I use ab initio simulations in combination with force-field molecular dynamics to study electrochemical (metal/water) interfaces under conditions of applied bias. I am also involved in the development of the pyiron software package http://pyiron.org, a python based IDE for computational materials science. pyiron is open source and available on github. I am also interested in Machine learning and its application in computational materials design.

My doctoral thesis

Surendralal, Sudarsan. “Development of an ab initio computational potentiostat and its application to the study of Mg corrosion.” (2020). (Open Access link)

Publications

  • Surendralal, S., Todorova, M., & Neugebauer, J. (2021). Impact of Water Coadsorption on the Electrode Potential of H-Pt(1 1 1)-Liquid Water Interfaces. Physical Review Letters, 126(16), 166802 (Open Access link)

  • Janssen, J., Surendralal, S., Lysogorskiy, Y., Todorova, M., Hickel, T., Drautz, R., Neugebauer J. (2019). pyiron: An integrated development environment for computational materials science. Computational Materials Science, 163 (Open Access link)

  • Surendralal, S., Todorova, M., Finnis, M. W., & Neugebauer, J. (2018). First-Principles Approach to Model Electrochemical Reactions: Understanding the Fundamental Mechanisms behind Mg Corrosion. Physical Review Letters, 120(24), 246801 (Journal link and Open Access link)