YBCO Reproducibility Framework: Application of Clinical Trial-Inspired Methodology to High-Tc Superconductivity

Author: Bleu Radiance
Date: December 27, 2025

Overview

This repository expands the clinical trial-inspired framework (from LENR work) to YBa₂Cu₃O₇-δ (YBCO) superconductivity. It includes Tc simulations with mathematical variants (noise, broader dome, inhomogeneous doping) to address reproducibility challenges and doping gaps.

Key: Parabolic Tc model, sensitivity analysis, and phased protocol for synthesis/validation.

Citation

Bleu Radiance (2025). YBCO Reproducibility Framework. Zenodo. https://doi.org/[YOUR_NEW_DOI]

Files

• manuscript.md: Full theoretical paper.
• ybco_tc_simulation.py: Reproducible Python code for Tc vs δ simulations (run with python ybco_tc_simulation.py).
• PROTOCOL.md: Experimental protocol for YBCO testing.
• figures/: Generated plots (e.g., Tc model and sensitivity).
• LICENSE: MIT (code), CC-BY-4.0 (manuscript).

Quick Start

git clone https://github.com/BleuRadiance/ybco-reproducibility-framework.git
cd ybco-reproducibility-framework
python ybco_tc_simulation.py  # Runs simulations, prints outputs, saves plots

## Consultations
This framework is designed to enhance reproducibility in physics research. For paid consultations or custom applications to your company's/institution's projects (e.g., quantum materials, superconductivity, or other CMP challenges), contact via GitHub issues or email (blueisresting@gmail.com). No unpaid consultancy.

Copyright (c) 2025 BleuRadience
All rights reserved for moral attribution.
Licensed under Apache 2.0 for code use.