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Media Contacts
Researchers at Oak Ridge National Laboratory have developed free data sets to estimate how much energy any building in the contiguous U.S. will use in 2100. These data sets provide planners a way to anticipate future energy needs as the climate changes.
Building innovations from ORNL will be on display in Washington, D.C. on the National Mall June 7 to June 9, 2024, during the U.S. Department of Housing and Urban Development’s Innovation Housing Showcase. For the first time, ORNL’s real-time building evaluator was demonstrated outside of a laboratory setting and deployed for building construction.
ORNL researchers used electron-beam additive manufacturing to 3D-print the first complex, defect-free tungsten parts with complex geometries.
A technology developed by Oak Ridge National Laboratory works to keep food refrigerated with phase change materials, or PCMs, while reducing carbon emissions by 30%.
Scientists at ORNL completed a study of how well vegetation survived extreme heat events in both urban and rural communities across the country in recent years. The analysis informs pathways for climate mitigation, including ways to reduce the effect of urban heat islands.
Scientists at the Department of Energy’s Oak Ridge National Laboratory have developed lubricant additives that protect both water turbine equipment and the surrounding environment.
Groundwater withdrawals are expected to peak in about one-third of the world’s basins by 2050, potentially triggering significant trade and agriculture shifts, a new analysis finds.
An international team using neutrons set the first benchmark (one nanosecond) for a polymer-electrolyte and lithium-salt mixture. Findings could produce safer, more powerful lithium batteries.
The United States could triple its current bioeconomy by producing more than 1 billion tons per year of plant-based biomass for renewable fuels, while meeting projected demands for food, feed, fiber, conventional forest products and exports, according to the DOE’s latest Billion-Ton Report led by ORNL.
To capitalize on AI and researcher strengths, scientists developed a human-AI collaboration recommender system for improved experimentation performance.