AI-based method speeds discovery of materials that harvest electricity from wasted heat

In any form of energy conversion--even with something as green as solar panels--extra heat is generated. But with up to 72 percent of it left unused, there's also great potential to harvest electricity from that waste. A University of Alberta researcher has successfully developed a way to figure out the chemistry behind that process. The finding could ultimately help speed up development of thermoelectric materials--products that, if attached to something like a solar panel system, can recover waste heat that can then be used to generate electrical current. Using two machine learning models he developed, Alexander Gzyl has been able to narrow down the chemical makeup of a group of alloys that could be used to create those materials.