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Graph-Based Approaches for Predicting Solvation Energy in Multiple Solvents: Open Datasets and Machine Learning Models

Logan Ward, Naveen Dandu, Ben Blaiszik, Badri Narayanan, Rajeev S. Assary, Paul C. Redfern, Ian Foster, Larry A. Curtiss

Version 1 posted 01 July 2021

598

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Theoretical and Computational Chemistry

Working Paper

Uncertainty-Informed Deep Transfer Learning of PFAS Toxicity

Jeremy Feinstein, ganesh sivaraman, Kurt Picel, Brian Peters, Alvaro Vazquez-Mayagoitia, Arvind Ramanathan, Margaret MacDonell, Ian Foster, Eugene Yan

Version 1 posted 15 April 2021

547

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Physical Chemistry

Working Paper

A Composition-Transferable Machine Learning Potential for LiCl-KCl Molten Salts Validated by HEXRD

Jicheng Guo, Logan Ward, Yadu Babuji, Nathaniel Hoyt, Mark Williamson, Ian Foster, Nicholas Jackson, Chris Benmore, ganesh sivaraman

Version 1 posted 04 February 2022

596

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Physical Chemistry

Working Paper

Automated Development of Molten Salt Machine Learning Potentials: Application to LiCl

ganesh sivaraman, Jicheng Guo, Logan Ward, Nathaniel Hoyt, Mark Williamson, Ian Foster, Chris Benmore, Nicholas Jackson

Version 1 posted 18 March 2021

669

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1

Citations

Energy

Working Paper

AL4GAP: Active Learning Workflow for generating DFT-SCAN Accurate Machine-Learning Potentials for Combinatorial Molten Salt Mixtures

Jicheng Guo, Vanessa Woo, David Andersson, Nathaniel Hoyt, Mark Williamson, Ian Foster, Chris Benmore, Nicholas Jackson, Ganesh Sivaraman

Version 1 posted 24 April 2023

485

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1

Citations

Chemical Education

Review

Review of Low-cost Self-driving Laboratories: The "Frugal Twin" Concept

Stanley Lo, Sterling Baird, Joshua Schrier, Ben Blaiszik, Nessa Carson, Ian Foster, Andrés Aguilar-Granda, Sergei Kalinin, Benji Maruyama, Maria Politi, Helen Tran, Taylor Sparks, Alán Aspuru-Guzik

Version 2 posted 16 November 2023

1,138

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1

Citations

Theoretical and Computational Chemistry

Working Paper

E_min: A First-Principles Thermochemical Descriptor for Predicting Molecular Synthesizability

Andrew Lee, Sarah N. Elliott, Hassan Harb, Logan Ward, Ian T. Foster, Larry A. Curtiss, Rajeev S. Assary

Version 1 posted 30 January 2024

237

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Theoretical and Computational Chemistry

Working Paper

Deep Learning for Molecular Orbitals

Daniel King, Daniel Grzenda, Ray Zhu, Nathaniel Hudson, Ian Foster, Laura Gagliardi

Version 1 posted 30 April 2024

395

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Theoretical and Computational Chemistry

Working Paper

Virtual Excited State Reference for the Discovery of Electronic Materials Database (VERDE Materials DB): An Open-Access Resource for Ground and Excited State Properties of Organic Molecules

Biruk Abreha, Snigdha Agarwal, Ian Foster, Ben Blaiszik, Steven Lopez

Version 2 posted 16 October 2019

864

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9 results in Ian Foster in Authors: Ian Foster

Graph-Based Approaches for Predicting Solvation Energy in Multiple Solvents: Open Datasets and Machine Learning Models

Uncertainty-Informed Deep Transfer Learning of PFAS Toxicity

A Composition-Transferable Machine Learning Potential for LiCl-KCl Molten Salts Validated by HEXRD

Automated Development of Molten Salt Machine Learning Potentials: Application to LiCl

AL4GAP: Active Learning Workflow for generating DFT-SCAN Accurate Machine-Learning Potentials for Combinatorial Molten Salt Mixtures

Review of Low-cost Self-driving Laboratories: The "Frugal Twin" Concept

E_min: A First-Principles Thermochemical Descriptor for Predicting Molecular Synthesizability

Deep Learning for Molecular Orbitals

Virtual Excited State Reference for the Discovery of Electronic Materials Database (VERDE Materials DB): An Open-Access Resource for Ground and Excited State Properties of Organic Molecules

9 results in Authors: Ian Foster