Publications by authors named "Aditya Nandy"

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Mapping the diverse topologies of protein-protein interaction fitness landscapes.
Shannon S Lu, Matthew J Styles, Cheng Frank Gao, Aditya Nandy, Christopher Basile

bioRxiv· October 2025

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Ligand Many-Body Expansion as a General Approach for Accelerating Transition Metal Complex Discovery.
Daniel B K Chu, David A González-Narváez, Ralf Meyer, Aditya Nandy, Heather J Kulik

J Chem Inf Model· December 2024

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MOFs with the Stability for Practical Gas Adsorption Applications Require New Design Rules.
Changhwan Oh, Aditya Nandy, Shuwen Yue, Heather J Kulik

ACS Appl Mater Interfaces· October 2024

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Fitness Landscapes and Evolution of Catalytic RNA.
Ranajay Saha, Alberto Vázquez-Salazar, Aditya Nandy, Irene A Chen

Annu Rev Biophys· July 2024

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Protein3D: Enabling analysis and extraction of metal-containing sites from the Protein Data Bank with molSimplify.
Freya Edholm, Aditya Nandy, Clorice R Reinhardt, David W Kastner, Heather J Kulik

J Comput Chem· March 2024

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Discovering Molecular Coordination Environment Trends for Selective Ion Binding to Molecular Complexes Using Machine Learning.
Shuwen Yue, Aditya Nandy, Heather J Kulik

J Phys Chem B· December 2023

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Computational Discovery of Stable Metal-Organic Frameworks for Methane-to-Methanol Catalysis.
Husain Adamji, Aditya Nandy, Ilia Kevlishvili, Yuriy Román-Leshkov, Heather J Kulik

J Am Chem Soc· July 2023

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Assessing the performance of approximate density functional theory on 95 experimentally characterized Fe(II) spin crossover complexes.
Vyshnavi Vennelakanti, Michael G Taylor, Aditya Nandy, Chenru Duan, Heather J Kulik

J Chem Phys· July 2023

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Identifying Underexplored and Untapped Regions in the Chemical Space of Transition Metal Complexes.
Aditya Nandy, Michael G Taylor, Heather J Kulik

J Phys Chem Lett· June 2023

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Insights into the deviation from piecewise linearity in transition metal complexes from supervised machine learning models.
Yael Cytter, Aditya Nandy, Chenru Duan, Heather J Kulik

Phys Chem Chem Phys· March 2023

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Low-cost machine learning prediction of excited state properties of iridium-centered phosphors.
Gianmarco G Terrones, Chenru Duan, Aditya Nandy, Heather J Kulik

Chem Sci· February 2023

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Active Learning Exploration of Transition-Metal Complexes to Discover Method-Insensitive and Synthetically Accessible Chromophores.
Chenru Duan, Aditya Nandy, Gianmarco G Terrones, David W Kastner, Heather J Kulik

JACS Au· February 2023

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DFT-Based Multireference Diagnostics in the Solid State: Application to Metal-Organic Frameworks.
Yeongsu Cho, Aditya Nandy, Chenru Duan, Heather J Kulik

J Chem Theory Comput· January 2023

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A transferable recommender approach for selecting the best density functional approximations in chemical discovery.
Chenru Duan, Aditya Nandy, Ralf Meyer, Naveen Arunachalam, Heather J Kulik

Nat Comput Sci· January 2023

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Ligand additivity relationships enable efficient exploration of transition metal chemical space.
Naveen Arunachalam, Stefan Gugler, Michael G Taylor, Chenru Duan, Aditya Nandy

J Chem Phys· November 2022

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Machine Learning Models Predict Calculation Outcomes with the Transferability Necessary for Computational Catalysis.
Chenru Duan, Aditya Nandy, Husain Adamji, Yuriy Roman-Leshkov, Heather J Kulik

J Chem Theory Comput· July 2022

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Machine Learning for the Discovery, Design, and Engineering of Materials.
Chenru Duan, Aditya Nandy, Heather J Kulik

Annu Rev Chem Biomol Eng· June 2022

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Molecular orbital projectors in non-empirical jmDFT recover exact conditions in transition-metal chemistry.
Akash Bajaj, Chenru Duan, Aditya Nandy, Michael G Taylor, Heather J Kulik

J Chem Phys· May 2022

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Ligand Additivity and Divergent Trends in Two Types of Delocalization Errors from Approximate Density Functional Theory.
Yael Cytter, Aditya Nandy, Akash Bajaj, Heather J Kulik

J Phys Chem Lett· May 2022

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New Strategies for Direct Methane-to-Methanol Conversion from Active Learning Exploration of 16 Million Catalysts.
Aditya Nandy, Chenru Duan, Conrad Goffinet, Heather J Kulik

JACS Au· May 2022

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Detection of multi-reference character imbalances enables a transfer learning approach for virtual high throughput screening with coupled cluster accuracy at DFT cost.
Chenru Duan, Daniel B K Chu, Aditya Nandy, Heather J Kulik

Chem Sci· May 2022

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MOFSimplify, machine learning models with extracted stability data of three thousand metal-organic frameworks.
Aditya Nandy, Gianmarco Terrones, Naveen Arunachalam, Chenru Duan, David W Kastner

Sci Data· March 2022

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Representations and strategies for transferable machine learning improve model performance in chemical discovery.
Daniel R Harper, Aditya Nandy, Naveen Arunachalam, Chenru Duan, Jon Paul Janet

J Chem Phys· February 2022

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Deciphering Cryptic Behavior in Bimetallic Transition-Metal Complexes with Machine Learning.
Michael G Taylor, Aditya Nandy, Connie C Lu, Heather J Kulik

J Phys Chem Lett· October 2021

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Using Machine Learning and Data Mining to Leverage Community Knowledge for the Engineering of Stable Metal-Organic Frameworks.
Aditya Nandy, Chenru Duan, Heather J Kulik

J Am Chem Soc· October 2021

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