---
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)

![banner](figures/banner.png)

## 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.*

![training convergence](figures/lcurve.png)

**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superseded intermediates and aren't included here.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.