How AI is becoming a research companion to materials scientists

By automating scientific processes and introducing artificial intelligence for decision-making, TRI's new closed-loop research platforms free up scientists' time for more creative tasks. When I first started graduate school almost 10 years ago, I was mixing ingredients by hand, writing down reaction conditions on a piece of paper, and grabbing a quick lunch in between lab sessions. At that time, the idea of a robot doing my experiments -- or using machine learning to predict the outcomes of my reactions -- would have never occurred to me. I accepted a future as a scientist where I would only be able to explore a tiny fraction of the billions of possible materials in the universe by hand. If lucky, a scientific discovery might arrive serendipitously as I became better at making "educated guesses."