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

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

PNNL scientists have developed a new mass spectrometry method for in-depth analysis of proteins in individual cells.

Data from increasingly complex mass spectrometry instruments met with adaptable data analysis solution.

Different sized helium cavities that form after ion irradiation are unevenly distributed in a ductile-phase toughened tungsten composite.

IDREAM researchers assess the potential of photon-in/photon-out XFEL techniques to explore early time reaction steps and ultimately improve nuclear waste processing strategies.

Researchers characterize protein signatures that indicate Acute Kidney Injury in COVID-19 patients.

Simulations reveal advantages of using new model vs. allometric scaling for risk assessment.

A multi-institutional team has developed a deep learning framework to identify novel molecules as drug candidates.

New PNNL research provides the first direct evidence that amorphous intermediates influence subsequent crystallization outcomes using in situ imaging.

A strengthened softer alloy phase increases the toughness of a tungsten composite material.

Hypergraphs can more faithfully identify important genes in complex immune responses.

The web-based tool, called PLATIPUS, is publicly available and interacts with publications available in the CovidScholar database.

New study elucidates the complex relaxation kinetics of supercooled water using a pulsed laser heating technique at previously inaccessible temperatures.

New quantum chemistry pipeline can help predict the effects of bioengineering.

High-throughput biochemical assays targeting a vital viral protein identified one molecule out of more than 13,000 with promising antiviral activity against SARS-CoV-2.

Understanding lipid composition of ant fungal gardens provides new knowledge on interkingdom communications band and also advances toward the development of microbial systems that can produce valuable compounds from plant biomass.

Researchers developed a new tool that combines artificial intelligence and microscopy data to rapidly test new materials for fusion reactor use.

By studying discrete functional components of the soil microbiome at high resolution, researchers obtained a more complete picture of soil diversity compared to analysis of the entire soil community.

Researchers trained deep neural networks to accurately predict microbial interactions captured by fluorescence microscopy.