Herbert Wertheim College of Engineering
McDevitt Lab
Led by Chris McDevitt · Materials Science and Engineering
What we study
The McDevitt Lab studies fusion plasmas using computer models. They focus on tokamak disruptions, runaway electrons, and plasma turbulence.
What working here is like
- Computational
- No organisms (data only)
- Coding required
- Papers
- 5
Recent papers, explained
- Physics-informed neural network for rapid ion trajectory prediction in ion-etch reactors
2026 · Physics of Fluids
Uses a physics-informed neural network to quickly model plasma sheaths in semiconductor manufacturing.
- An adjoint formulation of energetic particle confinement
2026 · Journal of Plasma Physics
Uses a neural network to predict how fast ions escape in tokamak reactors.
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- A deep learning approach to describing the plasma sheath
2026 · Plasma Sources Science and Technology
Uses a neural network to model the plasma sheath without needing experimental data.
- An efficient surrogate model of secondary electron formation and evolution
2025 · Physics of Plasmas
Extends a deep learning model to track runaway electrons and their secondary collisions in plasmas.
- A runaway electron avalanche surrogate for partially ionized plasmas
2025 · Nuclear Fusion
Develops a physics-constrained deep learning model to predict runaway electron growth in tokamak disruptions.
Plain-language summaries are AI-written and reviewed by us; check the paper for details.
How to reach out
Chris McDevitt hasn't set up this page yet. You can also look them up in the UF directory (search “Chris McDevitt”).