Materials-Workbench

Package Install

Installable package: python3.11 -m pip install zer0pa-materials-workbench. Current release: 0.1.0 on PyPI. Source: Zer0pa/Materials-Workbench.

python3.11 -m pip install zer0pa-materials-workbench

For full install, smoke, source, and developer commands, click here.

---

00 · MATERIALS · INSILICO WORKBENCH RESEARCH-READY · H100 ARTIFACT OPEN Seven-Layer Physics Materials Workbench Materials lane · Materials-Workbench · PyPI zer0pa-materials-workbench v0.1.0 stale · github.com/Zer0pa/Materials-Workbench Materials Workbench is a CPU-side bench for in-silico battery and thermoelectric research. Candidate chains arrive with schemas, validators, recompute checks, and dispatch wired together, so weak chemistries are rejected at the desk before they consume cluster hours. 3,547 strict-full tests pass and 588 Runpod-sim parity tests hold; the H100 campaign is the next wave, not the current result. Real GPU evidence is not claimed yet.

Scope: CPU-side materials workbench. Schemas, validators, recompute, and Runpod-sim parity pass; real H100 evidence is next.

01 · THE GAP SPLIT WORKFLOWS “Most candidate chemistries reach the cluster before anyone has really vetted them.”

02 · MARKETS WORKFLOW FIT Battery R&D groups fit Materials informatics teams primary Thermoelectric R&D groups fit Industrial AI / MLIP teams fit DFT / solver groups adjacent Workflow-fit hypotheses for a CPU pre-screen bench; not adoption, not TAM, not a discovery claim.

03 · VALUE OF MARKET CPU-side bench Best fit: materials informatics, battery, thermoelectric, and industrial AI teams that need pre-HPC candidate checks.

04 · INSIGHT Reject weak materials chains before any GPU runs them.

05.0 · CURRENT TECH SPECIALIZED SOLVERS, SPLIT HANDOFF Today's stack threads DFT, phonons, MLIP, CALPHAD, phase-field, provenance, and lab automation through separate specialised tools. The gap is not a missing solver. It is a shared candidate record that lives before H100 spend.

05.1 · OUR TECH RAW-EVIDENCE RECOMPUTE Materials Workbench at Zer0pa/Materials-Workbench is an installable alpha that holds schemas, validators, seven recompute checks, packet records, Runpod dispatch, and an H100 cutover path in one CPU-side bench. Battery and thermoelectric candidates run the same pre-screen on a laptop today that they will run against real GPU artifacts in the H100 wave.

05.2 · BENCHMARKS POST-WAVE-F · CPU + RUNPOD-SIM Tests3,547strict-full PASS Parity588Runpod parity tests Recompute7raw-evidence checks Stress cases16plus 7 checks CPU strict 3,547/3,547 Runpod parity 588/588 H100 evidence pending Current status: 16/16 stress cases caught · 7 recompute checks hardened · no real GPU-backed runpod_rest artifact yet.

06 · MEASUREMENT RECOMPUTE + HASH HISTORY 7 recompute checks, 16 stress cases, hash history over every chain.

06.1 · COMPARATIVE PERFORMANCE · CPU WORKBENCH VS GPU CAMPAIGN CPU strict-full 3,547 / 3,547 PASS Runpod parity 588 / 588 PASS H100 real artifact campaign pending DFT/MLIP comparator not yet measured CPU strict-full and Runpod-sim parity hold today. H100 is the next campaign — no real GPU result has been produced yet. DFT/MLIP comparator parity sits outside the CPU bench.

07 · KEY METRICS MATERIALS-WORKBENCH POST-WAVE-F

07.1 · CPU STRICT CHECK 3,547/3,547 Strict-full pass · 2 pycalphad skips, 0 misses

07.2 · RUNPOD PARITY 588PASS Runpod parity tests · mock results blocked from posing as real

07.3 · RECOMPUTE CHECKS 7hardened Raw-evidence recompute · inputs, sources, novelty, ionic, NEB stages

07.4 · STRESS CASES 16/16 Replay-error breaches plus recompute checks · 0 misses

07.5 · GPU EVIDENCE null Metric pending · no real GPU result produced yet

08 · DETERMINISM RECOMPUTE BEFORE GPU Every chain replays on CPU before any GPU touches it.

