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Cars and coronavirus

Oak Ridge National Laboratory researchers have developed a machine learning model that could help predict the impact pandemics such as COVID-19 have on fuel demand in the United States.

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.

Map with focus on sub-saharan Africa

Researchers at Oak Ridge National Laboratory developed a method that uses machine learning to predict seasonal fire risk in Africa, where half of the world’s wildfire-related carbon emissions originate.

Scanning probe microscopes use an atom-sharp tip—only a few nanometers thick—to image materials on a nanometer length scale. The probe tip, invisible to the eye, is attached to a cantilever (pictured) that moves across material surfaces like the tone arm on a record player. Credit: Genevieve Martin/Oak Ridge National Laboratory; U.S. Dept. of Energy.

Liam Collins was drawn to study physics to understand “hidden things” and honed his expertise in microscopy so that he could bring them to light.