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Steven Campbell and Radha Krishna-Moorthy discuss part of the power electronics that make up the Smart Universal Power Electronics Regulator technology developed at ORNL. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Researchers at ORNL are helping modernize power management and enhance reliability in an increasingly complex electric grid.

This newly manufactured fixed guide vane of a hydropower turbine system was printed at the DOE Manufacturing Demonstration Facility at ORNL. Credit: Genevieve Martin/ORNL, U.S Dept. of Energy

A new report published by ORNL assessed how advanced manufacturing and materials, such as 3D printing and novel component coatings, could offer solutions to modernize the existing fleet and design new approaches to hydropower.

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 researchers have developed a way to manage car batteries of different types and sizes as energy storage for the power grid. Credit: Andy Sproles/ORNL, U.S. Dept. of Energy

When aging vehicle batteries lack the juice to power your car anymore, they may still hold energy. Yet it’s tough to find new uses for lithium-ion batteries with different makers, ages and sizes. A solution is urgently needed because battery recycling options are scarce.

A multiport design allows a utility to easily interface with an EV truck stop to provide fast-charging at megawatt-scale. Credit: Andy Sproles/ORNL, U.S. Dept. of Energy

Researchers at Oak Ridge National Laboratory have designed architecture, software and control strategies for a futuristic EV truck stop that can draw megawatts of power and reduce 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.

ORNL, VA and Harvard researchers developed a sparse matrix full of anonymized information on what is thought to be the largest cohort of healthcare data used for this type of research in the U.S. The matrix can be probed with different methods, such as KESER, to gain new insights into human health. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy

A team of researchers has developed a novel, machine learning–based  technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.

Genetic analysis revealed connections between inflammatory activity and development of atomic dermatitis, according to researchers from the UPenn School of Medicine, the Perelman School of Medicine, and Oak Ridge National Laboratory. Credit: Kang Ko/UPenn

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.

An ORNL-led team studied the SARS-CoV-2 spike protein in the trimer state, shown here, to pinpoint structural transitions that could be disrupted to destabilize the protein and negate its harmful effects. Credit: Debsindhu Bhowmik/ORNL, U.S. Dept. of Energy

To explore the inner workings of severe acute respiratory syndrome coronavirus 2, or SARS-CoV-2, researchers from ORNL developed a novel technique.

This protein drives key processes for sulfide use in many microorganisms that produce methane, including Thermosipho melanesiensis. Researchers used supercomputing and deep learning tools to predict its structure, which has eluded experimental methods such as crystallography.  Credit: Ada Sedova/ORNL, U.S. Dept. of Energy

A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.