08.1 · WHAT DETERMINISTIC MEANS RAW-EVIDENCE RECOMPUTE The seven recompute checks take a candidate chain's outputs and re-derive every layer's hash from inputs. Any divergence rejects the chain; only chains that survive the recompute move forward. The discipline runs today on CPU and on the Runpod-sim parity surface (3,547 strict-full + 588 parity). The H100 wave will run the same checks against real GPU artifacts. The unit of bit-exactness is per-chain, per-layer-hash.

08.2 · THE FIDELITY GAP Honest Blocker · No real GPU-backed runpod_rest artifact has been produced. Discovery of any material is not claimed. Public PyPI v0.1.0 is live but stale pending v0.1.1. License is SAL-7.1 / GitHub NOASSERTION; UMA/HF org, Materials Project credential, real endpoints, and EMMO cleanup remain open.

09 FIVE PATHS FROM ONE PRE-GPU BENCH.

09.1 · THIS REPO'S AMBITION The hinge is not one chemistry result. It is a bench where candidate generation, validators, constraints, and run history travel together from a researcher's laptop to a GPU cluster. If that path survives H100 completion, materials exploration becomes something other teams can repeat, compare, and contest.

09.2 · WHAT WORKS NOW Working now: candidate-bench architecture, validation route, CPU and Runpod-sim parity, H100 completion target.

09.3 · WHAT'S STILL OPEN Still open: H100 execution, real GPU artifact, candidate data, release evidence, and source context.

09.4 · LAB BUDGETS · NEAR-TERM (12–24 MO) Weak chemistries die at the desk A battery research lead can spend a Monday morning killing forty candidate chains on a laptop instead of carrying them into a Friday cluster reservation. The H100 queue starts holding fewer candidates that nobody really believed in.

09.5 · INFORMATICS · NEAR-TERM (12–24 MO) Every search path carries its own paper trail A materials-informatics team that ran a thermoelectric sweep last quarter can pull any candidate back up months later and see exactly which validator fired and which input drove it. The next investigator does not start from the team's slack scrollback.

09.6 · GPU ECONOMICS · MID-TERM (24–48 MO) H100 hours stop funding speculation When the same recompute discipline survives onto real GPU runs, a lab director can justify H100 spend against a candidate's pre-screen record. The conversation with procurement moves from “we need more cluster time” to “these forty chains earned it.”

09.7 · COLLABORATION · MID-TERM (24–48 MO) One candidate, not eight notebooks A battery candidate handed between two groups — a DFT specialist and a phase-field modeller — arrives as one object carrying schema, constraints, validator output, and run history. The receiving team can rerun and contest it without rebuilding the reasoning from emails.

09.8 · DISCOVERY DISCIPLINE · PARADIGM (48 MO+) Materials R&D inherits release discipline If candidate generation, validation, and execution stay coupled all the way through GPU scale, the center of gravity in materials discovery moves from a single hero result toward governed evidence flows that any independent group can pick up and continue.

---

Install / Developer Commands Detailed

Package Install

Installable package: python3.11 -m pip install zer0pa-materials-workbench. Current release: 0.1.0 on PyPI. Source: Zer0pa/Materials-Workbench.

python3.11 -m pip install zer0pa-materials-workbench

Import smoke:

python3.11 - <<'PY'
import importlib.metadata as md
import zer0pa_materials_workbench

print("zer0pa-materials-workbench", md.version("zer0pa-materials-workbench"))
PY

CLI smoke:

zer0pa-materials-workbench --help

Install success only proves package acquisition/import. Product scope, stale PyPI state, platform limits, and blockers remain in the front-door sections below.

• PyPI copy is stale or pending refresh; install success is not product readiness.