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

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

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.

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.

Molecular dynamics simulations using LAMMPS and OVITO (Beginner)

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.