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cgcnn2 is a reproduction of crystal graph convolutional neural network (CGCNN) for predicting material properties. This documentation will help you get started with using CGCNN for your materials science research.

Features

• Training a CGCNN model with a customized dataset.
• Predicting material properties with a pre-trained CGCNN model.
• Fine-tuning a pre-trained CGCNN model on a new dataset.
• Extracting atomic features as descriptors for the downstream task.

Getting Started

1. Package Installation
2. CGCNN Preliminaries
3. Function Usage
4. Examples