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An all-in-one experimental platform developed at Oak Ridge National Laboratory’s Center for Nanophase Materials Sciences accelerates research on promising materials for future technologies.

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.

ORNL researchers have developed an intelligent power electronic inverter platform that can connect locally sited energy resources such as solar panels, energy storage and electric vehicles and smoothly interact with the utility power grid.

From materials science and earth system modeling to quantum information science and cybersecurity, experts in many fields run simulations and conduct experiments to collect the abundance of data necessary for scientific progress.

Scientists at Oak Ridge National Laboratory have demonstrated a direct relationship between climate warming and carbon loss in a peatland ecosystem.

Five researchers at the Department of Energy’s Oak Ridge National Laboratory have been named ORNL Corporate Fellows in recognition of significant career accomplishments and continued leadership in their scientific fields.

Burak Ozpineci of the Electrical and Electronics Systems Research Division at Oak Ridge National Laboratory has won the 2020 IEEE Power Electronics Society Vehicle and Transportation Systems Achievement Award.

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.

An ORNL team used a simple process to implant atoms precisely into the top layers of ultra-thin crystals, yielding two-sided structures with different chemical compositions.

In the search to create materials that can withstand extreme radiation, Yanwen Zhang, a researcher at the Department of Energy’s Oak Ridge National Laboratory, says that materials scientists must think outside the box.