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Media Contacts
ORNL researchers have developed a training camp to help manufacturing industries reduce energy-related carbon dioxide emissions and improve cost savings.
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.
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.
Oak Ridge National Laboratory researchers developed and demonstrated algorithm-based controls for a hybrid electric bus that yielded up to 30% energy savings compared with existing controls.
Algorithms developed at Oak Ridge National Laboratory can greatly enhance X-ray computed tomography images of 3D-printed metal parts, resulting in more accurate, faster scans.
Oak Ridge National Laboratory researchers have developed a machine learning model that could help predict the impact pandemics such as COVID-19 have on fuel demand in the United States.
Researchers at Oak Ridge National Laboratory developed a method that uses machine learning to predict seasonal fire risk in Africa, where half of the world’s wildfire-related carbon emissions originate.
A new method developed at Oak Ridge National Laboratory improves the energy efficiency of a desalination process known as solar-thermal evaporation.
By automating the production of neptunium oxide-aluminum pellets, Oak Ridge National Laboratory scientists have eliminated a key bottleneck when producing plutonium-238 used by NASA to fuel deep space exploration.