A combined experimental and theoretical study identified multiple interactions that affect the performance of redox-active metal oxides for potential electrochemical separation and quantum computing applications.

Irradiated boehmite nanoplatelets form smaller aggregates and have a rougher surface than non-irradiated platelets.

Water affects the intermediates present on the surface of a metal oxide catalyst during ketonization.

PNNL welcomes new joint appointments to expand the research productivity and scientific impact of both PNNL and the university partners, broadening the base of expertise at each institution and helping to build interdisciplinary teams.

Combining peptoids and carbon nanotube porins creates a new class of stable membranes with potential applications in separations science.

A combined experimental and modeling study shows that electronic interactions direct how a metal-organic framework grows.

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.

Hydrogen bonding and proton transfer control the identity and reactivity of molecules in highly concentrated and alkaline aluminate solutions.

Within zeolite pores, rates of alcohol dehydration increase with ionic strength until reaching a maximum and then decreasing.

The work by the team at PNNL takes a critical step in leveraging ML to accelerate advanced manufacturing R&D, specifically for manufacturing techniques without access to efficient, first-principles simulations.

In a water-containing system, the open circuit potential stabilizes positively charged species and lowers the energy barrier of the reaction.

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.

Researchers identified a new intermediate phase that forms during the crystallization of hydrated aluminum-containing salts.

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.

A new deep learning approach allows researchers to rapidly analyze three-dimensional representations of multi-component catalysts.