Uncovered the molecular basis of nitric acid speciation across dilute and concentrated solutions and identified competing hydration-shell rearrangements around lanthanide ions at the dilute limit.

A new memorandum of understanding creates a framework for expanded research, talent development, and technology transfer between Georgia Tech and PNNL.

Across 47 sites in the Yakima River Basin of Washington State, faster oxygen consumption occurred with warmer water, more nutrients, and more suspended solids.

Researchers reveal how uncharacterized molecules affect the diversity and composition of dissolved organic matter in rivers.

Measurements show river flow volumes and seasonal timing have shifted; models project where flows will rise, fall, or shift in the future.

Yong Wang’s joint appointment connects PNNL, WSU, and the next generation of scientists.

Demonstrated that cathodic potential accelerates aqueous phase benzaldehyde hydrogenation.

Artificial intelligence helps analyze images and reduce uncertainty for a key measure of watershed function.

Dynamic organic matter traits tied to reactions can surpass static descriptors in explaining decomposition rates and responses to environmental change.

Using an AI approach to combine outputs from microbial models and apply them as inputs to reactive-transport models reduces computational time by several orders of magnitude.

Researchers showed that spiking neural networks can be accurate for regression problems, opening opportunities for efficient neuromorphic computing.

Research provided definitive spectroscopic characterization, reactivity, and deactivation of a reactive monomeric diphosphine-copper hydride intermediate.

PNNL scientists were among the specialists keeping the crowds safe at the recent FIFA World Cup competition.

Developed a method for selectively anchoring diverse divalent metal cations in zeolites, important for precise control over catalytic materials.

Developed a simple kinetic framework for evaluating catalyst hydride transfer ability.

PNNL has formed a partnership with the Orlando-based firm Refinity, which has licensed a key process from PNNL that will help the company convert mixed plastic waste into valuable industrial products like chemicals, plastics, and fuels.

New partnership agreement to focus on AI, robotics, and advanced energy systems.

A new report highlights a public workshop hosted by the National Academies Forum on Microbial Threats and features PNNL's Lauren Charles and the AI-Driven One Health Security program.

A research team from Pacific Northwest National Laboratory used machine reasoning to schedule scientific workflows while guaranteeing quality of service (QoS).

Researchers at PNNL have developed an interpretable, lightweight AI model that can easily predict weld microstructure features using only basic machine sensor inputs.