PNNL

Dr Krishna Chaitanya Pitike is a computational materials scientist in the Nuclear Sciences Division of the Pacific Northwest National Laboratory (PNNL). He has a broad interest in materials modeling and discovery and has expertise in computational materials science using density functional theory (DFT), molecular dynamics (MD), Monte Carlo, phase field methods, development of classical/machine learned surrogate materials models, and computational tools development. His research at PNNL primarily focuses on predictive modeling of He/H bubbles in nuclear fusion materials using multiscale modeling facilitated through development of machine learned interatomic potentials. Before joining PNNL, Pitike worked on multiscale modeling of perovskite ferroelectrics and combinatorial discovery of high entropy materials. He holds a PhD in materials science and engineering from University of Connecticut, Storrs, USA and has an undergraduate degree in metallurgical engineering from Jawaharlal Nehru Technological University, Hyderabad, India.

• Fusion reactor materials
• High-entropy materials
• Multifunctional materials
• Perovskite- and Hafnia- based multiferroics
• Materials for energy storage and conversion
• High-throughput and combinatorial materials discovery
• Machine learned surrogate materials models
• Radiation damage simulations
• Multiscale and integrated materials modeling
• Machine learned interatomic potentials
• Message passing interface (MPI) parallel programming for materials modeling.

• PhD in Material Science and Engineering, University of Connecticut, Storrs, USA
• BTech in Metallurgical Engineering, Jawaharlal Nehru Technological University, Hyderabad, India.

• American Physical Society
• American Ceramic Society.

• Second place winner of the Best Poster Award at the conference on Electronic and Advanced Materials jointly programmed by the Electronics Division and Basic Science Division of The American Ceramic Society, held at Orlando, Florida (2018).

2022

Pitike K., H. Ke, D.J. Edwards, and W. Setyawan. 2022. "Helium interaction with solutes and impurities in neutron-irradiated nanostructured ferritic alloys: A first principles study." Journal of Nuclear Materials 566. PNNL-SA-169716. doi: 10.1016/j.jnucmat.2022.153771

Pitike K.C. and W. Setyawan. 2022. “Accurate Fe–He machine learning potential for studying He effects in BCC-Fe.” Journal of Nuclear Materials. PNNL-SA-177551. doi: 10.1016/j.jnucmat.2022.154183