Computing Resources

Our research is powered by modern computational chemistry workflows, reproducible Python pipelines, and high-performance computing resources. Students in the group gain direct experience in model setup, simulation workflows, and scientific data analysis.

Software and Methods

Electronic Structure and Molecular Simulation Analysis

  • Gaussian16
  • ORCA
  • Quantum ESPRESSO
  • CP2K
  • ASE (Atomic Simulation Environment)

Kinetics and Workflow Automation

  • Python scientific stack (NumPy, SciPy, pandas)
  • Jupyter notebooks
  • Microkinetic and reaction-network analysis scripts

High-Performance Computing

  • In-House Linux-based cluster workflows
  • ACCESS allocations (Bridges-2)
  • SLURM-based batch job submission

Student Training Focus

  • Building robust computational models with physically meaningful assumptions
  • Interpreting reaction energetics, kinetics, and mechanism trends
  • Writing reproducible scripts for data analysis and visualization
  • Communicating computational findings to experimental collaborators

Last updated: July 2026