Improving Fuel Cell Performance With AI Fuel cells use clean hydrogen fuel, which can be generated by wind and solar energy, to produce heat and electricity, and lithium-ion batteries, like those found in smartphones, laptops, and electric cars, are a popular type of energy storage. The performance of both is closely related to their micro-structure: how the pores (holes) inside their electrodes are shaped and arranged can affect how much power fuel cells can generate, and how quickly batteries charge and discharge. However, because the micrometer-scale pores are so small, their specific shapes and sizes can be difficult to study at a high enough resolution to relate them to overall cell performance. Now, Imperial researchers have applied machine learning techniques to help them explore these pores virtually and run 3D simulations to predict cell performance based on their micro-structure. The researchers used a novel machine learning technique called “deep convolutional ge...