Machine learning marched forward

Abstract

Intelligent robots may yet take our jobs; they definitely grabbed a lot of C&EN’s headlines this year. Researchers continued to explore applications of machine learning, a type of artificial intelligence used to make predictions or decisions through algorithms that can learn from large data sets. The technology powers self-driving cars and image-recognition software. Scientists demonstrated numerous ways in which machine learning can help explore chemical space. For example, Heather Kulik of the Massachusetts Institute of Technology and colleagues identified inorganic molecules called spin-crossover complexes that could be useful as sensors or electronic switches (J. Phys. Chem. Lett. 2018, DOI: 10.1021/acs.jpclett.8b00170). Apurva Mehta of the SLAC National Accelerator Laboratory, along with collaborators, used machine learning to identify new alloys that are metallic glasses (Sci. Adv. 2018, DOI: 10.1126/sciadv.aaq1566). And the chemical company Symrise teamed up with IBM to search for new fragrances us...