README.md

---
license: cc-by-4.0
pretty_name: Magnet-Anisotropy-Screening
language:
- en
size_categories:
- 1K<n<10K
task_categories:
- tabular-regression
- tabular-classification
task_ids: []
tags:
- chemistry
- materials-science
- magnetism
- permanent-magnets
- magnetocrystalline-anisotropy
- DFT
- crystal-structure
- rare-earth-free
- tabular
- science
configs:
- config_name: default
  data_files:
  - split: train
    path: magnet_screening.parquet
---

# Magnet-Anisotropy-Screening

A calibrated screening dataset of computed magnetocrystalline anisotropy for uniaxial rare-earth-free inorganic crystals: **3,573 screened structures, 2,242 anisotropy labels** (2,044 flagged reliable), with relaxed structures for 88% of labeled entries and a **287-compound high-accuracy calibration tier that quantifies the per-label error**.

Magnetocrystalline anisotropy is the property that makes a permanent magnet hard, and it is absent from every large public materials database because computing it requires fully-relativistic density functional theory. Each label here carries the anisotropy constant K1, saturation magnetization Ms, the dimensionless magnetic hardness κ = √(K1/µ₀Ms²), and the easy-axis direction, alongside Curie temperature, hull stability, and, for gate-passing compounds, micromagnetic energy-product estimates over 2,000 sampled microstructures.

Full technical report (17 figures, methods, validation): **[A Calibrated Screening Dataset of Magnetocrystalline Anisotropy for Rare-Earth-Free Magnet Discovery](https://www.ghost-projects.tech/project-014/magnet-anisotropy-dataset/)**

## At a glance

| | |
|---|---|
| Rows | 3,573 screened structures |
| Anisotropy labels | 2,242 (2,044 κ-reliable) |
| Relaxed structures | 2,787 P1 CIFs, record-linked (88% of labeled rows) |
| Materials Project provenance | 1,958 rows carry `mp_id` (spot-verified against the live MP API) |
| Calibration tier | 287 compounds recomputed at tightened DFT settings |
| Format | Apache Parquet (main table, 41 columns) + CSV, JSONL, CIF |
| Coverage | 60 elements, 72 space groups, 3 uniaxial crystal systems |
| License | CC-BY-4.0 |

## Quick start

```python
from datasets import load_dataset

ds = load_dataset("willgbryan13/magnet-anisotropy-screening", split="train")
row = ds[0]
print(row["record_id"], row["composition"], row["kappa_corrected"], row["easy_axis"])
```

Or directly with pandas:

```python
import pandas as pd

df = pd.read_parquet("magnet_screening.parquet")
reliable = df[df.kappa_reliable & ~df.k1_outlier.astype(bool)]
hard = reliable[(reliable.kappa_corrected > 1) & (reliable.easy_axis == "001")]
print(len(reliable), "reliable labels;", len(hard), "easy-axis hard compounds")
```

## The error model

The distinguishing feature of this dataset is that its noise floor is measured. A stratified subset of 287 compounds was recomputed at tightened DFT settings (k-spacing 0.16 → 0.10 Å⁻¹, plane-wave cutoff 65 → 80 Ry), and the comparison separates the label error into a bias and a scatter:

- The systematic bias is small and corrected: per-κ-band median corrections of ×1.00 to ×0.96 are applied in the shipped `kappa_corrected` and `K1_corrected_J_per_m3` columns.
- The per-label scatter is the dominant error: in the magnet-relevant bands the interquartile range of the refinement ratio is [0.84, 1.05] (~±16% robust one-sigma), with 48% of labels within ±10% of their refined value.
- In practice, a regression model trained on these labels cannot be validated below a ±15–20% error floor on κ, because the labels themselves move that much under convergence refinement.
- Absolute magnitudes are zero-temperature DFT values, ~1.5–2× room-temperature experiment for hard magnets (the well-documented DFT↔experiment MAE gap).

The calibration pairs ship in `data/calibration.jsonl` as a held-out gold tier for uncertainty-aware training.

## Files

| File | Contents |
|---|---|
| `magnet_screening.parquet` | main table, 3,573 rows × 41 columns |
| `data/magnet_screening.csv` | same table, CSV |
| `data/screening_records.jsonl` | complete nested per-record pipeline output |
| `data/relaxed_cifs.tar.gz` | 2,787 relaxed structures (P1 CIF) + manifest linking `record_id` → file |
| `data/calibration.jsonl` | 287-compound high-accuracy calibration tier |
| `data/calibration_summary.json` | per-band corrections and scatter statistics |
| `data/METHODS.md` | full parameter-level provenance |
| `data/validation_table.md` | computed vs literature K1 for canonical hard magnets |
| `summary_stats.json` | machine-readable dataset statistics |

