We apply Computational Chemistry and Machine Learning methods to discover materials with improved performance for energy and environmental applications. Our research guides experiments by providing atomic-level insights employing principles of Quantum Chemistry, Thermodynamics, Electrochemistry and Catalysis.
Postdoctoral Researcher, 2017 - 2019
University of Pittsburgh, USA
Postdoctoral Fellow, 2013 - 2016
Bar-Ilan University, Israel
Ph.D. in Computational Chemistry, 2008-2013
CSIR-National Chemical Lab, Pune
Plane-wave DFT and ab-initio
Reaction Dynamics and Kinetics
Demonstrated that SCAN is a versatile functional that provides good all-round performance for all relevant electrochemical properties of prototype layered cathode materials.
Structure–activity relationships were developed in alkane dehydrogenation on γ-Al2O3, revealing a site-dependent catalytic behavior and identifying active sites through a volcano plot.
we elucidate the CO2 dissociation mechanism on β-Mo2C (001) under different oxygen coverage on the catalyst surface. We reveal linear relationships between the oxygen coverage and electronic modification with the reactivity of the catalyst.
Through a detailed computational study, we demonstrated that why the Ni-rich cathode materials (for Li-ion batteries) possess low structural stability.
We show Al stabilizes the structure of the NCM cathode materials via strong Al-O iono-covalent bonding due to a significant Al(s)-O(p) overlap and significant charge transfer capabilities of Al.
We illustrate the catalytic control exerted by trichodiene synthase, and in particular, we discover features that could be general catalytic tools adopted by other terpenoid cyclases.
We present lattice doping as a strategy to improve the structural stability and voltage fade on prolonged cycling of LiNi0.6Co0.2Mn0.2O2 (NCM-622) doped with zirconium.
We show that cationic ordering of NCM cathodes can be predicted employing cheap atomistic simulations, instead of using expensive first-principles methods.Subsequently, we investigate the electrochemical, thermodynamic and kinetic properties of NCM-523.
Electrochemical Energy Storage, Computational Catalysis, Machine Learning for Chemistry
Computational Electrochemical Energy
Computational Catalysis, Hydroden storage
Journal front cover
My work has been selected to be highlighted on the front cover of Journal of The Electrochemical Society. Cover Link