Dr Chi-Young Jung and the Hydrogen Research & Demonstration Center at KIER introduced a groundbreaking technology for analyzing carbon fibre paper in fuel cells with unprecedented speed and precision. The traditional methods for assessing the microstructure of carbon fibre paper in fuel cells were time-consuming and damaging to the sample. To overcome these limitations, the research team developed an AI-based model that utilizes X-ray diagnostics to analyze the paper's microstructure in real-time without the need for electron microscopes. By training a machine learning algorithm with thousands of images, they achieved remarkable accuracy in predicting the distribution of key components. This advancement not only allows for quick identification of performance degradation causes but also facilitates the comparison of the paper's initial and current states. The study also delved into how design factors impact fuel cell performance, leading to the extraction of optimal parameters and proposing an improved design plan. Dr Chi-Young Jung emphasized the significance of the study in enhancing analysis technology and its practical applicability to various energy-related fields. Funded by KIER, the research was published in Applied Energy, marking a significant milestone in fuel cell research.