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Heather J. Kulik
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Year
Density Functional Theory in Transition-Metal Chemistry: A Self-Consistent Hubbard Approach
HJ Kulik, M Cococcioni, DA Scherlis, N Marzari
Physical Review Letters 97 (10), 103001, 2006
6432006
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
3492020
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
2882019
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
2712019
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
2322014
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
2222017
Perspective: Treating electron over-delocalization with the DFT+ U method
HJ Kulik
The Journal of chemical physics 142 (24), 240901, 2015
2032015
Predicting electronic structure properties of transition metal complexes with neural networks
JP Janet, HJ Kulik
Chemical Science 8 (7), 5137-5152, 2017
1912017
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
1892016
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
1872018
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
1742019
molSimplify: A toolkit for automating discovery in inorganic chemistry
EI Ioannidis, TZH Gani, HJ Kulik
Journal of computational chemistry 37 (22), 2106-2117, 2016
1632016
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
1452018
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
1422020
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
1422018
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
1352021
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
1232012
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
1192016
Towards quantifying the role of exact exchange in predictions of transition metal complex properties
EI Ioannidis, HJ Kulik
The Journal of chemical physics 143 (3), 034104, 2015
1122015
Systematic study of first-row transition-metal diatomic molecules: A self-consistent approach
HJ Kulik, N Marzari
The Journal of chemical physics 133 (11), 114103, 2010
1112010
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Articles 1–20