Guiding the experimental development of coatings to improve the performance of solid-state batteries.
Leading 2 collaborative projects to accelerate the screening of battery materials using machine learning-driven simulations
Secured computational resources towards the development of novel cathodes for solid-state batteries
Idaho National Laboratory, Idaho Falls, USA, May 2021 - Aug 2021
Research Internship, Computational Mechanics and Materials Organisation
Modeled hydrogen stability and transport in transition-metal hydrides, oxides using density functional theory calculations, ab initio molecular dynamics and kinetic monte carlo simulations.
Developed machine learned interatomic potentials from ab initio molecular dynamics datasets, to model the proton kinetics in crystalline and amorphous media.
Designed and tested active machine learning workflows on various HPC systems, to develop Gaussian approximation potentials.
Achieved a ~350 times improvement in simulation speeds, and within 7% agreement with quantum mechanical calculations for proton diffusion coefficients.
University of Michigan, Ann Arbor, USA, Sept 2017 - Aug 2022
Graduate Student, Materials Science and Engineering
Established collaborations with Universities and National Labs to guide materials selection for advanced energy applications.
Developed multiscale computational models and proposed new materials for hydrogen/solar energy storage and infrastructure.
Conceptualized/co-led 4 collaborative projects resulting in 9 technical manuscripts and 8 conference presentations.
Larsen and Toubro, Mumbai, India, Summer 2013
Engineering Internship, Heavy Engineering Division
Used non destructive evaluation techniques such as liquid dye penetrant testing and ultrasonic testing to identify surface and internal defects (cracks and porosity) in weld components