| MOFSimplify, machine learning models with extracted stability data of three thousand metal–organic frameworks A Nandy, G Terrones, N Arunachalam, C Duan, DW Kastner, HJ Kulik Scientific Data 9 (1), 74, 2022 | 74 | 2022 |
| Large-scale comparison of 3d and 4d transition metal complexes illuminates the reduced effect of exchange on second-row spin-state energetics A Nandy, DBK Chu, DR Harper, C Duan, N Arunachalam, Y Cytter, ... Physical Chemistry Chemical Physics 22 (34), 19326-19341, 2020 | 31 | 2020 |
| Representations and strategies for transferable machine learning improve model performance in chemical discovery DR Harper, A Nandy, N Arunachalam, C Duan, JP Janet, HJ Kulik The Journal of Chemical Physics 156 (7), 2022 | 17 | 2022 |
| A transferable recommender approach for selecting the best density functional approximations in chemical discovery C Duan, A Nandy, R Meyer, N Arunachalam, HJ Kulik Nature Computational Science 3 (1), 38-47, 2023 | 16 | 2023 |
| Ligand additivity relationships enable efficient exploration of transition metal chemical space N Arunachalam, S Gugler, MG Taylor, C Duan, A Nandy, JP Janet, ... The Journal of Chemical Physics 157 (18), 2022 | 14 | 2022 |
| Deep Kernel Inversion: Rapid and Accurate Molecular Interaction Prediction for Drug Design SA Myers, C Miller, K Lugo, T Trinh, C Lee, N Arunachalam, H Chen, ... bioRxiv preprint 2024.11.19.624391, 2024 | | 2024 |
| The Emperor’s New Clothes or the Next Big Thing?-Web3 Applications in Real Estate Decarbonization Z Tan, A Guo, N Arunachalam MIT Center for Real Estate Research Paper, 2023 | | 2023 |
| Web3 in Real Estate Decarbonization Z Tan, A Guo, N Arunachalam AFIRE Summit, 40-49, 2023 | | 2023 |
| Autonomous First-Principles Design of Transition Metal Complexes N Arunachalam Massachusetts Institute of Technology, 2023 | | 2023 |
| Leveraging Experimental Transition Metal Complex Information to Improve Generalizability of Machine Learning Models M Taylor, C Duan, N Arunachalam, A Nandy, D Harper, H Kulik 2020 Virtual AIChE Annual Meeting, 2020 | | 2020 |
| Navigating Combinatorial Challenges in High-Throughput Transition Metal Complex Discovery N Arunachalam, A Nandy, C Duan, M Taylor, D Harper, H Kulik 2020 Virtual AIChE Annual Meeting, 2020 | | 2020 |
| A Database with Automated Quantum Chemistry Calculations and Machine Learning for Functional Transition Metal Complex Discovery C Duan, M Taylor, D Harper, A Nandy, N Arunachalam, F Liu, H Kulik 2020 Virtual AIChE Annual Meeting, 2020 | | 2020 |
| Molecular Design Blueprints: Catalysts and Principles from New Simulation and Machine Learning Tools H Kulik, A Nandy, D Harper, M Taylor, C Duan, F Liu, JP Janet, ... 2020 Virtual AIChE Annual Meeting, 2020 | | 2020 |
| Machine Learning and Transition Metal Chemistry: Data-Driven Comparisons of First and Second Row Complexes JP Janet, D Harper, N Arunachalam, A Nandy, C Duan, H Kulik 2019 AIChE Annual Meeting, 2019 | | 2019 |
| Understanding the Role of Asymmetry in Inorganic Discovery N Arunachalam, JP Janet, HJ Kulik New England Energy Research Forum, 2019 | | 2019 |
| Numerical Analysis of Flow Chamber Morphologies for Pilot-Scale Ultrasonication N Arunachalam COMSOL Conference 2017, Singapore, 2017 | | 2017 |
| Computational Prediction of Interactions Between β-Ionone and hOR5A1-6 N Arunachalam Caltech Undergraduate Research Journal 17 (1), 13-21, 2015 | | 2015 |
Heather J. KulikChemical Engineering and Chemistry, Massachusetts Institute of TechnologyEmail verificata su mit.edu