PNNL led a multi-institutional effort to design a highly active and more durable catalyst made from cobalt, which sets the foundation for fuel cells to power transportation, stationary and backup power, and more.
Project manager Larry Morgan has spent half a century at Pacific Northwest National Laboratory—marking one of the longest tenures in the laboratory’s history.
As COVID-19 was limiting in-person contact, halting travel, and creating additional barriers, researchers at PNNL were working to find solutions on how they could still get work done while establishing new safety protocols.
PNNL researchers have shown an improved binarized neural network can deliver a low-cost and low-energy computation to help the performance of smart devices and the power grid.
A new report outlines future research paths that are needed for airlines to reduce carbon emissions and notes that the only way to achieve emission reduction goals is with Sustainable Aviation Fuels.
Researchers at Pacific Northwest National Laboratory (PNNL) are closer to understanding how iron may pave the way for sequestration of technetium-99 contaminants in the subsurface.
Researchers at PNNL have developed a bacteria testing system called OmniScreen that combines biological and synthetic chemistry with machine learning to hunt down pathogens before they strike.
PNNL scientists have developed a catalyst that converts ethanol into C5+ ketones that can serve as the building blocks for everything from solvents to jet fuel.
PNNL’s new Smart Power Grid Simulator, or Smart-PGSim, combines high-performance computing and artificial intelligence to optimize power grid simulations without sacrificing accuracy.
PNNL researchers are contributing expertise and hydrothermal liquefaction technology to a project that intercepts harmful algal blooms from water, treats the water, and concentrates algae for transformation to biocrude.
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.
PNNL researchers established an Internet of Things Common Operating Environment (IoTCOE) laboratory to explore the risks associated with IoT connectivity to the internet, the energy grid and other critical infrastructures.
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.
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.
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.