## Schema

Key columns of `magnet_screening.parquet` (full dictionary with units in `data/METHODS.md`):

| Column | Type | Description |
|---|---|---|
| `record_id` | str | stable identifier, `mag-00001` … `mag-03573` |
| `mp_id` | str | Materials Project id of the source structure (1,958 rows; null for off-database variants and ambiguous polymorph pulls) |
| `composition` | str | reduced chemical formula |
| `source` | str | provenance tag: mp_broad / substitution / template / ordered / generated / doping |
| `verdict`, `stopped_at` | str | cascade outcome and the stage that ended it |
| `actual_space_group`, `actual_crystal_system` | str | symmetry of the relaxed cell |
| `a, b, c, alpha, beta, gamma, volume_A3` | float | relaxed lattice parameters (Å, °, ų) |
| `e_above_hull_meV` | float | hull distance, meV/atom |
| `Tc_K` | float | Curie-temperature estimate, K |
| `Ms_A_per_m` | float | saturation magnetization, A/m |
| `K1_J_per_m3`, `kappa`, `easy_axis` | float, float, str | anisotropy label at production settings; easy axis 001 = axis, 100/010 = plane |
| `kappa_corrected`, `K1_corrected_J_per_m3` | float | per-band convergence-corrected labels, recommended for downstream use |
| `easy_axis_confidence` | float | 1 − per-band axis↔plane flip rate |
| `kappa_reliable` | bool | False where the Ms→0 artifact inflates κ |
| `k1_outlier` | bool | extreme-value flag; recompute at refined settings before use |
| `fm_assumption_risk` | bool | ferromagnetic-alignment assumption plausibly overestimates Ms |
| `peak_BHmax_kJ_per_m3`, `peak_Br_T`, `robustness_score` | float | microstructure-sweep ceilings (gate-passing rows only) |

## Quality control

- Every record relaxed (Orb-v3) before labeling; unphysical cells (nearest-neighbor < 1.5 Å) rejected
- κ artifacts from near-compensated moments flagged (`kappa_reliable`, 198 labels)
- Extreme single-shot values flagged (`k1_outlier`, 165 labels)
- Ferromagnetic-alignment risk flagged (`fm_assumption_risk`, ~50% of rows, consistent with an oxide-heavy set)
- Rejected candidates retained with valid labels as negative examples (easy-plane, soft, metastable)
- `mp_id` provenance spot-verified against the live Materials Project API (12/12 sampled ids resolve to the same reduced formula)

## Distribution snapshots

| | |
|---|---|
| Sources | mp_broad 2,013 / substitution 1,101 / template 367 / ordered 57 / generated 30 / doping 5 |
| Crystal system (labeled) | trigonal 1,062 / tetragonal 793 / hexagonal 343 |
| Easy axis (reliable) | 001 966 : in-plane 1,078 (nearly even) |
| κ_corrected (reliable, p5/p50/p95) | 0.16 / 1.22 / 5.9 |
| Ms (reliable, min/median/max) | 0.10 / 0.46 / 1.84 MA/m |
| Hull distance | 67% of reliable labels within 100 meV/atom |
| Elements | O 825 / Mn 741 / Fe 672 / Cr 414 / Co 272 lead; no lanthanides (uncomputable by construction) |

## Considerations for using the data

**Biases and limitations.**

- Uniaxial crystal systems only (tetragonal, hexagonal, trigonal); no cubic anisotropy data.
- Ferromagnetic alignment is assumed throughout; true ground-state orderings are not resolved, only flagged. Magnetization-derived figures are upper bounds where `fm_assumption_risk` is set.
- Labels are single calculations at screening settings with the quantified per-label uncertainty above; treat this as a screening/ML dataset, not a reference database.
- Curie temperatures and exchange stiffness are method-level estimates and typically run high.
- Rare-earth compounds are absent by construction: the fully-relativistic pseudopotential set behind the anisotropy stage contains no lanthanides. This matches the dataset's purpose (rare-earth-free discovery). Precious-metal compounds are included as high-anisotropy positives.
- Chemistry is Fe/Mn/O-heavy; nickel-rich uniaxial magnets are intrinsically scarce.

**Out-of-scope.** Cubic magnets, rare-earth magnets, 2D materials, noncollinear or temperature-dependent anisotropy, and experimental coercivity (the microstructure sweep is a proxy model).

## Provenance

Screening cascade: Orb-v3 relaxation → symmetry gate → convex-hull stability → Curie temperature and magnetization → TB2J magnetic-interaction extraction over ABACUS DFT (PseudoDojo fully-relativistic norm-conserving pseudopotentials, k-spacing 0.16 Å⁻¹, cutoff 65 Ry; calibration tier at 0.10 Å⁻¹ / 80 Ry) → micromagnetic microstructure sweep (2,000 Latin-hypercube samples per gate-passing compound). Roughly 2,900 anisotropy calculations over an eight-day screening period in June 2026. Property calculations ran as hosted routes on [Ouro](https://ouro.foundation). Full parameters in `data/METHODS.md`.

## Citation

If you use this dataset, please cite it (a `CITATION.cff` file is provided alongside this card) and the Materials Project for entries carrying an `mp_id`.

```bibtex
@misc{bryan2026magnetanisotropy,
  author = {Bryan, Will and Moderwell, Matt},
  title  = {Magnet-Anisotropy-Screening: a calibrated magnetocrystalline-anisotropy
            dataset for rare-earth-free magnet discovery},
  year   = {2026},
  url    = {https://huggingface.co/datasets/willgbryan13/magnet-anisotropy-screening},
  note   = {ghost-projects, Project 014. v1.0}
}
```

Companion work: [GPSK-300](https://www.ghost-projects.tech/project-014/gpsk-300/) (structure generation) and the [GPSK-Inorganic-Crystals](https://huggingface.co/datasets/willgbryan13/gpsk-inorganic-crystals) corpus.

## License

Released under **CC-BY-4.0**. Source structures from the Materials Project retain their identifiers in the `mp_id` column; see `LICENSE` for attribution terms.