A new AI model developed at PNNL can identify patterns in electron microscope images of materials without requiring human intervention, allowing for more accurate and consistent materials science.
To overcome high-performance computing bottlenecks, a research team at PNNL proposed using graph theory, a mathematical field that explores relationships and connections between a number, or cluster, of points in a space.
Scientists at PNNL are working to better prepare authorities, emergency responders, communities and the grid in the face of increasingly extreme hurricanes.
Scientists are pioneering approaches in the branch of artificial intelligence known as machine learning to design and train computer software programs that guide the development of new manufacturing processes.
PNNL researchers developed a new model to help power system operators and planners better evaluate how grid-forming, inverter-based resources could affect the system stability.
Top scientists and officials from government, academia, Alaskan Native communities, and industry are heading to Alaska to focus on driving energy technologies for a more sustainable Arctic region.
Lighting control data are critical for optimizing the design and operation of future lighting systems for the benefit of occupants and energy efficiency.
