ORNL’s Lab-on-a-crystal uses machine learning to correlate materials’ mechanical, optical and electrical responses to dynamic environments. Credit: Ilia Ivanov/ORNL, U.S. Dept. of Energy
An all-in-one experimental platform developed at Oak Ridge National Laboratory’s Center for Nanophase Materials Sciences accelerates research on promising materials for future technologies.
The “Lab-on-a-crystal,” designed on a commercially available quartz crystal microbalance, or QCM, measures materials’ interrelated responses to the environment in real time – something that traditionally required different specialized instruments, multiple experiments and a lot of time.
Modified QCM hardware has been incorporated into a machine learning platform that optimizes data collection and identifies correlations among several simultaneous measurements, including mechanical, electrical and optical.
“Being able to characterize multiple functionalities simultaneously at macro-, micro- and nanoscales on the same sample is a breakthrough for materials sciences. In a day, we can accomplish a month’s worth of experiments,” said ORNL’s Ilia Ivanov.
A collaboration with researchers from the European Union on advancing rapid-detection methods for enzymes that degrade milk quality highlights the platform’s broad applications to CNMS users. — Ashley Huff
