Description: Curated multi-source DFT + experimental dataset for thermodynamic screening and benchmarking of battery-relevant inorganic materials, aggregated from Materials Project, OQMD, and JARVIS-DFT.
Storage: Parquet (dataset/entries_v3.parquet) with indexed lookup — 0.18 GB instead of 1.6 GB JSON.
Experimental data: 599 OBELiX entries integrated (Therrien et al. 2025, NRC-Mila), including 498 new experimental_gold tier entries with measured Li-ion conductivity.
Transport proxies: BVSE migration barrier proxy (bvlain engine, validated against 7 known SSEs, 5/7 pass within literature ranges). See scripts/compute_bvse_barriers.py.
Sources
Source
Entries
License
Download Date
Materials Project
69,279
CC BY 4.0
2026-07-20
OQMD
171,780
Non-commercial + attribution
2026-07-20
JARVIS-DFT
25,673
CC0
2026-07-20
License Warning
⚠️ This dataset is NOT uniformly licensed. Each entry carries its own license.
A Commercial-Safe edition (commercial_safe_subset_v3.json) containing only MP + JARVIS entries (~94,952 entries) is available for commercial use. All entries are CC BY 4.0 or CC0 1.0 licensed. Any model trained for commercial deployment should be trained on this edition.
import json
# Load commercial-safe editionwithopen("dataset/commercial_safe_subset_v3.json") as f:
entries = json.load(f)
print(f"{len(entries):,} entries — all commercial-safe")
Fields
Primary fields
Field
Type
Description
Coverage
license
str
Per-entry license tag
100%
source_id
str
Original source ID
100%
formula
str
Raw formula string
100%
structured_formula
str
Reduced formula
100%
elements
list[str]
Element symbols
100%
nsites
int
Number of atoms in cell
100%
space_group
int
International number
99.99%
space_group_symbol
str
Hermann–Mauguin symbol
99.99%
volume
float
Cell volume (ų)
100%
density
float
Density (g/cm³)
100%
formation_energy_per_atom
float
FE (eV/atom)
100%
energy_above_hull
float
EaH (eV/atom)
90.4% → 100% (JARVIS hull added)
band_gap
float
Band gap (eV)
99.94%
total_magnetization
float
Total
100%
magnetic_ordering
str
Magnetic ordering
100%
is_metal
bool
Metallic character
100%
is_experimental
bool
From experiment?
100%
families
list[str]
Material families
100%
carrier_elements
list[str]
Mobile ion carriers
100%
anions
list[str]
Anion species
100%
structure_json
str
JSON-encoded pymatgen Structure
100%
quality_score
int
Composite quality (0–88)
100%
quality_sub_scores
dict
Per-category scores
100%
quality_flags
list[str]
Quality flags
100%
tier
str
Gold / Validated / Raw
100%
tier_detail
dict
Gate pass/fail details
100%
tier_gates
dict
Per-gate results
100%
strict_gold
dict
Strict Gold pass/fail
100%
duplicate_group
int
Dedup group ID
7.9%
provenance
dict
Full provenance chain
100%
source_weight
float
Source priority weight
100%
references
list[str]
Source references
100%
SSE proxy fields (added in v0.1.0)
Field
Type
Description
Coverage
carrier_fraction
float
Fraction of mobile ion carriers
100%
volume_per_carrier
float
Volume per mobile carrier (ų)
100%
fe_per_carrier
float
Formation energy per carrier (eV)
100%
electronic_insulation
bool
Band gap > 1.0 eV
100%
sse_family
str
SSE family classification
100%
mobile_ion
str
Primary mobile ion (Li/Na/Mg)
61.1%
oxidation_states
dict
Per-element oxidation states
100%
predicted_oxidation_states_valid
bool
BVA-validated prediction?
100%
ssb_screening block (v0.2.0)
Field
Type
Description
Coverage
mobile_ion
str
Mobile ion species
61.1%
mobile_ion_fraction
float
Fraction of mobile ions
100%
sse_family
str
SSE family tag
100%
electronic_insulation
bool
Band gap > 1.0 eV
100%
thermo_stable
bool
E_hull < 0.025 eV/atom
100%
gates_passed
list[str]
SSE screening gates passed
100%
sse_candidate_score
int
Composite SSE score (0–100)
100%
cavd_channel_dimensionality
str
0D/1D/2D/3D percolation
~61%
stability_window_low_V
float
Lower stability limit vs Li/Na
~2.2%
stability_window_high_V
float
Upper stability limit vs Li/Na
~2.2%
window_width_V
float
Electrochemical window width
~2.2%
passivating_interphase
bool
Forms passivating interphase?
~14.9%
interfacial_reaction_energy_vs_Li_eV_atom
float
Decomposition energy vs Li
~14.9%
bulk_modulus_GPa
float
Bulk modulus (geometric proxy)
100%
shear_modulus_GPa
float
Shear modulus (geometric proxy)
100%
dendrite_suppression_flag
bool
Shear modulus > 6 GPa
100%
elastic_source
str
"MP_API" / "geometric_proxy" / null
100%
Intended Use
Primary: Training machine learning models for property prediction of solid-state battery materials
Secondary: Materials discovery, phase stability analysis, and computational screening
Not recommended for: Quantitative phase diagram construction (use MP/OQMD directly)
