Degree: BS, MS
Nationality: International Students
Application deadlines: Fall 2022
The CMS group, led by Prof. Tianshu Li https://www.cee.seas.gwu.edu/li-tianshu, works on a variety of materials related research topics that mainly fall under the heading of materials theory. Our goals are: 1) explain experimental data, 2) elucidate fundamental mechanisms, and 3) predict materials behaviors. We employ a variety of computational methods, with a combination of, ab initio, molecular dynamics, Monte Carlo, advanced sampling, and machine learning. Currently, our research focuses on developing theory of SiGeSn medium-entropy alloys for mid-infrared technology and understanding thermodynamics and kinetics of crystal nucleation. For further information about our research, please visit https://blogs.gwu.edu/tsli/research/
- One position is expected to work on method development and implementation for modeling crystal nucleation. The CMS group is working closely with another team at UC Davis to deploy a LAMMPS based, large-scale computational suite that integrates advanced sampling methods to model crystal nucleation and growth under realistic conditions. The infrastructure will enable broad applications in materials synthesis, surface engineering, membrane fouling, and inorganic mineralization. Representative publication: https://www.nature.com/articles/ncomms15372
- The other position is expected to work on understanding the fundamental structures and properties of Si-Ge-Sn alloys. The CMS group is collaborating with experimentalists in other institutions to deploy next generation materials for mid-infrared applications including sensing, security, and autonomous vehicles. We are particularly interested in developing theory of short-range chemical order in medium-entropy alloy and high-entropy alloy. Representative publication https://pubs.acs.org/doi/abs/10.1021/acsami.0c18483
- The qualified applicants should have a good GPA for admission and a strong interest in molecular modeling and theory. Experience in coding using C++, Python, and/or other computer languages under Unix/Linux environment is strongly preferred.
Interested candidate should send CV and transcript to Dr. Li ([email protected])