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Theoretical and Computational Chemistry

Working Paper

Learning from Failure: Predicting Electronic Structure Calculation Outcomes with Machine Learning Models

Chenru Duan, Jon Paul Janet, Fang Liu, Aditya Nandy, Heather Kulik

Version 1 posted 23 January 2019

1,322

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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

815

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1

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Theoretical and Computational Chemistry

Working Paper

Semi-Supervised Machine Learning Enables the Robust Detection of Multireference Character at Low Cost

Chenru Duan, Fang Liu, Aditya Nandy, Heather Kulik

Version 1 posted 02 July 2020

835

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Theoretical and Computational Chemistry

Working Paper

The Effect of Hartree-Fock Exchange on Scaling Relations and Reaction Energetics for C–H Activation Catalysts

Vyshnavi Vennelakanti, Aditya Nandy, Heather Kulik

Version 1 posted 11 June 2021

402

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Theoretical and Computational Chemistry

Working Paper

Strategies and Software for Machine Learning Accelerated Discovery in Transition Metal Chemistry

Aditya Nandy, Chenru Duan, Jon Paul Janet, Stefan Gugler, Heather Kulik

Version 1 posted 21 August 2018

1,097

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1

Citations

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

759

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Theoretical and Computational Chemistry

Working Paper

Ligand Many-Body Expansion as a General Approach for Accelerating Transition Metal Complex Discovery

Daniel Chu, David Gonzalez-Narvaez, Ralf Meyer, Aditya Nandy, Heather Kulik

Version 1 posted 13 September 2024

109

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Catalysis

Working Paper

Understanding the Role of Geometric and Electronic Structure in Bioinspired Catalyst Design: the Case of Formate Dehydrogenase

Mingjie Liu, Azadeh Nazemi, Michael Taylor, Aditya Nandy, Chenru Duan, Adam Steeves, Heather Kulik

Version 1 posted 30 September 2021

377

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Inorganic Chemistry

Working Paper

Assessing the Performance of Approximate Density Functional Theory on 95 Experimentally Characterized Fe(II) Spin Crossover Complexes

Vyshnavi Vennelakanti, Michael Taylor, Aditya Nandy, Chenru Duan, Heather Kulik

Version 1 posted 08 May 2023

337

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Inorganic Chemistry

Working Paper

Identifying Underexplored and Untapped Regions in the Chemical Space of Transition Metal Complexes

Aditya Nandy, Michael Taylor, Heather Kulik

Version 1 posted 05 May 2023

308

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25 results in Aditya Nandy in Authors: Aditya Nandy

Learning from Failure: Predicting Electronic Structure Calculation Outcomes with Machine Learning Models

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

Semi-Supervised Machine Learning Enables the Robust Detection of Multireference Character at Low Cost

The Effect of Hartree-Fock Exchange on Scaling Relations and Reaction Energetics for C–H Activation Catalysts

Strategies and Software for Machine Learning Accelerated Discovery in Transition Metal Chemistry

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

Ligand Many-Body Expansion as a General Approach for Accelerating Transition Metal Complex Discovery

Understanding the Role of Geometric and Electronic Structure in Bioinspired Catalyst Design: the Case of Formate Dehydrogenase

Assessing the Performance of Approximate Density Functional Theory on 95 Experimentally Characterized Fe(II) Spin Crossover Complexes

Identifying Underexplored and Untapped Regions in the Chemical Space of Transition Metal Complexes

25 results in Authors: Aditya Nandy