README.md

metadata

license: cc-by-4.0
pretty_name: AI4Sci atomistic-materials v2 (universal crystal potential task)
tags:
  - materials
  - interatomic-potential
  - dft
  - benchmark

AI4Sci atomistic-materials v2

Prepared data for the atomistic-materials task of T0-RSI/ai4sci-tasks: develop one universal crystal potential that stays MP-compatible and accurate far from equilibrium.

• pool/: training pool in ASE-LMDB shards, one directory per source: MPtrj, sAlex, MatPES-PBE, and a 35 % shard sample of the OMat24 training subsets. Every composition and parent ID of an evaluation material is removed. pool/manifest.json lists every file.
• archives/val.tar, archives/test-inputs.tar, archives/test-references.tar: validation and test splits of eight suites:
  • WBM discovery, MDR phonons, MP elasticity;
  • PhononDB κ, MOFSimBench bulk moduli, AM26 amorphous energies and forces;
  • cleavage energies, LiTraj nebDFT2k barriers.
• archives/models.tar: UMA-S-1.1 and two fine-tuned baselines (FAIR Chemistry License and Acceptable Use Policy).
• archives/baselines.tar: the original task's 500k MPtrj + sAlex fine-tuning sample, v2-filtered.
• release-manifest.json: size and SHA-256 of every artifact.

Install with environment/data/materialize.sh release DIR from the task repository.

Licenses of the components:

• MPtrj: MIT;
• sAlex, OMat24 and the cleavage benchmark: CC BY 4.0;
• MatPES: BSD-3-Clause;
• Matbench Discovery references: MIT / CC BY 4.0;
• MOFSimBench and LiTraj: MIT;
• AM26: as published by Fragapane and Deringer (no license file at the pinned commit);
• UMA weights and derivatives: FAIR Chemistry License.

Cite the original datasets when using them.