PNNL senior materials scientist Keerti Kappagantula has been named to the 2023 Nominating Committee of ASM International.

Thin oxide films play an important role in electronics and energy storage. Researchers in PNNL’s film growth laboratory create, explore, and improve new thin oxide films.

Mitra Taheri served as a co-editor on a special issue of the Materials Research Society Bulletin, which also featured work from Daniel Schreiber and Cindy Powell.

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

Machine learning models help identify important environmental properties that influence how often extreme rain events occur with critical intensity and duration.

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.

PNNL researchers combined deep operator networks with spectral methods to efficiently and accurately solve complex equations.

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.

The Building and Environment journal named Drgoňa’s co-authored work one of 2022’s best papers.

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

Data-driven autonomous technology to rapidly design and deliver antiviral interventions targeting SARS-CoV-2 to reduce drug discovery timeline and advance bio preparedness capabilities.

Data scientist Jung Lee accepted the position of review editor for Frontiers in Computational Neuroscience after serving as a guest editor for a special issue.

Scientists have taken a key step toward harnessing a form of AI known as deep reinforcement learning to protect computer networks.

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