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.
PNNL and Argonne researchers developed and tested a chemical process that successfully captures radioactive byproducts from used nuclear fuel so they could be sent to advanced reactors for destruction while also producing electrical power.
Seventeen teams from regional colleges and universities gathered at PNNL Nov. 16 to put their cyber skills to the test by protecting critical energy infrastructure against simulated cyberattacks as part of DOE's CyberForce Competition.
In the third year of the DISCOVR Consortium project, the consortium team has identified an algal strain that progressed successfully through multiple evaluation phases.
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 new Co-Optima report describes an assessment of 400 biofuel-derived samples and identifies the top ten candidates for blending with petroleum fuel to improve boosted spark ignition engine efficiency.
Nitrogen oxides, also known as NOx, form when fossil fuels burn at high temperatures. When emitted from industrial sources such as coal power plants, these pollutants react with other compounds to produce harmful smog.
Eric Hoppe, senior scientist, was selected a 2019 American Chemical Society (ACS) fellow. Eric is being recognized for his contributions to analytical chemistry measurements and three decades of volunteer service to the ACS community.
Researchers at PNNL have developed a model that predicts outcomes from the algae hydrothermal liquefaction process in a way that mirrors commercial reality much more closely than previous analyses.
Researchers at PNNL have introduced an alternative method using a molecular-based pump that could potentially use a quarter less energy than the age-old mechanical pump.
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 at PNNL and their collaborators have made a significant improvement to a catalyst that is more rugged and can reduce tailpipe pollution at lower temperatures than existing methods.