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.
Controlling the nanostructure of silk fibroin—a protein found in silk—is a key step toward designing and fabricating electronics that leverage the material’s promising mechanical, optical and biocompatible properties.
PNNL’s patented Shear Assisted Processing and Extrusion (ShAPE™) technique is an advanced manufacturing technology that enables better-performing materials and components while offering opportunities to reduce costs and energy consumption.
A breakthrough in electron microscopy based on deep learning can automatically visualize and identify areas of interest, helping to speed advances in materials science.
Imagine a hollow tube thousands of times smaller than a human hair. Now envision filthy water flowing through an array of such tubes, each designed to capture contaminants on the inside, with clean water emerging at the other end.
July in the Tri-Cities usually brings sunny skies, hot weather and high demand for electricity as many of us retreat to air-conditioned homes and offices.
Cybersecurity is increasingly top-of-mind and in the news. Individuals worry about identify theft and the compromise of financial and medical records. And the federal government battles myriad threats aimed at our national security.
At the Department of Energy's Pacific Northwest National Laboratory, we are developing sophisticated mathematical techniques and software tools to securely manage and analyze vast amounts of data.
