Infusing data science and artificial intelligence into electron microscopy could advance energy storage, quantum information science, and materials design.
PNNL has three small-scale spectroscopy devices that are speeding up the testing and analysis of candidate novel materials used in energy storage research and environmental remediation.
In recognition of Nuclear Science Week on Oct. 19-23, Pacific Northwest National Laboratory reflects on more than half a century of advancing nuclear science for the nation’s energy, environment, and security frontiers.
Pacific Northwest National Laboratory researchers used machine learning to explore the largest water clusters database, identifying—with the most accurate neural network—important information about this life-essential molecule.
Five PNNL technologies were recently awarded six R&D 100 honors. The R&D 100 Awards, now in its 58th year, recognize pioneers in science and technology from industry, the federal government, and academia.
The American Society for Quality (ASQ) has recognized Laboratory Fellow and Pacific Northwest National Laboratory (PNNL) Statistician Greg Piepel with the William G. Hunter Award.
First-ever measurements provide evidence that supercooled water exists in two distinct structures that co-exist and vary in proportion dependent on temperature.
An international team used PNNL microscopy to answer questions about how uranium dioxide—used in nuclear power plants—might behave in long-term storage.
A new radiation-resistant material for the efficient capture of noble gases xenon and krypton makes it safer and cheaper to recycle spent nuclear fuel.
A 2011 earthquake and tsunami in Japan that knocked out a nuclear power plant helped inspire PNNL computational scientists looking for clues of future nuclear reactor mishaps by tracking radioactive iodine.