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ORNL seismic researcher Chengping Chai placed seismic sensors on the ground at various distances from an ORNL nuclear reactor to learn whether they could detect its operating state. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Like most scientists, Chengping Chai is not content with the surface of things: He wants to probe beyond to learn what’s really going on. But in his case, he is literally building a map of the world beneath, using seismic and acoustic data that reveal when and where the earth moves.

An open-source code developed by an ORNL-led team could provide new insights into the everyday operation of the nation’s power grid. Credit: Pixabay

Oak Ridge National Laboratory, University of Tennessee and University of Central Florida researchers released a new high-performance computing code designed to more efficiently examine

An algorithm developed and field-tested by ORNL researchers uses machine learning to maintain homeowners’ preferred temperatures year-round while minimizing energy costs. Credit: ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory researchers designed and field-tested an algorithm that could help homeowners maintain comfortable temperatures year-round while minimizing utility costs.

Sergei Kalinin

Five researchers at the Department of Energy’s Oak Ridge National Laboratory have been named ORNL Corporate Fellows in recognition of significant career accomplishments and continued leadership in their scientific fields.

From left, Peter Jiang, Elijah Martin and Benjamin Sulman have been selected for Early Career Research Program awards from the Department of Energy's Office of Science. Credit: Oak Ridge National Laboratory, U.S. Dept. of Energy

The Department of Energy’s Office of Science has selected three Oak Ridge National Laboratory scientists for Early Career Research Program awards.

Smart Neighborhood homes

To better determine the potential energy cost savings among connected homes, researchers at Oak Ridge National Laboratory developed a computer simulation to more accurately compare energy use on similar weather days.