Prakriti Kayastha

Hello and welcome to my personal website!

I am Prakriti Kayastha, a PhD student at Northumbria University, UK. I am part of the Center for Doctoral Training in Renewable Energy Northeast Universities (ReNU). My work is based on modelling materials using density functional theory and machine learning.

Broadly, I am interested in modelling materials for next-generation photovoltaics. Currently, I am working on modelling the properties of chalcogenide perovskites for solar cell applications. A particular focus is on the topic of phonons, through which several properties of interest can be derived - thermodynamics, spectroscopy, and phase transitions. Here is a summary of topics I’m closely working with at the moment:

anharmonic_phonons

We also use machine learning potentials, which is a state of the art technique to model the anharmonic potential energy surface of a material. Additionally, I am always thinking about information theory, dataset curation, and descriptor space. I am also very interested in crystallography and symmetries of materials and I am always excited to talk about it, reach out!

Publications

Google Scholar
Orcid

Talks/Posters: