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

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 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.

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

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

A novel database of tracked deep convective storms reveals how environmental factors affect storm formation and growth in South America.

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.

Investigating cloud condensation nuclei activities in various airmasses enabled linking activity variations with organic oxidation levels and volatility

New study investigates how to use a non-toxic condensation particle counter for airborne atmospheric research

The COVID-19 pandemic massively disrupted human activities, which caused additional turmoil through regional record rainfall and floods.

A new capability facilitates source apportionment of organic aerosols in real time.

Measuring the ice nucleation activity of particles in the ambient atmosphere can help develop better representations for use in climate models.

PNNL contributes to 30 years of data on clouds, radiation, and other climate-making factors as part of field campaigns and analysis conducted by DOE's Atmospheric Radiation Measurement user facility.

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

Combining advanced powder synthesis with solid state processing allows researchers to streamline oxide dispersion-strengthened steel fabrication.