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Theoretical and Computational Chemistry

Working Paper

Accelerated Modeling of Lithium Diffusion in Solid State Electrolytes Using Artificial Neural Networks

Karun Kumar Rao, Yan Yao, Lars Grabow

Version 1 posted 07 May 2020

898

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Theoretical and Computational Chemistry

Working Paper

Mol2vec: Unsupervised Machine Learning Approach with Chemical Intuition

Sabrina Jaeger, Simone Fulle, Samo Turk

Version 1 posted 23 October 2017

5,128

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2

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Theoretical and Computational Chemistry

Working Paper

Machine Learning Accelerates the Discovery of Design Rules and Exceptions in Stable Metal-Oxo Intermediate Formation

Aditya Nandy, Jiazhou Zhu, Jon Paul Janet, Chenru Duan, Rachel Getman, Heather Kulik

Version 1 posted 28 May 2019

828

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1

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Energy

Working Paper

A machine learning framework for remaining useful lifetime prediction of li-ion batteries using diverse neural networks

Junghwan Lee, Huanli Sun, Yongshan Liu, Xue Li

Version 2 posted 15 September 2023

366

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Theoretical and Computational Chemistry

Working Paper

Artificial Neural Network to Predict Structure-based Protein-protein Free Energy of Binding from Rosetta-calculated Properties

Matheus Ferraz, José Neto, Roberto Lins, Erico Teixeira

Version 1 posted 09 August 2022

804

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Analytical Chemistry

Working Paper

A Rapid Dynamic Headspace Method for Authentication of Whiskies using Artificial Neural Networks

James Swift, Matthew Arran Turner, James Christopher Reynolds

Version 1 posted 14 February 2023

154

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Theoretical and Computational Chemistry

Working Paper

Seeing is Believing: Experimental Spin States from Machine Learning Model Structure Predictions

Michael Taylor, Tzuhsiung Yang, Sean Lin, Aditya Nandy, Jon Paul Janet, Chenru Duan, Heather Kulik

Version 1 posted 21 February 2020

773

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Chemical Engineering and Industrial Chemistry

Working Paper

On the continuous modeling of fluid and solid states

Gustavo Chaparro, Erich A. Müller

Version 2 posted 28 May 2024

380

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Chemical Engineering and Industrial Chemistry

Working Paper

Physics-based neural networks for simulation and synthesis of cyclic adsorption processes

Sai Gokul Subraveti, Zukui Li, Vinay Prasad, Arvind Rajendran

Version 2 posted 25 February 2022

733

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1

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Catalysis

Working Paper

Kinetics-Constrained Neural Ordinary Differential Equations: Artificial Neural Network Models tailored for Small Data to boost Kinetic Model Development

Aleksandr Fedorov, Anna Perechodjuk, David Linke

Version 1 posted 15 May 2023

971

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14 results in Artificial Neural Networks in Keywords: Artificial Neural Networks

Accelerated Modeling of Lithium Diffusion in Solid State Electrolytes Using Artificial Neural Networks

Mol2vec: Unsupervised Machine Learning Approach with Chemical Intuition

Machine Learning Accelerates the Discovery of Design Rules and Exceptions in Stable Metal-Oxo Intermediate Formation

A machine learning framework for remaining useful lifetime prediction of li-ion batteries using diverse neural networks

Artificial Neural Network to Predict Structure-based Protein-protein Free Energy of Binding from Rosetta-calculated Properties

A Rapid Dynamic Headspace Method for Authentication of Whiskies using Artificial Neural Networks

Seeing is Believing: Experimental Spin States from Machine Learning Model Structure Predictions

On the continuous modeling of fluid and solid states

Physics-based neural networks for simulation and synthesis of cyclic adsorption processes

Kinetics-Constrained Neural Ordinary Differential Equations: Artificial Neural Network Models tailored for Small Data to boost Kinetic Model Development

14 results in Keywords: Artificial Neural Networks