First principles calculations, usually based on density functional theory (DFT), are a crucial aspect of modern materials physics research. This computational approach, based on quantum mechanics, can help materials research by a) directly simulating and interpreting experiments, b) establishing relationships between material structure and properties, and c) predicting new phenomena and discovering improved materials for applications.
Our efforts in this area use a variety of modeling approaches to answer questions on materials systems of interest, often in direct collaboration with NIST experiments. The materials systems we have studied recently include topological materials, 2D materials, magnetic materials, dielectrics and ferroelectrics, thermoelectrics, and nanomaterials. Computational modeling approaches include high-throughput computation (see jarvis.nist.gov), predictive tight-binding analysis, cluster expansion, classical potential development, and machine learning. We both apply existing methods and develop new ones as appropriate for the problem, with an emphasis on simulations of realistic materials.
Successful candidates will have experience in some aspect of atomic-scale materials modeling and its application to real systems. Familiarity with first principles techniques is a plus, as is ideas on how to apply these techniques in new ways or to answer relevant materials questions. Please contact me for further information or to develop a specific project proposal.
1) "Topological surface states of MnBi2Te4 at finite temperatures and at domain walls" https://journals.aps.org/prmaterials/abstract/10.1103/PhysRevMaterials.5.024207
2) "Distinct magneto-Raman signatures of spin-flip phase transitions in CrI3" https://www.nature.com/articles/s41467-020-17320-3
3) "The joint automated repository for various integrated simulations (JARVIS) for data-driven materials design" https://www.nature.com/articles/s41524-020-00440-1
first principles; density functional theory; DFT; topological materials; materials modelling; magnetic; 2D materials; tight-binding; ferroelectrics; high-throughput