PNNL's “co-scientist” serves as a one-stop AI shop for accelerating scientific discovery. By leveraging AI agents, researchers can explore scientific databases, conduct analyses and request step-by-step plans for testing their hypotheses.
By combining computational modeling with experimental research, scientists identified a promising composition that reduces the need for a critical material in an alloy that can withstand extreme environments.
Accessing groundwater may become more difficult—and more expensive—as groundwater supplies become increasingly scarce and underground aquifer levels fall.
A breakthrough in electron microscopy based on deep learning can automatically visualize and identify areas of interest, helping to speed advances in materials science.
Researchers seek to bring down costs, address potential environmental risks and maximize the benefits of harnessing wind energy above the deep waters of the Pacific.
Researchers use models to represent relationships between climate and socio-economic processes, helping inform decisions for slowing climate change and enhancing resilience.
Summer is for science! PNNL’s interns are diving into science and technology and getting a front-row view of the research and development of a national laboratory.
Peering through the thick, green glass of a decades-old "hot cell," an expert technician manipulates robotic arms to study highly radioactive waste from Hanford, in support of ongoing cleanup.
This time of year finds many of us busy with holiday shopping. While PNNL might not be developing the latest video games or hoverboards, we are working hard to deliver a few presents you might like.