Prakriti Kayastha

Hello and welcome to my personal website!

I am Prakriti Kayastha, a postdoctoral researcher at University College London (UCL). I am based in the Materials Design and Informatics group led by Keith Butler in the Chemistry Department at UCL. My work is based on modelling materials using density functional theory and machine learning. At UCL, I will be studying barocalorics, which are materials that undergo spontaneous phase transitions under pressure. I will be working with a team of scientists based at Queen Mary University of London and Diamond Light Source. I’m excited to bring my expertise to this project, and at the same time, I am looking forward to learning more about core ML and collaborating with the wider community in London.

I use machine learning interatomic potentials to model the anharmonic potential energy surface of a material. These methods greatly reduce the evaluation time of energies and forces (on par with empirical force fields) while maintaining (near) accuracy of ab initio methods. MLIP

My postdoctral work continues well from my PhD work, where I studied phase transitions in potential solar cell materials. I got my PhD at Northumbria University, under the supervision of Lucy Whalley. I was part of the Center for Doctoral Training in Renewable Energy Northeast Universities (ReNU). My PhD focused on studying atomic vibrations, also known as phonons, through which several properties of interest can be derived - thermodynamics, spectroscopy, and phase transitions.

Here is a summary of topics that interested me during this time:

anharmonic phonons

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: