Simulations show that pH influences boehmite nanoparticle structure and sorption ability.

Developing a new understanding of the structure of natrophosphate, a complex mineral found in radioactive tank waste at the Hanford Site, by integrating experimental techniques.

Newly funded research will look at the underlying science of controlling hydrogen interactions with two-dimensional materials composed of carbon, boron, and nitrogen.

A newly funded research project draws inspiration from nature to store carbon dioxide.

New research makes molecular-level calculations of water faster and easier.

PNNL researchers teamed up with SambaNova to enhance artificial intelligence for scientific computing.

A new simple and scalable synthesis produces nanoparticle assemblies that can perform catalytic hydrogen sensing at room temperature for the first time.

New research from PNNL results in faster and more accurate variational quantum algorithm training.

A new approach to epitaxial growth can produce different complex oxides through ion movement.

The buried interfaces between sections of a doped material can play a key role in the overall electronic properties of the system.

Protein ribbons direct and facilitate the formation of a calcium-based mineral that forms tooth enamel.

PNNL researchers developed a hybrid quantum-classical approach for coupled-cluster Green’s function theory that maintains accuracy while cutting computational costs.

PNNL researchers created a model that helps materials scientists not only predict what is, but what could be.

PNNL researchers design an artificial intelligence-guided electron microscope in a Laboratory Directed Research and Development study.

Researchers are studying the chemical reactions that occur when oxygen mixes into the surface of oxide materials.

Tuning the environment and platinum-group metal allows researchers to control which bonds the catalyst breaks using hydrogen.

Combining multiple experimental techniques allowed researchers to observe the early stages of oxidation in a model material.

The size of the alkali metal within the material influences the crystallization pathway.

PNNL scientists developed new capabilities to study materials under extreme conditions.

Researchers use machine learning to speed up the analysis of aerosol datasets from mass spectrometry.