Vision Transformers for X-ray Diffraction Patterns Analysis

Understanding materials properties depends largely on the ability to determine its components, and in particular its mineral phases. Powder X-ray diffraction (XRD) is a powerful tool for such purposes. This paper presents a Transformer-based vision model (ViT) for mineral phase identification, and proportion inference to quantify the mineral phases present in a material. Our analysis shows that the tokenization strategy is a critical step for XRD pattern analysis. The results obtained for both tasks are excellent and more robust than those obtained with a CNN. The proposed approach also makes it possible to introduce visualization tools for signal analysis, to better understand how information flows through the model and how data is classified or quantified.