Computational microstructure physics group
Our mission is to computationally discover atomic-scale phenomena that will help in engineer materials for targeted applications. For this purpose, our team utilizes atomistic simulations, phase-field modeling and machine learning algorithms to examine a broad category materials and phenomena. This requires us to employ concepts at the intersection of Materials Science, Condensed Matter Physics, Chemistry & Micromechanics.
Research highlights
Research highlights
In-liquid nucleus captured using unsupervised machine learning
In-liquid nucleus captured using unsupervised machine learning
Vibrational trajectories of a benzene-di-carboxylate ligand within a MOF at 300K
Vibrational trajectories of a benzene-di-carboxylate ligand within a MOF at 300K
Dislocation core structure in a BCC alloy at 1000K
Electron charge density around a hydrolyzed quartz defect site
Deep Choudhuri, Associate Professor
Department of Materials and Metallurgical Engg., New Mexico Tech
Office: Jones 116
Office Phone: 575-835-5465