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A team of scientists led by ORNL discovered the gene in agave that governs when the plant goes dormant and used it to create poplar trees that nearly doubled in size, increasing biomass yield for biofuels production
The presence of minerals called ash in plants makes little difference to the fitness of new naturally derived compound materials designed for additive manufacturing, an Oak Ridge National Laboratory-led team found.
Global carbon emissions from inland waters such as lakes, rivers, streams and ponds are being undercounted by about 13% and will likely continue to rise given climate events and land use changes, ORNL scientists found.
A multi-lab research team led by ORNL's Paul Kent is developing a computer application called QMCPACK to enable precise and reliable predictions of the fundamental properties of materials critical in energy research.
Researchers at Oak Ridge National Laboratory and Momentum Technologies have piloted an industrial-scale process for recycling valuable materials in the millions of tons of e-waste generated annually in the United States.
Scientists at Oak Ridge National Laboratory are closer to unlocking the secrets to better soil carbon sequestration by studying the tiny, sand-like silicon deposits called phytoliths in plants.
Researchers at Oak Ridge National Laboratory are using state-of-the-art methods to shed light on chemical separations needed to recover rare-earth elements and secure critical materials for clean energy technologies.
Oak Ridge National Laboratory researchers developed an invertible neural network, a type of artificial intelligence that mimics the human brain, to improve accuracy in climate-change models and predictions.
Measuring water quality throughout river networks with precision, speed and at lower cost than traditional methods is now possible with AquaBOT, an aquatic drone developed by Oak Ridge National Laboratory.
University of Pennsylvania researchers called on computational systems biology expertise at Oak Ridge National Laboratory to analyze large datasets of single-cell RNA sequencing from skin samples afflicted with atopic dermatitis.