The Facility Cybersecurity toolkit, developed by PNNL, is designed for federal facilities to help implement the presidential executive order on cybersecurity, but it is also available for commercial facilities without charge.
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.
PNNL engineer Srinivas Katipamula was recognized by the American Council for an Energy-Efficient Economy with a 2020 Champion of Energy Efficiency Award.
Radiation from natural sources in the environment can limit the performance of superconducting quantum bits, known as qubits. The discovery has implications for quantum computing and for the search for dark matter.
A cadre of physical scientists, engineers and computing experts at Pacific Northwest National Laboratory is poised to participate in the launch of three new DOE Office of Science-sponsored quantum information science research centers.
PNNL’s Karthikeyan Ramasamy was elected to a three-year term as a director in the American Institute of Chemical Engineers’ Fuels and Petrochemicals Division.
After years of planning, building, and calibration, researchers at the Belle II accelerator experiment in Japan have published their first physics paper.
The world’s largest scientific society honored Sue B. Clark, a PNNL and WSU chemist, for contributions toward resolving our legacy of radioactive waste, advancing nuclear safeguards, and developing landmark nuclear research capabilities.
B3? E4? Remember the board game Battleship? One player suggests a set of coordinates to another, hoping to find the elusive location of an unseen vessel.That is a good place to start in assessing the search for dark matter.
A gathering of international experts in Portland, Oregon, explored the future of electron microscopy and surfaced potential solutions in areas including new instrument designs, high-speed detectors, and data analytics capabilities.
Researchers at PNNL are applying deep learning techniques to learn more about neutrinos, part of a worldwide network of researchers trying to understand one of the universe’s most elusive particles.