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Theoretical and Computational Chemistry

Working Paper

Active Learning and Neural Network Potentials Accelerate Molecular Screening of Ether-based Solvate Ionic Liquids

Wujie Wang, Tzuhsiung Yang, William Harris, Rafael Gomez-Bombarelli

Version 1 posted 18 May 2020

427

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Organic Chemistry

Working Paper

Machine Learning to Reduce Reaction Optimization Lead Time – Proof of Concept with Suzuki, Negishi and Buchwald-Hartwig Cross-Coupling Reactions

Fernando Huerta, Samuel Hallinder, Alexander Minidis

Version 1 posted 07 July 2020

1,206

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2

Citations

Theoretical and Computational Chemistry

Working Paper

PySurf - A Framework for Database Accelerated Direct Dynamics

Shirin Faraji, Johannes Ehrmaier, Maximilian Menger

Version 1 posted 28 October 2020

223

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Theoretical and Computational Chemistry

Working Paper

Inverse Material Search and Synthesis Verification by Hand Drawings via Transfer Learning and Contour Detection

Nikita Serov, Vladimir Vinogradov

Version 1 posted 08 June 2021

279

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Theoretical and Computational Chemistry

Working Paper

Predicting Critical Micelle Concentrations for Surfactants using Graph Convolutional Neural Networks

Shiyi Qin, Tianyi Jin, Reid Van Lehn, Victor Zavala

Version 2 posted 09 April 2021

1,385

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Catalysis

Working Paper

A Study of Two-Dimensional Single Atom-Supported MXenes as Hydrogen Evolution Reaction Catalysts Using DFT and Machine Learning

HONGXING LIANG, Min Xu, Edouard Asselin

Version 1 posted 11 May 2021

963

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1

Citations

Organic Chemistry

Working Paper

Computational Methods for Training Set Selection and Error Assessment Applied to Catalyst Design: Guidelines for Deciding Which Reactions to Run First and Which to Run Next

Scott Denmark, Andrew Zahrt, William Darrow, Brennan Rose, Jeremy Henle

Version 1 posted 16 November 2020

439

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Theoretical and Computational Chemistry

Working Paper

Accurate and Rapid Prediction of pKa of Transition Metal Complexes: Semiempirical Quantum Chemistry with a DataAugmented Approach

Vivek Sinha, Jochem Jan Laan, Evgeny Pidko

Version 1 posted 14 October 2020

531

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Theoretical and Computational Chemistry

Working Paper

An Analysis of Proteochemometric and Conformal Prediction Machine Learning Protein-Ligand Binding Affinity Models

conor parks, Zied Gaieb, Rommie Amaro

Version 1 posted 29 January 2020

681

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Nanoscience

Working Paper

Selecting Machine Learning Models for Metallic Nanoparticles

Amanda Barnard, George Opletal

Version 1 posted 15 May 2020

611

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Refine Search

14 results in machine Learning Methods Enable Predictive Modeling in Keywords: machine Learning Methods Enable Predictive Modeling

Active Learning and Neural Network Potentials Accelerate Molecular Screening of Ether-based Solvate Ionic Liquids

Machine Learning to Reduce Reaction Optimization Lead Time – Proof of Concept with Suzuki, Negishi and Buchwald-Hartwig Cross-Coupling Reactions

PySurf - A Framework for Database Accelerated Direct Dynamics

Inverse Material Search and Synthesis Verification by Hand Drawings via Transfer Learning and Contour Detection

Predicting Critical Micelle Concentrations for Surfactants using Graph Convolutional Neural Networks

A Study of Two-Dimensional Single Atom-Supported MXenes as Hydrogen Evolution Reaction Catalysts Using DFT and Machine Learning

Computational Methods for Training Set Selection and Error Assessment Applied to Catalyst Design: Guidelines for Deciding Which Reactions to Run First and Which to Run Next

Accurate and Rapid Prediction of pKa of Transition Metal Complexes: Semiempirical Quantum Chemistry with a DataAugmented Approach

An Analysis of Proteochemometric and Conformal Prediction Machine Learning Protein-Ligand Binding Affinity Models

Selecting Machine Learning Models for Metallic Nanoparticles

14 results in Keywords: machine Learning Methods Enable Predictive Modeling