Create, run, and analyze simulations. Manage data and utilize computing resources.
Computational Materials Science (CMS) is an interdisciplinary field that involves defining problems through the creation or selection of models for material systems of interest, formulating system representations (from atoms to continuum), selecting methodologies/algorithms (e.g., DFT, MD, Phase-field, or FEM) to solve problems, and implementing models on various computing systems.
Typical CMS activities include preparing inputs, managing and analyzing outputs, interpreting results, accelerating discoveries, and optimizing specific targets or processes as needed.
xyz, cif, pdb, POSCAR, data.inrun.in, INCAR, inp, POTCARopi, parameters.in, txtinp, mphlog, out, xml, OUTCAR (energy, forces, stress tensors)dump, xtc (structural evolution)WAVECAR, CHGCAR, cube (wavefunctions and charge density)"Run an EOF simulation on the perovskite KNbO3"
"List candidates of dielectric materials for TFET NVM"
"Identify the most efficient catalysts and visualize the HER process at the atomic scale"
rag.py: query contents using RAGrun_simulations.py: main engines for running simulationsanalysis.py: analyze output data to provide insights