Crystal Representation

Crystal representation research focuses on developing effective computational methods to encode the complex structural information of crystalline materials, enabling accurate prediction of their properties. Current efforts center on creating comprehensive representations that capture both local atomic arrangements and global periodic patterns, often employing graph neural networks and diffusion models with novel architectures designed to handle the inherent periodicity and symmetry of crystals. These improved representations are crucial for accelerating materials discovery and design, enabling researchers to predict material properties with greater accuracy and efficiency, ultimately leading to the development of new materials with desired functionalities.