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license: cc-by-4.0 # TODO: confirm — placeholder, common choice for open MLIP releases (e.g. MACE-OFF/MACE-MP). Change if you want something else.
tags:
- deepmd-kit
- molecular-dynamics
- interatomic-potential
- materials-science
- battery-materials
- cathode-material
- layered-oxide
- lithium-ion-battery
- nmc
---
# NMC622 — LiNi₀.₆Mn₀.₂Co₀.₂O₂ Cathode (DeepMD)
## What this is
DeepMD-kit potentials for **NMC622** (LiNi₀.₆Mn₀.₂Co₀.₂O₂), a layered-oxide
Li-ion cathode material — one of the most widely used commercial cathode
chemistries, here used to study Li-ion diffusion in the layered structure.
## Transport properties
| | AIMD | MLMD (DeepMD) |
|---|---|---|
| D (Li⁺, cm²/s) | 9.0×10⁻¹² | 2.58×10⁻¹¹ (300K) / 5.12×10⁻¹¹ (600K) |
| Eₐ (eV) | 0.34 | 0.035 |
Mechanical: E = 200 GPa, ν = 0.30, ρ = 4.7 g/cm³.
## Files & Validation
| File | RMSE energy (eV/atom) | RMSE force (eV/Å) | Training steps | Size |
|---|---|---|---|---|
| `model/nmc622_production.pb` | 0.00239 | 0.166 | 1,000,000 | 450.6 MB |
| `model/nmc622_model1.pb` | 0.00226 | 0.178 | 1,000,000 | 407.6 MB |
*RMSE values are validation-set (held-out) energy/force error, read directly from each run's DeepMD-kit `lcurve.out` at its final training step — not re-derived or estimated.*
**2 of 3** current production potentials, the pair with the lowest
validation force RMSE; several earlier iterations (6k/11k/22k-atom
cell-size scans, memory-optimization variants) exist in the source tree as
superseded intermediates and aren't included here.
## Training pipeline
AIMD random-structure sampling (VASP, PBE, 500K) → DeepMD-kit train/freeze/
compress. Produced by HPCA (github.com/selvachandrasekaranselvaraj/hpca).
## Citation
Selva Chandrasekaran Selvaraj, University of Illinois Chicago. Continuum
transport model parameters per Ncube et al. 2026.
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