Tracking down nefarious users is just one example of work at PNNL’s Center for Advanced Technology Evaluation, a computing proving ground supported by DOE’s Advanced Scientific Computing Research program.
Using a large repository of blood samples from military personnel, PNNL and Uniformed Services University scientists have discovered a group of 13 proteins that could provide early detection of head and neck cancers.
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.
Researchers at PNNL have increased the conductivity of copper wire by about five percent via a process called Shear Assisted Processing and Extrusion. General Motors tested the wire for application in vehicle motor components.
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.
Each summer, PNNL invites middle and high school STEM teachers from nearby underrepresented and underserved rural communities from the Mid-Columbia Basin region to participate in the Teacher-Scientist Partnership.
PNNL deployed two research buoys in waters off the West Coast for the first time in deep water, supporting a DOE and Bureau of Ocean Energy Management effort to gather measurements that support offshore wind locations and technologies.
A new agreement between Pacific Northwest National Laboratory and The University of Texas at El Paso will create research and internship opportunities.
PNNL researchers used machine learning to develop a tool for a nonprofit to identify orthopedic implants in X-ray images to improve surgical speed and accuracy.
Culminating 10 years of study, researchers at PNNL’s Marine and Coastal Research Laboratory developed a new predictive framework for estuarine–tidal river research and management.
PNNL team has developed and implemented a generalizable computational framework to study the resilience of the multilayered London Rail Network to the compound threat of intense flooding and a targeted cyberattack.
A team of researchers led by scientists from PNNL simulated carbon cycling and community composition during 100 years of forest regrowth following disturbance.