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ORNL scientists used commuting behavior data from East Tennessee to demonstrate how machine learning models can easily accept new data, quickly re-train themselves and update predictions about commuting patterns. Credit: April Morton/Oak Ridge National La

Oak Ridge National Laboratory geospatial scientists who study the movement of people are using advanced machine learning methods to better predict home-to-work commuting patterns.

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While studying the genes in poplar trees that control callus formation, scientists at Oak Ridge National Laboratory have uncovered genetic networks at the root of tumor formation in several human cancers.

Nuclear—Deep space travel

By automating the production of neptunium oxide-aluminum pellets, Oak Ridge National Laboratory scientists have eliminated a key bottleneck when producing plutonium-238 used by NASA to fuel deep space exploration.

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Scientists at Oak Ridge National Laboratory and Hypres, a digital superconductor company, have tested a novel cryogenic, or low-temperature, memory cell circuit design that may boost memory storage while using less energy in future exascale and quantum computing applications.

ORNL bioscience researcher Jerry Tuskan had an early interest in plant genetics.

It’s been 10 years since the Department of Energy first established a BioEnergy Science Center (BESC) at Oak Ridge National Laboratory, and researcher Gerald “Jerry” Tuskan has used that time and the lab’s and center’s resources and tools to make good on his college dreams of usi...

ORNL’s Manjunath Gorentla Venkata helped develop a new approach to analyze thousands of genetic samples by connecting powerful computing resources.

Computing experts at the Department of Energy’s Oak Ridge National Laboratory collaborated with a team of university researchers and software companies to develop a novel hybrid computational strategy to efficiently discover genetic variants 

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The Department of Energy’s Oak Ridge National Laboratory has received funding from DOE’s Exascale Computing Project (ECP) to develop applications for future exascale systems that will be 50 to 100 times more powerful than today’s fastest supercomputers.