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README.md

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+---
+license: cc-by-4.0
+pretty_name: "Crystal-RL: surrogate-vs-DFT effective-mass gap (negative-result dataset)"
+tags:
+  - materials-science
+  - effective-mass
+  - dft
+  - quantum-espresso
+  - jarvis
+  - reinforcement-learning
+  - surrogate-model
+  - negative-results
+  - methodology
+  - tabular
+task_categories:
+  - tabular-regression
+  - tabular-classification
+language:
+  - en
+size_categories:
+  - n<1K
+configs:
+  - config_name: bootstrap_signed_mstar
+    data_files: "data/bootstrap_signed_mstar.parquet"
+    default: true
+  - config_name: surrogate_dft_pairs
+    data_files: "data/surrogate_dft_pairs.parquet"
+---
+
+# Crystal-RL: surrogate-vs-DFT effective-mass gap
+
+Two related tables from the [`crystal-rl`](https://github.com/bshepp/crystal-rl)
+materials-discovery project:
+
+1. **`bootstrap_signed_mstar`** — 794 Quantum ESPRESSO DFT calculations on
+   perturbed semiconductor crystal structures, with **signed** effective
+   mass values (681 negative, 113 positive). Signed-m\* DFT data is rare:
+   JARVIS, Materials Project, and AFLOW all store magnitudes only, which
+   destroys the sign that distinguishes band-inverted from normal-curvature
+   bands. This subset is the primary reusable artifact for anyone training
+   signed-m\* surrogate models.
+
+2. **`surrogate_dft_pairs`** — 24 surrogate-prediction-vs-DFT-truth pairs
+   across three independent RL+surrogate validation rounds. This subset
+   exists to support a methodological claim: **across three independent
+   pipeline variants** (unsigned-m\* baseline, signed-m\* with bootstrap data
+   absent, signed-m\* with bootstrap data loaded), **zero of 24 surrogate-
+   selected candidates DFT-validated as low-positive-effective-mass
+   semiconductors**. 19 of 24 instead showed negative DFT band curvature
+   (band-inversion signature). The dataset is published so other groups can
+   study the gap directly.
+
+## Dataset summary
+
+| Subset | Records | What's in it |
+|---|---|---|
+| `bootstrap_signed_mstar` | 794 | Per-structure DFT outputs + 156-dim structural fingerprint |
+| `surrogate_dft_pairs`    |  24 | Per-candidate surrogate prediction *and* DFT measurement |
+
+Both subsets load with the standard 🤗 Datasets library:
+
+```python
+from datasets import load_dataset
+
+# Default config (the bootstrap table)
+boot = load_dataset("bshepp/rl-surrogate-dft-gap", split="train")
+
+# Explicit subset
+pairs = load_dataset("bshepp/rl-surrogate-dft-gap",
+                     "surrogate_dft_pairs", split="train")
+```
+
+## Subsets
+
+### `bootstrap_signed_mstar` (794 rows)
+
+Effective-mass + band-gap DFT outputs for 794 perturbed semiconductor
+structures, plus the 156-dimensional structural fingerprint used by the
+`crystal-rl` surrogate. Generated on AWS EC2 (`c5.4xlarge`) in February
+2026 over 4 rounds of bootstrap exploration starting from 10 seed
+families (Si, Ge, C-diamond, GaAs, AlAs, InAs, GaP, SiC-3C, InP, AlN).
