A PNNL innovation uses steam to recover heat from the high-temperature reactor effluent in the HTL process, substantially reducing the propensity for fouling and potentially reducing costs.

Machine learning models help identify important environmental properties that influence how often extreme rain events occur with critical intensity and duration.

PNNL researchers discovered a faster, more economical method to verify the amount of biofuel in mixtures of bio and fossil fuel.

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 researchers combined deep operator networks with spectral methods to efficiently and accurately solve complex equations.

Cesar Moriel from University of Texas at El Paso will be interning at the PNNL over the summer as part of the Energy Environment Diversity Internship Program.

PNNL researchers design liquid-based porous electrolyte that could transport lithium ions more easily between electrodes, improving battery efficiency.

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.

The Model Selection Platform compares more than 60 energy storage modeling, valuation, and simulation tools developed by DOE’s national laboratories.

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.

Harnessing the sea for decarbonized energy is the focus of a new collaboration between PNNL and the University of Guam.

Researchers developed a machine learning model that can analyze chemical reactions as they happen in an electron microscope.

PNNL researchers are moving energy research forward through collaborative projects with universities across the United States.

Research published in Journal of Manufacturing Processes demonstrates innovative single-step method to manufacture oxide dispersion strengthened copper materials from powder.

As leaders in AI and machine learning, PNNL experts are sharing their latest findings at the 36th annual Neural Information Processing Systems (NeurIPS) Conference, Nov. 28–Dec. 9, 2022.

Multidisciplinary teams from research and industry are brought together using management systems developed by a team of software engineers at PNNL.

Tailoring hydrogen-based energy storage solutions to specific real-world applications.

PNNL gathered researchers from eight national laboratories plus the U.S. Department of Energy (DOE) to share ideas and build synergy at the Energy Equity and Environmental Justice Summit.

The Department of Energy Secretary Jennifer Granholm made her first in-person visit to PNNL, a leading center for scientific discovery and technical innovation in sustainable energy.