In New Delhi, a research team led by Dr Chi-Young Jung from the Hydrogen Research and Demonstration Center at the Korea Institute of Energy Research has made a significant breakthrough in the analysis of carbon fibre paper, a vital material in hydrogen fuel cells. By leveraging digital twin technology and artificial intelligence (AI), they have developed a method that accelerates the microstructure analysis of carbon fibre paper by 100 times compared to previous methods. Carbon fibre paper is crucial in hydrogen fuel cell stacks, aiding in water discharge and fuel supply. The team's technology utilizes X-ray diagnostics and an AI-based image learning model to analyze the microstructure, eliminating the need for an electron microscope and enabling real-time condition diagnosis. Through training a machine learning algorithm with 5,000 images from 200 carbon fibre paper samples, the model accurately predicts the 3D distribution of key components such as carbon fibers, binders, and coatings with over 98% accuracy. Dr Jung emphasized the practical applicability of this advancement in understanding the relationship between structure and properties of energy materials, foreseeing its impact in secondary batteries and water electrolysis applications.