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.
Researchers at PNNL are pursuing new approaches to understand, predict and control the phenome—the collection of biological traits within an organism shaped by its genes and interactions with the environment.
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.
Recognizing how innovation and clean technologies at the very edge of the grid can work together to transition the electricity system, PNNL takes a multidisciplinary approach to advancing and integrating renewable energy solutions.
From water purification, to better batteries and tools to foil a cyberattack—a look back at how PNNL helped to invent a brighter and better future over the last year.