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One of the proteins identified through a new ORNL-developed approach could be key to communications between poplar trees and beneficial microbes that can help boost poplar trees’ growth, carbon storage and climate resilience. Credit: Andy Sproles/ORNL, U.S. Dept. of Energy

ORNL researchers have identified specific proteins and amino acids that could control bioenergy plants’ ability to identify beneficial microbes that can enhance plant growth and storage of carbon in soils.

Through the Honnold Foundation and Casa Pueblo, solar panels are installed in Adjuntas, Puerto Rico, and hooked to microgrids with battery storage. ORNL researchers are developing a microgrid orchestrator to manage the microgrids together for increased long-term electrical reliability. Credit: Fabio Andrade

ORNL researchers Ben Ollis and Max Ferrari will be in Adjuntas to join the March 18 festivities but also to hammer out more technical details of their contribution to the project: making the microgrids even more reliable.

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.

A team of ORNL researchers used neutron diffraction experiments to study the 3D-printed ACMZ alloy and observed a phenomenon called “load shuffling” that could inform the design of stronger, better-performing lightweight materials for vehicles. Credit: ORNL, U.S. Dept. of Energy

ORNL researchers have identified a mechanism in a 3D-printed alloy – termed “load shuffling” — that could enable the design of better-performing lightweight materials for vehicles.

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.

Technology to retrofit nonpowered dams such as the Lake Sequoyah Dam in North Carolina could be tested before deploying to ensure performance and reliability. Credit: Scott DeNeale/ORNL, U.S. Dept. of Energy

Researchers at Oak Ridge National Laboratory have identified a key need for future hydropower innovations – full-scale testing – to better inform developers and operators before making major investments.

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.

A new online tool developed by ORNL researchers, VERIFI, provides an easy to use dashboard for plant managers to track carbon emissions produced by industrial processes. The tool also monitors energy usage and produces trend reports. Credit: ORNL, U.S. Dept. of Energy

Researchers at ORNL have developed an online tool that offers industrial plants an easier way to track and download information about their energy footprint and carbon emissions.

Melton Hill Dam

To further the potential benefits of the nation’s hydropower resources, researchers at Oak Ridge National Laboratory have developed and maintain a comprehensive water energy digital platform called HydroSource.

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.