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Presenter: Kaiden Boisjolie

Faculty Sponsor: James Walsh

School: UMass Amherst

Research Area: Chemistry and Materials Science

Session: Poster Session 4, 2:15 PM - 3:00 PM, Auditorium, A31

ABSTRACT

The scientific pursuit of materials discovery has significant potential to revolutionize technology through the development of new materials with superlative properties, such as spin-liquid behavior, superconductivity, and platinum-like catalysis. The development of these material properties has vast implications across a range of applications, such as nuclear fusion, energy storage, and quantum computing. Promising materials might be found in the indium–carbon system, which currently has no known phases. This is unfortunate, as a compositionally similar material, indium nitride, has notable semiconducting behavior. Despite this possible significance, the search for stable or metastable binary-phase indium carbide has remained unexplored. Using computational methods, this research aims to determine the possibility of stable phases in this system. The method of density functional theory (DFT) with ab initio random structure search (AIRSS) is used to explore the phase space of this material for phases with thermodynamic stability. Machine-learned interatomic potentials, specifically using ephemeral data derived potentials (EDDPs), are trained on DFT data to reduce the computational cost of geometry optimization, allowing for the exploration of low-symmetry In–C phases. Lastly, phonon-dispersion calculations are used to test for dynamical stability. This will produce a good understanding of the feasibility of synthesizing phases in the In–C system, and will direct further theoretical, and possibly experimental research into a new class of materials.