Master’s Thesis - Computational Materials Modeling (DFT, Python automation for high-throughput analysis)
Conducted computational and analytical work that supported experimental validation by extracting and interpreting adsorption-related results for materials research. Built and applied Python-based workflows to automate high-throughput extraction and analysis of simulation outputs in Linux/HPC settings. Focused on selecting and screening energetically favorable structures by processing computed metrics across multiple configurations. • Automated data extraction pipelines for high-throughput analysis. • Performed screening of adsorption configurations to identify favorable structures. • Ran first-principles DFT simulations and compared adsorption energies/structural stability. • Validated computational outputs against experimental data to improve predictive reliability.