Imaging ice microstructures formed by water freezing with atomic resolution for the first time.

Tailored assemblies mimic natural enzyme activity with significantly higher stability.

In high-entropy oxides, chromium tends to segregate during growth due to oxidation-induced migration of smaller, high-valence cations.

This summer, PNNL hosted the inaugural “As Conductive As Copper” (AC2.0) workshop, fostering a collaborative conversation on the future of the U.S. copper supply chain.

The first direct molecular-scale evidence of the temperature-driven transformation of the coordination environment of ytterbium at geologically relevant conditions.

Researchers developed a way to precisely control dopant structures and locations in carbon-based materials.

Researchers developed a pathway for the solution synthesis of core–crown heterostructures with controlled electronic properties.

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

Ampcera has an exclusive licensing agreement with PNNL to commercially develop and license a new battery material for applications such as vehicles and personal electronics.

RemPlex and IAEA convene international leaders to tackle recruitment and retention in complex environmental cleanup efforts.

Chromium cations better adapt to changes in oxygen stoichiometry than iron cations.

Using interfacial charge transfer to control cation charges in oxide superlattices offers insights for designing functional heterostructures.

PNNL's new energy storage facility now houses the Lab's vehicle battery research programs, which have more lab space and a slew of new capabilities.

Calcium carbonate mineralization occurs through a multi-step process that begins with a dense liquid phase.

New methodology can evaluate the potential for carbon storage and critical mineral recovery in undercharacterized geological settings.

A new database allows researchers to connect lattice parameters and composition in olivine.

A newly funded project will develop the fundamental understanding of phenomena that underpin material properties important for quantum applications.

PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.

Data from SOSAT web tool informs site selection and management for the subsurface injection of captured carbon dioxide.

Fully identifying what controls nanocrystal assembly requires incorporating non-traditional forces into models.