New machine learning program to speed up clean energy generation

Attention is increasingly turning to organic photovoltaic (OPV) solar cells after decades of relying on silicon, which is relatively expensive and lacks flexibility. OPV solar cells will be cheaper to make by using printing technologies, as well as being more versatile and easier to dispose of. But a major challenge is sorting through the huge volume of potentially suitable chemical compounds that can be synthesised (tailor-made by scientists) for use in OPVs. Researchers have tried using machine learning before to address this issue but many of those models were time consuming, required significant computer processing power and were difficult to replicate. Crucially, they did not provide enough guidance for the experimental scientists seeking to build new solar devices.