After years of planning, building, and calibration, researchers at the Belle II accelerator experiment in Japan have published their first physics paper.
PNNL’s Patrick Balducci delivered an information-packed tutorial on grid energy storage valuation at the Naval Postgraduate School in Monterey, California.
The Energy Storage System Safety and Reliability Forum at PNNL brought together more than 120 energy storage experts from the U.S. Department of Energy, the national laboratories, utilities, industry and academia.
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.
PNNL will lead three new grid modernization projects funded by the Department of Energy. The projects focus on scalability and usability, networked microgrids, and machine learning for a more resilient, flexible and secure power grid.
Pumped-storage hydropower offers the most cost-effective storage option for shifting large volumes of energy. A PNNL-led team wrote a report comparing cost and performance factors for 10 storage technologies.
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.
With support from DOE’s Office of Electricity and National Grid, PNNL led a groundbreaking study to accurately assess the full value of grid energy storage investments across a wide variety of use cases.
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.
Energy storage is slowly shifting utility planning practices from the current paradigm, which ensures grid reliability by building reserve generation resources, to ensuring grid reliability by optimizing grid services.
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.
Researchers used novel methods to safely create and analyze plutonium samples. The approaches could prove influential in future studies of the radioactive material, benefitting research in legacy, national security and nuclear fuels.