Liberal Arts and Sciences
Thorpe Lab
Led by James H. Thorpe · Chemistry
What we study
The Thorpe Lab studies how artificial intelligence can be combined with high‑level quantum chemistry to model complex chemical reactions. Students use machine‑learning methods and advanced wavefunction theories (like coupled‑cluster) to predict thermochemistry, kinetics, and mechanisms for systems such as flames and organometallic catalysts.
What working here is like
- Computational
- Reading, writing & theory
- No organisms (data only)
- Coding required
- Papers
- 2
Recent papers, explained
- Reducing the Cost of CCSD Basis Set Extrapolation in Ab Initio Computational Thermochemistry
2026 · Journal of Chemical Theory and Computation
Develops cheaper ways to extrapolate CCSD basis sets for high‑accuracy thermochemistry calculations.
- Sub 20 cm
−1
computational prediction of the CH bond energy – a case of systematic error in computational thermochemistry
2023 · Physical Chemistry Chemical Physics
Creates highly accurate predictions of the C–H bond energy to assess systematic errors in thermochemical methods.
Plain-language summaries are AI-written and reviewed by us; check the paper for details.
How to reach out
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