+
+| Column | Type | Description |
+|---|---|---|
+| `row_id` | int64 | Stable record index (0..793). Matches the row index in the source `bootstrap_expanded_all.json`. |
+| `seed` | string | Seed family the structure was derived from (e.g. `"Si"`, `"GaAs"`). |
+| `label` | string | Free-form provenance label from the bootstrap pipeline. |
+| `formula` | string | Chemical formula of the final structure (e.g. `"As2Ga2"`). |
+| `dft_m_electron` | float64 | Signed electron effective mass at the conduction band edge (mₑ units). Negative ⇒ negative band curvature (band inversion). |
+| `dft_m_hole` | float64 | Signed hole effective mass at the valence band edge (mₑ units). |
+| `dft_m_min_signed` | float64 | Smallest-magnitude effective mass found in the band structure, **signed** by curvature. This is the canonical signed-m\* training target. |
+| `dft_band_gap_ev` | float64 | PBE band gap in eV. 0 means metallic. |
+| `dft_vbm_ev` / `dft_cbm_ev` | float64 | Valence/conduction band edge positions in eV. |
+| `is_direct_gap` | bool? | True if Γ-point gap, False if indirect, null if undetermined. |
+| `qe_runtime_seconds` | float64 | Wall-clock seconds the QE `pw.x` job took on a c5.4xlarge core. |
+| `fingerprint_156` | list&lt;float32&gt;\[156\] | 12 composition + 4 elemental property + 8 lattice + 64 RDF + 64 partial-RDF features. Composition palette: `H, C, N, O, Si, P, Ge, Ga, As, In, Sn, Al, Sb, Bi, Se, Te`. See [`qe_interface/structures.py`](https://github.com/bshepp/crystal-rl/blob/master/qe_interface/structures.py) for the exact fingerprint code. |
+
+**Signed-m\* distribution**: 681 records with `dft_m_min_signed < 0`,
+113 with `dft_m_min_signed > 0`. The skew toward negative is a property
+of which structures the bootstrap perturbation chose to retain — *not*
+of materials in general.
+
+### `surrogate_dft_pairs` (24 rows)
+
+Side-by-side surrogate prediction and DFT measurement for the top
+candidates produced by three independent RL training runs.
+
+| Column | Type | Description |
+|---|---|---|
+| `run_id` | string | One of `phase7`, `pathb_run1`, `pathb_run3`. See [Methodology](#methodology) below for what changed between runs. |
+| `formula` | string | Chemical formula of the candidate produced by the PPO agent. |
+| `seed` | string | Seed structure the agent perturbed from. |
+| `surrogate_m_star` | float64 | Surrogate's predicted effective mass for this candidate. |
+| `surrogate_reward` | float64 | PPO reward the agent received from the surrogate. |
+| `dft_m_min_signed` | float64 | DFT signed m\* of the minimum-magnitude band. |
+| `dft_m_electron` | float64 | Signed conduction-band m\*. |
+| `dft_m_hole` | float64 | Signed valence-band m\*. |
+| `dft_band_gap_ev` | float64 | PBE band gap in eV. |
+| `dft_converged` | bool | True if QE SCF + bands converged. (All 24 are True.) |
+| `dft_runtime_seconds` | float64 | Wall-clock QE time. |
+| `unusual_topology` | bool | True if DFT showed negative band curvature (band-inversion signature). |
+| `is_low_positive_semiconductor` | bool | Convenience: `dft_m_min_signed > 0 AND < 0.5 AND dft_band_gap_ev > 0.1`. **True for 0 of 24 records.** |
+
+## Methodology
+
+The `surrogate_dft_pairs` subset spans three runs of the
+`crystal-rl` pipeline:
+
+| `run_id` | Surrogate variant | What changed | Surrogate m\* corr | DFT-validated low-pos. m\* |
+|---|---|---|---|---|
+| `phase7`     | Unsigned-m\* (pre Phase-9 fix) | Original 152-dim, 12-element palette | 0.928 | 0 / 8 |
+| `pathb_run1` | Signed-m\*, palette expanded to 16, **bootstrap data accidentally not loaded** (fingerprint-dim mismatch with cached `surrogate_data.npz`) | 156-dim fingerprint, 16-element palette, Sb/Bi/Se/Te pseudopotentials registered | 0.495 | 0 / 8 |
+| `pathb_run3` | Signed-m\*, palette expanded to 16, **bootstrap data loaded** (after zero-padding the cached 152-dim fingerprints to 156-dim via `scripts/regen_bootstrap_for_palette.py`) | as above | 0.768 | 0 / 8 |
+
+The cumulative finding is **0 / 24** — the same answer regardless of the
+surrogate's accuracy on its own validation set. The 24 candidates were
+picked by three different surrogate models trained on three different
+data mixes, but the DFT outcome is consistent: surrogate-selected
+low-m\* predictions don't validate.
