Physics-informed neural networks (PINNs) for forward simulation and inverse parameter estimation in 2D martensitic phase transformations.

GPU-accelerated AI for solid-state battery materials discovery — GNN property prediction, graph diffusion DDPM, DeepMD MLMD, and NVIDIA ALCHEMI BCS/BMD NIM integration on NREL Kestrel H100

Interactive physics simulation of rigid and elastic pendulums. Features real-time material stress analysis, Young's Modulus dynamics, and structural breaking points.

Molecular dynamics simulations using LAMMPS and OVITO (Beginner)

Public overview of NOVA, an early-stage ICME design study on advanced Ni-based ODS superalloys for nuclear IV GEN and high-temperature applications.

Numerical implementation of the Phase-Field method using the finite volume approach in Python (FiPy). Includes 1D Allen–Cahn simulations to simulate solidification as a non-conserved order parameter evolution and 1D/2D Cahn–Hilliard simulations for conserved concentration dynamics in the spinodal decomposition of Ni–Al binary system.

Atomistic simulation of Cu in ASE with the EMT potential, including equilibrium lattice-parameter determination across SC/BCC/FCC structures, extraction of FCC elastic constants from energy–strain relations, and assessment of the strain range over which linear elasticity remains valid using NVT Langevin MD benchmarks.