projects / Lithium in graphitic carbon

Lithium in graphitic carbon

◆ completed 2026 python, pyscf, orca
diffusion barriers vs interlayer spacing across methods

First-principles modeling of lithium-ion batteries leans almost entirely on semilocal DFT, and inside a periodic calculation its accuracy is hard to check. This project builds a ladder of molecular stand-ins for lithiated graphite: AA-stacked aromatic bilayers from LiC20 to LiC132, with a lithium between the sheets. They are large enough to approach graphitic behavior and small enough for coupled-cluster benchmarks.

Fifteen functionals agree to about 0.1 eV on the diffusion barrier but scatter by 0.3–0.45 eV per lithium on the discharge energy, which makes the thermochemistry the more discriminating target. The largest cluster reproduces a periodic dilute-limit reference (0.617 eV) to better than 0.01 eV when both are computed with matched settings. The wavefunction side needed the most care. A spin-contaminated open-shell reference can inflate a coupled-cluster barrier by as much as 0.8 eV.

Behind the numbers sits a provenance-audited dataset of 566 calculations and 234 barriers across four campaigns, with every accepted output gated on completion and geometry checks. With Zachary Goldsmith, Hong-Zhou Ye, and Tim Berkelbach. A manuscript is in preparation.