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.

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

PNNL researchers co-organized a workshop on fusion commercialization with partners from industry and academia

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

PNNL researchers will pursue both fundamental and applied projects with this support from the Department of Energy

Combining cold spray deposition and friction stir processing for a more efficient route to oxide dispersion strengthened steel.

PNNL researchers studied the microstructure of lithium silicates under emulated fusion conditions.

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

Researchers studied the boundary precipitation of tungsten heavy alloys in an extended high temperature irradiation environment

The Department of Energy Office of Nuclear Energy acting assistant secretary makes his first visit to a national laboratory in his new role, touring PNNL's Radiochemical Processing Laboratory.

Combining X-ray-based techniques allows researchers to locate and characterize small concentrations of electrons in complex semiconductor films.

Elias Nakouzi brings 3D atomic force microcopy expertise to a project focused on understanding how hybrid bio-based nanomaterials assemble.

Researchers created a methodology to design custom network topologies that improve the execution time for scientific applications.

The pathway of oxygen ion movement can be controlled based on the initial structure and substrate of strontium iron oxide thin films.

Researchers unveil user-friendly software to keep complex projects on budget and on schedule.

PNNL researchers present challenges and opportunities for fusing graph neural networks with deep reinforcement learning.

PNNL researchers demonstrated a simple method to create stable, identical nanoparticles of PdTe2-like composition, which is known to be superconducting, on a WTe2 TMD support.

PNNL researchers outline open problems in different scientific areas in the Journal of Combinatorics.

Methods review suggests ways to use artificial intelligence and machine learning to handle missing data when integrating two or more omics approaches.