Machine learning accelerates the discovery of new materials

IMAGE: Feedback from experiments: augmented dataset with four new alloys. view more LOS ALAMOS, N.M., May 9, 2016–Researchers recently demonstrated how an informatics-based adaptive design strategy, tightly coupled to experiments, can accelerate the discovery of new materials with targeted properties, according to a recent paper published in Nature Communications. “What we’ve done is show that, starting with a relatively small data set of well-controlled experiments, it is possible to iteratively guide subsequent experiments toward finding the material with the desired target,” said Turab Lookman, a physicist and materials scientist in the Physics of Condensed Matter and Complex Systems group at Los Alamos National Laboratory. Lookman is the principal investigator of the research project. “Finding new materials has traditionally been guided by intuition and trial and error,” said Lookman.”But with increasing chemical…


Link to Full Article: Machine learning accelerates the discovery of new materials

Pin It on Pinterest

Share This

Join Our Newsletter

Sign up to our mailing list to receive the latest news and updates about homeAI.info and the Informed.AI Network of AI related websites which includes Events.AI, Neurons.AI, Awards.AI, and Vocation.AI

You have Successfully Subscribed!