Complex metal alloys enter a new era of predictive design for aerospace and other high-temperature applications.

A new study demonstrates a hybrid model that can simulate part of a system at the molecular scale and other parts at larger scales in a computationally efficient manner, providing greater simulation flexibility.

The Department of Energy Office of Nuclear Energy acting assistant secretary makes his first visit to a national laboratory in his new role, touring PNNL's Radiochemical Processing Laboratory.

PNNL researchers review ceramic-metal composite technology for immobilizing radioactive wastes from nuclear reactors, including advanced reactors.

The 2024 Jack Simons Award honor recognizes Li for his expertise in integrating chemistry with computing for fundamental science research.

PNNL researchers learn to control peptoid “handedness,” one key to precision drug delivery and diagnostics.

Data scientist at PNNL receives the Environmental and Engineering Geophysical Society and Geonics Limited Early Career Award for work with geophysical modeling and subsurface inversion codes.

IDREAM scientists capture electronic response to ionization.

A breakthrough in electron microscopy based on deep learning can automatically visualize and identify areas of interest, helping to speed advances in materials science.

New research informs the development of foundational models for computational chemistry through hardware-software co-design.

Beyond melting ice and higher temperatures: On Earth Day, scientists consider how climate change will affect national security.

IDREAM research shows the size of cations in highly concentrated nitrite solutions affects the production of radicals.

As new paradigms in advanced computing take shape, computational chemistry researchers are finding new ways to solve challenging chemistry problems.

PNNL research exploring tungsten heavy alloys for use in advanced nuclear fusion reactors makes Scientific Reports Top 100 Collection.

Researchers investigated how stable nanoparticle suspensions form using facet engineering on hematite nanoparticles, demonstrating that controlling the faceting of nanoparticles can effectively maintain particle dispersity.

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.

Chemists Wilma Rishko and Samantha Johnson are set to receive an ACS Division of Inorganic Chemistry Award for Undergraduate Research as a mentor-mentee pair.

Researchers devised a quantitative and predictive understanding of the cloud chemistry of biomass-burning organic gases helping increase the understanding of wildfires.

Senior Advisor Isabella van Rooyen shares her journey from child to internationally recognized scientist in nuclear materials and manufacturing.

Reproducible workflows for binning and visualizing nuclear magnetic resonance spectra from environmental samples.