Patented microchannel heat-exchange technology enables the production of hydrogen from methane, the main ingredient of natural gas, while producing 30 percent less carbon dioxide than conventional processes.
Machine learning models help identify important environmental properties that influence how often extreme rain events occur with critical intensity and duration.
A PNNL-developed computational framework accurately predicts the thermomechanical history and microstructure evolution of materials designed using solid phase processing, allowing scientists to custom design metals with desired properties.
PNNL is working with the Port of Seattle and Seattle City Light to assess the risks of long-term hydrogen storage that can bring clean power for decarbonization.
Report for the Oregon Public Utility Commission highlights innovations and best practices for resilience and utility planning could be helpful to other states as well.
Data-driven autonomous technology to rapidly design and deliver antiviral interventions targeting SARS-CoV-2 to reduce drug discovery timeline and advance bio preparedness capabilities.
Data scientist Jung Lee accepted the position of review editor for Frontiers in Computational Neuroscience after serving as a guest editor for a special issue.
A research buoy managed by PNNL has been deployed in Hawai’ian waters, collecting oceanographic and meteorological measurements off the coast of O’ahu.
A new sodium battery technology shows promise for helping integrate renewable energy into the electric grid. The battery uses Earth-abundant raw materials such as aluminum and sodium.
The work by the team at PNNL takes a critical step in leveraging ML to accelerate advanced manufacturing R&D, specifically for manufacturing techniques without access to efficient, first-principles simulations.