Topological Material

Topological materials exhibit unique electronic properties stemming from their nontrivial topology, making them promising for technological applications. Current research heavily utilizes machine learning, employing techniques like transformer-based models and graph neural networks, to predict and discover these materials, often incorporating structural and chemical information to improve accuracy and efficiency in classifying topological properties. This focus on machine learning-driven material discovery aims to accelerate the identification of novel topological materials and overcome limitations of traditional ab initio methods, ultimately advancing both fundamental understanding and technological development in this field.