Using AI and robots to speed up optimization of new battery development

A team of researchers at Carnegie Mellon University has developed a new approach to speeding up the process of creating ever more optimized batteries. In their paper published in the journal Nature Communications, the group describes how they paired a unique type of robot with an AI learning system to create ever more useful non-aqueous liquid electrolytes.

As sales of handheld devices have skyrocketed and car makers have turned to electric vehicles, demand for batteries that last longer and charge more quickly has risen as well. Unfortunately, the science of developing new batteries to serve such needs has lagged—it typically involves the use of intuition on the part of chemists along with persistence. Such efforts can take years. In this new study, the researchers in Pittsburgh sought to speed up the process by using automation techniques.