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ORNL’s Adam Guss began adapting the SAGE gene editing tool to modify microbes in graduate school. Today, SAGE is rapidly accelerating the design of custom microbes for a variety of applications. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

A DNA editing tool adapted by Oak Ridge National Laboratory scientists makes engineering microbes for everything from bioenergy production to plastics recycling easier and faster.

Hybrid poplar trees such as these shown in an ORNL greenhouse were engineered with the REVEILLE1 gene to delay dormancy and produce more biomass. The research was led by the Center for Bioenergy Innovation at ORNL with the Joint Genome Institute, Brookhaven National Laboratory, the HudsonAlpha Institute for Biotechnology, the University of Connecticut and other partners. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

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

Researchers found that moderate levels of ash — sometimes found as spheres in biomass — do not significantly affect the mechanical properties of biocomposites made up of corn stover, switchgrass and PLA thermoplastic. Credit: Andy Sproles/ORNL, U.S. Dept. of Energy

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.

Researchers at ORNL designed a recyclable carbon fiber material to promote low-carbon manufacturing. Credit: Chad Malone/ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory scientists designed a recyclable polymer for carbon-fiber composites to enable circular manufacturing of parts that boost energy efficiency in automotive, wind power and aerospace applications.

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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.

Researchers at Oak Ridge National Laboratory probed the chemistry of radium to gain key insights on advancing cancer treatments using radiation therapy. Credit: Adam Malin/ORNL, U.S. Dept. of Energy

Researchers at ORNL explored radium’s chemistry to advance cancer treatments using ionizing radiation.

Researchers used quantum Monte Carlo calculations to accurately render the structure and electronic properties of germanium selenide, a semiconducting nanomaterial. Credit: Paul Kent/ORNL, U.S. Dept. of Energy

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.

These images show increasing levels of magnification of phytoliths in the leaves of poplar trees, a key biofuel crop, imaged using ORNL’s specialized microscopy-spectroscopy. Credit: Elizabeth Herndon/ORNL, U.S. Dept. of Energy

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.

Physicist Charles Havener uses the NASA end station at ORNL’s Multicharged Ion Research Facility to simulate the origin of X-ray emissions from space. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Scientists are using Oak Ridge National Laboratory’s Multicharged Ion Research Facility to simulate the cosmic origin of X-ray emissions resulting when highly charged ions collide with neutral atoms and molecules, such as helium and gaseous hydrogen.

With seismic and acoustic data recorded by remote sensors near ORNL’s High Flux Isotope Reactor, researchers could predict whether the reactor was on or off with 98% accuracy. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy

An Oak Ridge National Laboratory team developed a novel technique using sensors to monitor seismic and acoustic activity and machine learning to differentiate operational activities at facilities from “noise” in the recorded data.