+
+## Source data &amp; collection
+
+- **`bootstrap_signed_mstar`** was collected by perturbing the 10 seed
+  crystal families (formula edits, lattice scaling, position
+  perturbation) and running PBE DFT (Quantum ESPRESSO 7.3.1, SSSP
+  Efficiency pseudopotentials, 30 Ry wavefunction cutoff, 4×4×4 k-points
+  for SCF, 20-point band path for the m\* extraction). Effective mass
+  was extracted from a parabolic fit to the band curvature at extrema
+  — sign-preserving. All 794 calculations converged.
+- **`surrogate_dft_pairs`** was collected by running each trained PPO
+  agent for 30 deterministic episodes, deduplicating by formula, taking
+  the top 8 by surrogate-predicted reward, and DFT-validating each. All
+  3 × 8 = 24 calculations converged.
+
+## Intended uses
+
+- **Train signed-m\* surrogates** without losing the negative-curvature
+  examples. The 681 negative records are particularly load-bearing —
+  most public datasets remove the sign.
+- **Benchmark RL-discovery pipelines** against a known failure mode.
+  If your method produces surrogate predictions that disagree
+  systematically with DFT in this same way, you're hitting the same
+  gaming dynamic.
+- **Study the surrogate-DFT calibration gap.** The `surrogate_dft_pairs`
+  subset is small (24 rows) but each pair is a controlled
+  comparison: same fingerprint, same structure, same DFT settings,
+  different surrogate.
+- **Cite the negative result.** This dataset is intentionally published
+  to make the finding citable rather than letting it die as a side
+  comment in a repo README.
+
+## Limitations &amp; what this dataset is *not*
+
+- This is **not a benchmark of "best low-m\* materials"** — the
+  candidate formulas listed in `surrogate_dft_pairs` were chosen by an
+  RL agent that turned out to game its surrogate. Treating them as
+  recommended materials would invert the intended use.
+- **PBE-level DFT.** All values are PBE outputs from Quantum ESPRESSO
+  with SSSP Efficiency pseudopotentials. PBE is known to underestimate
+  band gaps and, for some compositions, give qualitatively wrong band
+  ordering. Hybrid-functional (HSE06) or GW calculations would shift
+  some values significantly. The signed-m\* *sign* is generally robust
+  to functional choice; the magnitudes are not.
+- **Small validation cohort.** 24 surrogate-DFT pairs is a strong signal
+  for a single project but not large enough to claim a universal law
+  about RL-surrogate gaming. We report what we observed across our 3
+  runs; we make no claim about every possible surrogate architecture.
+- **Bootstrap structures cluster around 10 seed families.** They are
+  not a uniform sample of the periodic table.
+
+## Reproducibility
+
+- **Code:** [github.com/bshepp/crystal-rl](https://github.com/bshepp/crystal-rl)
+- **Pipeline:** the assembly script for this dataset is
+  [`scripts/build_hf_dataset.py`](https://github.com/bshepp/crystal-rl/blob/master/scripts/build_hf_dataset.py).
+- **Run artifacts:** the path-B runs (`pathb_run1`, `pathb_run3`) wrote
+  full per-stage logs, surrogate weights, PPO checkpoints, and
+  manifests to a private S3 bucket; they are not redistributed here
+  because they're bulky and replicable from the code. The
+  `surrogate_dft_pairs` table is the distilled scientific output.
+- **Quantum ESPRESSO version:** 7.3.1, built from source. SSSP
+  Efficiency pseudopotentials.
+- **Surrogate architecture:** `MultiTaskMLP(156 → [192 × SiLU + LN + Drop] ×
+  4 → m\* head + gap head)`, ~142k parameters, trained with two-phase
+  protocol (JARVIS+bootstrap then frozen-trunk MP gap fine-tune).
+
+## Citation
+
+```bibtex
+@misc{crystal_rl_surrogate_dft_gap_2026,
+  title  = {Crystal-RL: surrogate-vs-DFT effective-mass gap (negative-result dataset)},
+  author = {Sheppard, Brian},
+  year   = {2026},
+  url    = {https://huggingface.co/datasets/bshepp/rl-surrogate-dft-gap},
+  note   = {Companion dataset to github.com/bshepp/crystal-rl}
+}
+```
+
+## License
+
+CC-BY-4.0. Use freely, please cite.

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