GraphAIne

🚀 Neural Networks for Graphene Plasmonics

📌 Table of Contents

• 📖 About
• ⚙️ Installation
• 🛠 Prerequisites
• 🚀 How to Use
• 📜 License
• 📩 Contact

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📖 About

GraphAIne is a deep learning framework for graphene plasmonics using neural networks.
It predicts atomic charge distributions based on frequency-dependent interactions in graphene nanostructures.

This framework uses feedforward neural networks (FNNs) to model atomic-level charge responses
and is designed to handle large-scale graphene-based molecular simulations.

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⚙️ Installation

Run the installation script to set up GraphAIne:

chmod +x install.sh
./install.sh

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🛠 Prerequisites

• Python 3.8.10 or later
• pip3 (Python package manager for Python 3)
• Virtual environment support (venv or virtualenv)
• Required Python packages:
  • numpy (latest version)
  • pandas (latest version)
  • tensorflow (latest version)

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🚀 How to use

python3 src/inference/fnn_predict.py -h

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📜 License

This project is licensed under the GNU General Public License v3.0

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📩 Contact

For any issue contact pgrobasillobre@gmail.com