This project introduces students to modern computational chemistry techniques through a hands-on exploration of molecules and materials. Participants will carry out conformational analysis using semiempirical and density functional theory (DFT) methods, predict vibrational spectra, and investigate crystal structures. A key focus will be the comparison of theoretical results with experimental data, allowing students to critically assess the accuracy of different computational approaches and understand their practical applications. By the end of the project, students will have completed a full workflow — from exploring molecular conformations to interpreting spectra and crystal packing — gaining practical experience with quantum-chemical software, semiempirical models, and theory–experiment correlation.
Tasks
- Perform conformational search with CREST and analyze results with Python.
- Optimize geometries and calculate vibrational spectra using ORCA.
- Compare theoretical spectra with experimental data (scaling, peak assignment).
- Model and relax the crystal structure with Quantum ESPRESSO.
- Visualize and interpret results
- Summarize findings in a short scientific report and presentation.
Preliminary schedule by topics/tasks
Week 1: Project introduction, software setup (CREST, ORCA, QE, Python), molecular structure preparation
Week 2: Conformational search with CREST, Python analysis of conformer ensemble
Week 3: Geometry optimization and frequency calculations with ORCA
Week 4: Spectral comparison with experiment
Week 5: Crystal structure modeling and relaxation with Quantum ESPRESSO
Week 6: Integration of results, preparation of report and presentation
Required skills
- Confident computer literacy
Acquired skills and experience
- Basic knowledge of quantum chemistry
- Introductory experience with Python (NumPy, Pandas, Matplotlib)
- Understanding of molecular structure and spectroscopy fundamentals
- Familiarity with Linux command line and basic scripting
Recommended literature
1. Bursch, M., Mewes, J.-M., Hansen, A., & Grimme, S. (2022). Best-Practice DFT Protocols for Basic Molecular Computational Chemistry. Angewandte Chemie International Edition, 61(42), e202205735. https://doi.org/10.1002/anie.202205735
2. Materials modelling using density functional theory :properties and predictions · F. Giustino · Published 2014 · Materials Science, Physics.
