A PNNL-developed computational framework accurately predicts the thermomechanical history and microstructure evolution of materials designed using solid phase processing, allowing scientists to custom design metals with desired properties.

Cesar Moriel from University of Texas at El Paso will be interning at the PNNL over the summer as part of the Energy Environment Diversity Internship Program.

A review article led by researcher Jade Holliman explores the different classes of metamaterials, from the underlying fundamental science to potential applications.

Researchers developed a machine learning model that can analyze chemical reactions as they happen in an electron microscope.

PNNL researchers are moving energy research forward through collaborative projects with universities across the United States.

Research published in Journal of Manufacturing Processes demonstrates innovative single-step method to manufacture oxide dispersion strengthened copper materials from powder.

One year into an Early Career Research Program award, Marcel Baer is developing new workflows to model biologically inspired systems more efficiently.

Tailoring hydrogen-based energy storage solutions to specific real-world applications.

HiSVSIM enables large-scale quantum simulations through graph partitioning.

PNNL research, featured on the cover of two science journals, describes advancements in using Raman spectrometry for Hanford Site nuclear waste remediation.

Developing a new understanding of the structure of natrophosphate, a complex mineral found in radioactive tank waste at the Hanford Site, by integrating experimental techniques.

Newly funded research will look at the underlying science of controlling hydrogen interactions with two-dimensional materials composed of carbon, boron, and nitrogen.

A newly funded research project draws inspiration from nature to store carbon dioxide.

New research shows that compressing quantum circuits decreases noise and increases the accuracy of quantum calculations.

New research from PNNL results in faster and more accurate variational quantum algorithm training.

A new approach to epitaxial growth can produce different complex oxides through ion movement.

Protein ribbons direct and facilitate the formation of a calcium-based mineral that forms tooth enamel.

Tuning the environment and platinum-group metal allows researchers to control which bonds the catalyst breaks using hydrogen.

PNNL scientists developed new capabilities to study materials under extreme conditions.