PermitAI’s newly released dataset, NEPATEC 2.0, captures and curates environmental review data for faster, better federal permitting.

Micron and PNNL co-design the Crete computer system, delivering a new memory architecture for data-intensive scientific computing and AI applications.

PNNL researchers continue to deliver high-quality, high-impact research on radioactive waste and nuclear materials management, earning “Papers of Note” and “Superior Paper” awards.

After isolating copper hydride monomers, researchers identified the mechanistic details of catalyst aggregation and cluster formation.

Scientists have tapped AI and powerful computing to speed up how quickly officials are able to learn important details about nuclear events.

The Department of Energy Art of Science contest entry focuses on the extraordinary universe of chemical bond making and breaking under irradiation.

Trace amounts of iron and chromium can incorporate into gibbsite, affecting how the mineral dissolves.

Quantum computing promises leaps in chemistry and materials science, and PNNL is preparing to realize its potential with a collaborative approach.

New electees represent research in genomics, grid resilience, coastal ecology, and more.

PNNL researchers showcased subsurface sampling and remediation expertise at the 2025 Federal Remediation Technologies Roundtable.

Patricia Paviet has led 100+ international webinars, building a vital global resource for next-generation nuclear energy education and collaboration.

PNNL STEM Ambassadors engage students about salmon migration, hydropower, cybersecurity, water quality, and more at the annual Salmon Summit.

Properly identifying iodoplumbate species that are present and stable in a perovskite precursor solution is vital. New research offers insight into reactivity and dynamical processes in solution and the chemical properties of precursors.

Zhiqun (Daniel) Deng, Lab Fellow at PNNL, has been named a fellow of the American Society of Mechanical Engineers, an honor that recognizes outstanding engineering achievements.

A new time-dependent wavefunction formulation for the cumulant Green’s functions can produce more accurate simulations.

PNNL’s science and technology helps hydropower operators detect, prevent and recover from cyberattacks while protecting a source of electricity that enhances grid reliability and resilience.

Scientists are reviewing the current science of the mechanism and structural dynamics of methyl coenzyme-M reductase, an enzyme involved in biological methane conversion.

A team combined experiments and theory to predict the collective properties of electrolyte solutions.

Neural networks techniques enable the efficient capture of electron correlation effects in reduced-dimensionality spaces.

Under an optical field, nanoparticle attachment in a model system heavily depends on surface roughness.