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.
Researchers at Oak Ridge National Laboratory have developed a nationwide modeling tool to help infrastructure planners decide where and when to locate electric vehicle charging stations along interstate highways. The goal is to encourage the adoption of EVs for cross-country travel.
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.
Nuclear scientists at Oak Ridge National Laboratory have established a Nuclear Quality Assurance-1 program for a software product designed to simulate today’s commercial nuclear reactors – removing a significant barrier for industry adoption of the technology.
Oak Ridge National Laboratory is training next-generation cameras called dynamic vision sensors, or DVS, to interpret live information—a capability that has applications in robotics and could improve autonomous vehicle sensing.
Researchers at Oak Ridge National Laboratory are taking inspiration from neural networks to create computers that mimic the human brain—a quickly growing field known as neuromorphic computing.