Researchers are exploring the use of interpretable deep learning to understand the relationship between the structure and properties of materials. Various studies are applying machine learning techniques to predict and explain material properties, including mechanical properties and thermoelectric design. These efforts aim to advance the discovery and development of new materials, potentially leading to breakthroughs in fields such as energy applications and nanostructured catalysts.