About the Project
Machine Learning Algorithm Prediction and Synthesis of Next Generation Superhard Functional Materials is an NSF-funded project that aims to discover new materials that possess the properties needed to enable the technologies of the future. Many materials have outstanding properties that make them desirable for some applications but are deficient in other properties that limit their use. A well-known example is diamond, which is the hardest known material but is also an electrical insulator. Is there a material yet to be discovered that could satisfy the need for a superhard material that also has the high electrical conductivity of a metal or other useful properties?
This project will combine diverse areas of expertise to search for new superhard materials that also possess other desirable properties that enable them to fulfill uniquely demanding technological requirements. Both three-dimensional and two-dimensional forms of these materials will be synthesized. A feedback loop between experiment and theory will be used to characterize the materials, rationally design those with desired properties, and optimize the synthesis protocols. Students will be trained in an interdisciplinary collaborative team of theoreticians and experimentalists whose expertise includes chemistry, physics, and materials science and engineering.