| --- |
| license: cc-by-4.0 |
| tags: |
| - deepmd-kit |
| - molecular-dynamics |
| - interatomic-potential |
| - materials-science |
| - battery-materials |
| - fluoride-electrolyte |
| - coating |
| - lithium-metal-anode |
| - anion-conductor |
| --- |
| |
| # SrF₂ — Li-Metal Anode Protective Coating (DeepMD) |
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|
| ## What this is |
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|
| DeepMD-kit potentials for **SrF₂**, studied as an F⁻-conducting protective |
| coating on Li-metal anodes. Unlike the other families here, the mobile |
| species of interest is the **fluoride anion**, not Li⁺ — the coating's job is |
| to be an F⁻ conductor that physically/chemically shields the Li-metal |
| surface. |
|
|
| ## Transport properties (from this project's own AIMD/MLMD) |
|
|
| | | AIMD | MLMD (DeepMD) | |
| |---|---|---| |
| | D (F⁻, cm²/s) | 4.8×10⁻¹¹ | 5.0×10⁻¹¹ | |
| | Eₐ (eV) | 0.57 | 0.58 | |
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| Mechanical: E = 88 GPa, ν = 0.28, Ω = 19.5 ų/formula unit, ρ = 4.24 g/cm³. |
|
|
| ## Files & Validation |
|
|
| | File | RMSE energy (eV/atom) | RMSE force (eV/Å) | Training steps | Size | |
| |---|---|---|---|---| |
| | `model/srf2_aimd_run1.pb` | 0.00363 | 0.0865 | 1,000,000 | 207.1 MB | |
| | `model/srf2_aimd_run2.pb` | 0.00608 | 0.0999 | 1,000,000 | 146.6 MB | |
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|
| *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.* |
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|  |
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| **2 of 5** distinct potentials, both independent training runs against the |
| same AIMD trajectory set (`srf2_aimd_run1`/`run2`) — selected because they're |
| the only two with a preserved `lcurve.out` to validate against. The |
| large-scale production potential actually deployed for the multi-nanosecond |
| NVT/NPT interface runs (`deepmd/n_opt/mlpot.pb`) has no training log kept on |
| disk, so it's excluded from this metrics-first selection — ask if you want |
| it included anyway (unvalidated) or swapped in for one of these two. Several |
| older potentials from earlier iterations of this system are archived/ |
| superseded and also not included. |
|
|
| ## Training pipeline |
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| AIMD (VASP, PBE) → DeepMD-kit train → freeze → compress. Produced by HPCA |
| (github.com/selvachandrasekaranselvaraj/hpca). |
|
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| ## Citation |
|
|
| Selva Chandrasekaran Selvaraj, University of Illinois Chicago. |
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|
