Developing Battery Materials with Python
summary
Shows how density functional theory produces quantitative energies used to predict battery metrics, gives the explicit equilibrium‑voltage formula requiring three DFT calculations, and demonstrates a runnable Python workflow of ~25 lines of code that computes lithium energies and derives energy density, specific capacity and electronic‑structure plots. Performance numbers appear: small systems of ~10 atoms run in ~20 minutes on a laptop, while nanoclusters of a few hundred atoms require supercomputer resources. The lithium‑oxygen model is built and evaluated end‑to‑end with those results.
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chapters (11)
- 0:00Introduction
- 0:28Density functional theory
- 1:32DFT for computer science
- 4:02Quantum mechanics in matter
- 5:26Schrödinger’s equation problem
- 10:31How density functional theory solves the problem
- 14:46DFT importance recap
- 16:10DFT for battery materials
- 19:00Python tools for DFT
- 21:04Live battery analysis
- 22:29Q&A
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