Density Functional Theory in Transition-Metal Chemistry: A Self-Consistent Hubbard HJ Kulik, M Cococcioni, DA Scherlis, N Marzari
Physical Review Letters 97 (10), 103001, 2006
695 2006 Understanding the diversity of the metal-organic framework ecosystem SM Moosavi, A Nandy, KM Jablonka, D Ongari, JP Janet, PG Boyd, Y Lee, ...
Nature communications 11 (1), 1-10, 2020
455 2020 Protection of tissue physicochemical properties using polyfunctional crosslinkers YG Park, CH Sohn, R Chen, M McCue, DH Yun, GT Drummond, T Ku, ...
Nature biotechnology 37 (1), 73-83, 2019
369 2019 Critical knowledge gaps in mass transport through single-digit nanopores: a review and perspective S Faucher, N Aluru, MZ Bazant, D Blankschtein, AH Brozena, J Cumings, ...
The Journal of Physical Chemistry C 123 (35), 21309-21326, 2019
324 2019 Resolving transition metal chemical space: Feature selection for machine learning and structure–property relationships JP Janet, HJ Kulik
The Journal of Physical Chemistry A 121 (46), 8939-8954, 2017
273 2017 Mechanically triggered heterolytic unzipping of a low-ceiling-temperature polymer CE Diesendruck, GI Peterson, HJ Kulik, JA Kaitz, BD Mar, PA May, ...
Nature chemistry 6 (7), 623-628, 2014
254 2014 Perspective: Treating electron over-delocalization with the DFT+ U method HJ Kulik
The Journal of chemical physics 142 (24), 240901, 2015
221 2015 Accelerating chemical discovery with machine learning: simulated evolution of spin crossover complexes with an artificial neural network JP Janet, L Chan, HJ Kulik
The Journal of Physical Chemistry Letters 9 (5), 1064-1071, 2018
215 2018 Predicting electronic structure properties of transition metal complexes with neural networks JP Janet, HJ Kulik
Chemical Science 8 (7), 5137-5152, 2017
214 2017 How large should the QM region be in QM/MM calculations? The case of catechol O-methyltransferase HJ Kulik, J Zhang, JP Klinman, TJ Martinez
The Journal of Physical Chemistry B 120 (44), 11381-11394, 2016
211 2016 A quantitative uncertainty metric controls error in neural network-driven chemical discovery JP Janet, C Duan, T Yang, A Nandy, HJ Kulik
Chemical science 10 (34), 7913-7922, 2019
206 2019 Computational Discovery of Transition-metal Complexes: From High-throughput Screening to Machine Learning A Nandy, C Duan, MG Taylor, F Liu, AH Steeves, HJ Kulik
Chemical Reviews 121 (16), 9927-10000, 2021
201 2021 molSimplify: A toolkit for automating discovery in inorganic chemistry EI Ioannidis, TZH Gani, HJ Kulik
Journal of computational chemistry 37 (22), 2106-2117, 2016
195 2016 Accurate Multiobjective Design in a Space of Millions of Transition Metal Complexes with Neural-Network-Driven Efficient Global Optimization JP Janet, S Ramesh, C Duan, HJ Kulik
ACS Central Science 6 (4), 513-524, 2020
162 2020 Strategies and software for machine learning accelerated discovery in transition metal chemistry A Nandy, C Duan, JP Janet, S Gugler, HJ Kulik
Industrial & Engineering Chemistry Research 57 (42), 13973-13986, 2018
160 2018 Understanding and Breaking Scaling Relations in Single-Site Catalysis: Methane to Methanol Conversion by FeIV=O TZH Gani, HJ Kulik
ACS Catalysis 8 (2), 975-986, 2018
160 2018 Anion‐Selective Redox Electrodes: Electrochemically Mediated Separation with Heterogeneous Organometallic Interfaces X Su, HJ Kulik, TF Jamison, TA Hatton
Advanced Functional Materials 26 (20), 3394-3404, 2016
136 2016 Roadmap on machine learning in electronic structure HJ Kulik, T Hammerschmidt, J Schmidt, S Botti, MAL Marques, M Boley, ...
Electronic Structure 4 (2), 023004, 2022
135 2022 Ab initio quantum chemistry for protein structures HJ Kulik, N Luehr, IS Ufimtsev, TJ Martinez
The Journal of Physical Chemistry B 116 (41), 12501-12509, 2012
132 2012 Using Machine Learning and Data Mining to Leverage Community Knowledge for the Engineering of Stable Metal–Organic Frameworks A Nandy, C Duan, HJ Kulik
Journal of the American Chemical Society, 2021
118 2021 
Aditya NandySchmidt AI in Science Fellow at UChicago and Incoming Assistant Professor at UCLA (2025)Email verificata su ucla.edu
