🚀 HyCAN: Hydrogen Catalyst and Nanomaterials

Cutting-edge platform for clean hydrogen innovation, AI-powered nanomaterial analytics, and real-time monitoring.

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🧠 Project Overview

HyCAN is an open-source AI-enhanced hydrogen research platform integrating:

• Advanced synthesis and reaction monitoring
• Nanomaterial classification and simulation
• Real-time dashboards for analytics
• A modular, cross-platform architecture

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🔧 Features

• ⚛️ Hydrogen simulation & catalyst design
• 🤖 AI/ML models for prediction and automation
• 📈 Interactive visual dashboards
• 📊 Data ingestion, transformation, and analysis
• 🧬 Bioinformatics tools for synthetic biology workflows
• 🐳 Dockerized, scriptable, and field-deployable

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💻 Installation

🔁 Cross-platform Installers

Platform	Installer
Ubuntu/Debian	./build/hycan-x.x.x.deb
Windows	./build/HyCAN-Setup-x.x.x.exe
Linux (Portable)	./build/HyCAN-x86_64.AppImage

🐳 Docker

docker build -t hycan:latest .
docker-compose up --build

🧪 Manual

git clone https://github.com/rfc391/HyCAN.git
cd HyCAN
pip install -r requirements.txt
python main.py

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⚡ Quick Start

hycan-cli --simulate data/example_data.csv --model core/anomaly_detection.py

Use the GUI dashboard:

hycan-cli --dashboard

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📂 Folder Guide

Folder	Description
core/	AI/ML models & training logic
services/	Microservices & APIs
frontend/	Web interface files
config/	YAML/INI configs for modules
visualization/	Notebooks, dashboards, and plots
tests/	All test scripts using PyTest
docs/	User and developer documentation

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🧪 Testing

black . --check
flake8 .
pytest tests/

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🛠️ Developer Guide

• Auto-build: GitHub Actions for .deb, .exe, .AppImage
• Documentation: mkdocs serve
• Web Dashboard: Svelte/JS frontend (served via Flask or FastAPI)

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🧾 License

This project is under the MIT License.

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🤝 Contributing

We welcome PRs and new feature suggestions. See docs/CONTRIBUTING.md.