| Type | Group | Date | Project | Link | |
| MD | Rafael Gomez-Bombarelli | 2026-08-14 15:15 | Flow matching for accelerated simulation of atomic transport in crystalline materials | same cell |
| Material | Family | Role(s) | Ion |
|
4,186 lithium solid-electrolyte candidate structures
· LiFlow benchmark dataset
25-ps MD trajectories at four temperatures
|
Li solid-electrolyte candidate set
Other · as named
|
Electrolyte | Li |
| Li6PS5Br · Argyrodite |
Argyrodite
Inorganic SE
|
Electrolyte | Li |
| Li3PS4 · Thiophosphate glass-ceramic |
Sulfide glass / glass-ceramic
Inorganic SE
|
Electrolyte | Li |
Declared for sample 2025_JunoNam_RafaelGomezBombarelli_Nat.Mach.Intell._s42256-025-01125-4 — shared by every dataset on this sample.
| Model Name | LiFlow v0.1.0 |
| Model Type | Universal dataset: MACE-MP-0 small model NVT MD (pre-trained on DFT data). AIMD reference (LPS): DFT/VASP . AIMD reference (LGPS): DFT/VASP. Not a traditional MLIP — LiFlow learns displacement distributions, not energies/forces |
| Visibility | public |
| Publication Doi | 10.1038/s42256-025-01125-4 |
| Institution Code | ESRA |
| Target Properties | conditional distribution of atomic displacements ; LiFlow predicts displacements (not energies or forces) |
| Dft Training Level | Universal dataset: PBE (from MACE-MP-0)AIMD reference (LGPS/LPS): PBE |
| Training Dataset Name | Universal MLIP dataset: 4,186 Li-containing structures × 4 temperatures × 25 ps NVT MD trajectories (MACE-MP-0); 153 GB on Zenodo. Also: LPS AIMD dataset and LGPS AIMD datase |
| Training Dataset Size | 3,767 trajectories (90% of 4,186; composition-based train/test split); validation set sampled from training portion. Up to ~16,744 total trajectories (4 temperatures) |