Machine-learning to predict the performance of organic solar cells

Imagine looking for the optimal configuration to build an organic solar cell made from different polymers. Does the active layer need to be very thick, or very thin? Does it need a large or a small amount of each polymer? Knowing how to predict the specific composition and cell design that would result in optimum performance is one of the greatest unresolved problems in materials science. This is, in part, due to the fact that the device performance depends on multiple factors.