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.

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

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.

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.

AAAS Fellows are a distinguished cadre of scientists, engineers, and innovators who have been recognized for their achievements across disciplines.

Johannes Lercher receives award from the North American Catalysis Society and the European Federation of Catalysis Societies.

PNNL will partner with Commonwealth Fusion Systems to develop innovative steel materials for fusion applications under the INFUSE program

Tungsten heavy alloys show promise for nuclear fusion energy development, according to new research conducted at PNNL.

Tom Autrey presented at a forum to foster collaboration between Korea and the United States to develop hydrogen-related technologies.

PNNL’s contributions over the last year span scientific discovery, sustainable energy and national security.

Clarivate recently released the list of Highly Cited Researchers for 2022.

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.

Materials scientist Arun Devaraj has joined the editorial board of npj Materials Degradation.

Steven Spurgeon’s research is featured in the cover of the MRS Bulletin along with his team’s invited perspective on the future of machine learning for electron and scanning probe microscopy.

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.