Linear Atomic Cluster Expansion Force Fields for Organic Molecules: beyond RMSE

Spatio-Temporal Characterization of Water Diffusion Anomalies in Saline Solutions Using Machine Learning Force Field

Comparison of Machine-Learning and Classical Force Fields in Simulating the Solvation of Small Organic Molecules in Acetonitrile

Predicting Structural Properties of Pure Silica Zeolites Using Deep Neural Network Potentials

10 results in Keywords: machine learning force field