GreenH2-ML-DT-Revision

MACHINE LEARNING FOR PREDICTING CATALYST EFFICIENCY IN GREEN HYDROGEN PRODUCTION, PREDICTIVE MAINTENANCE, FAULT DETECTION AND MITIGATION

📊 Digital Twin Interactive Figures

This repository now generates interactive HTML figures alongside static PNGs for publication.

• results/Fig1_Feature_Importance.html: Hoverable bar chart of feature impacts.
• results/Fig3_RUL_Forecast.html: Zoomable degradation forecast with confidence intervals.
• results/Fig5_LCOH_Analysis.html: Interactive economic pathway analysis.

Open these files in any web browser to explore the data dynamically.

🚀 Quick Start

1. Install dependencies:

   pip install -r code/requirements.txt

2. Run the simulation:

   python code/main_simulation.py

📅 Project Roadmap (Phase 0 - Nature Energy Submission)

Phase	Goal	Deadline	Status
Phase 0	Setup & Integrity Baseline	Jan 12, 2026	Active
Phase 1	Data Acquisition & Quantum Sim	Feb 2026	Pending
Phase 2	Model Training & Validation	Mar 2026	Pending
Phase 3	Manuscript Refinement	Apr 2026	Pending
Phase 4	Submission	May 2026	Pending

Current Focus (Phase 0):

• Secure Repository & Version Control.
• Audit and Fix References (100% DOI Validity).
• Establish Ethics & Bias Disclosures.
• Baseline KPI Logging.