Publications

Author Title [ Type(Desc)] Year
Filters: Author is Aditya Nandy  [Clear All Filters]
Journal Article
Computational Discovery of Transition-Metal Complexes: From High-throughput Screening to Machine Learning, Nandy, Aditya, Duan Chenru, Taylor Michael G., Liu Fang, Steeves Adam H., and Kulik Heather J. , Chemical Reviews, (In Press)
Data-Driven Approaches Can Overcome the Cost-Accuracy Tradeoff in Multireference Diagnostics, Duan, Chenru, Liu Fang, Nandy Aditya, and Kulik Heather J. , Journal of Chemical Theory and Computation, Volume 16, p.4373-4387, (2020)
Designing in the Face of Uncertainty: Exploiting Electronic Structure and Machine Learning Models for Discovery in Inorganic Chemistry, Janet, Jon Paul, Liu Fang, Nandy Aditya, Duan Chenru, Yang Tzuhsiung, Lin Sean, and Kulik Heather J. , Inorganic Chemistry, Volume 58, p.10592-10606, (2019)
The Effect of Hartree-Fock Exchange on Scaling Relations and Reaction Energetics for C–H Activation Catalysts, Vennelakanti, Vyshnavi, Nandy Aditya, and Kulik Heather J. , Topics in Catalysis, (In Press)
Large-scale comparison of 3d and 4d transition metal complexes illuminates the reduced effect of exchange on second-row spin-state energetics, Nandy, Aditya, Chu Daniel B. K., Harper Daniel R., Duan Chenru, Arunachalam Naveen, Cytter Yael, and Kulik Heather J. , Physical Chemistry Chemical Physics, Volume 22, p.19326-19341, (2020)
Learning from Failure: Predicting Electronic Structure Calculation Outcomes with Machine Learning Models, Duan, Chenru, Janet Jon Paul, Liu Fang, Nandy Aditya, and Kulik Heather J. , Journal of Chemical Theory and Computation, Volume 15, p.2331-2345, (2019)
Machine Learning Accelerates the Discovery of Design Rules and Exceptions in Stable Metal-Oxo Intermediate Formation, Nandy, Aditya, Zhu Jiazhou, Janet Jon Paul, Duan Chenru, Getman Rachel B., and Kulik Heather J. , ACS Catalysis, Volume 9, p.8243-8255, (2019)
Navigating Transition-Metal Chemical Space: Artificial Intelligence for First-Principles Design, Janet, Jon Paul, Duan Chenru, Nandy Aditya, Liu Fang, and Kulik Heather J. , Accounts of Chemical Research, Volume 54, p.532-545, (2021)
Putting Density Functional Theory to the Test in Machine-Learning-Accelerated Materials Discovery, Duan, Chenru, Liu Fang, Nandy Aditya, and Kulik Heather J. , The Journal of Physical Chemistry Letters, Volume 12, p.4628-4637, (2021)
A quantitative uncertainty metric controls error in neural network-driven chemical discovery, Janet, Jon Paul, Duan Chenru, Yang Tzuhsiung, Nandy Aditya, and Kulik Heather J. , Chemical Science, Volume 10, p.7913-7922, (2019)
Representations and Strategies for Transferable Machine Learning Models in Chemical Discovery, Harper, Daniel R., Nandy Aditya, Arunachalam Naveen, Duan Chenru, Janet Jon Paul, and Kulik Heather J. , (Submitted)
Seeing is Believing: Experimental Spin States from Machine Learning Model Structure Predictions, Taylor, Michael G., Yang Tzuhsiung, Lin Sean, Nandy Aditya, Janet Jon Paul, Duan Chenru, and Kulik Heather J. , The Journal of Physical Chemistry A, Volume 124, p.3286-3299, (2020)
Semi-Supervised Machine Learning Enables the Robust Detection of Multireference Character at Low Cost, Duan, Chenru, Liu Fang, Nandy Aditya, and Kulik Heather J. , The Journal of Physical Chemistry Letters, Volume 11, p.6640-6648, (2020)
Strategies and Software for Machine Learning Accelerated Discovery in Transition Metal Chemistry, Nandy, Aditya, Duan Chenru, Janet Jon Paul, Gugler Stefan, and Kulik Heather J. , Industrial & Engineering Chemistry Research (invited for special issue), 09/2018, Volume 57, (2018)
Understanding the diversity of the metal-organic framework ecosystem, Moosavi, Seyed Mohamad, Nandy Aditya, Jablonka Kevin M., Ongari Daniele, Janet Jon Paul, Boyd Peter G., Lee Yongjin, Smit Berend, and Kulik Heather J. , Nature Communications, Volume 11, (2020)
Using Machine Learning and Data Mining to Leverage Community Knowledge for the Engineering of Stable Metal-Organic Frameworks, Nandy, Aditya, Duan Chenru, and Kulik Heather J. , (Submitted)
Why Conventional Design Rules for C-H Activation Fail for Open Shell Transition Metal Catalysts, Nandy, Aditya, and Kulik Heather J. , ACS Catalysis, Volume 10, p.15033-15047, (2020)

About Us

The Kulik group focuses on the development and application of new electronic structure methods and atomistic simulations tools in the broad area of catalysis.

Our Interests

We are interested in transition metal chemistry, with applications from biological systems (i.e. enzymes) to nonbiological applications in surface science and molecular catalysis.

Our Focus

A key focus of our group is to understand mechanistic features of complex catalysts and to facilitate and develop tools for computationally driven design.

Contact Us

Questions or comments? Let us know! Contact Dr. Kulik: