Meet Dillon Yost

Advisor: Jeffrey C. Grossman

Institution: Massachusetts Institute of Technology

Bio: Dr. Dillon C. Yost is an Intelligence Community Postdoctoral Research Fellow at the Massachusetts Institute of Technology, where he is advised by Professor Jeffrey Grossman. His intelligence community advisor is Dr. Paul Kolb at IARPA. Dillon earned a bachelor’s degree with honors in chemistry and mathematics from Berry College in 2014. He then attended the University of North Carolina – Chapel Hill where he was an NSF graduate research fellow, earning his Ph.D. in physical chemistry in 2019 under the direction of Professor Yosuke Kanai. His research interests cover a wide array of topics in computational materials science including electronic structure theory, first-principles electron dynamics simulations, and machine-learning aided materials design.

Abstract: Sophisticated surveillance capabilities, combined with the ever-increasing reliance on wireless communication, presents many challenges for information security. For secure locations where sensitive information may be handled, there is a need for materials that can selectively absorb in certain frequency ranges of the electromagnetic (EM) radiation spectrum. These materials could be used as window coatings that are visibly transparent and are simultaneously capable of preventing surveillance attempts, electromagnetic interference (EMI), and unauthorized transmission of information. With this need for tunable electromagnetic absorption, 2D materials such as graphene, transition metal dichalcogenides (TMDs), phosphorene, and others, show great potential. We research the rational design of 2D materials for ensuring information security through the application of high-throughput atomistic simulations performed on high performance supercomputers. Using real-time time-dependent density functional theory (RT-TDDFT) and the Kubo-Greenwood method for electrical conductivity, we calculate both the optical and dc conductivity for a given chemical structure. This computational approach has allowed us to screen over 2,000 unique materials, a much larger chemical space than what is accessible via experiments. We are identifying trends that help us to understand the complex physics and chemistry at play. Additionally, we are proposing novel 2D material candidates that could offer simultaneously higher transparency and EMI shielding efficiency than the current state-of-the-art.