In the search for rare physics events, extremely pure materials are essential. A partnership between PNNL and Ultramet has led to tungsten with low contamination from other elements.

PNNL researchers have published their paper “Introducing Molecular Hypernetworks for Discovery in Multidimensional Metabolomics Data” in the Journal of Proteome Research.

Neural networks techniques enable the efficient capture of electron correlation effects in reduced-dimensionality spaces.

The Center for Continuum Computing at PNNL aims to integrate cloud platforms, high-performance computing, and edge devices into a seamless ecosystem that accelerates scientific discovery.

A new study led by PNNL researcher TC Chakraborty provides some answers about how irrigated agricultural land near cities affects urban heat stress.

Erik Lentz and Christian Boutan will research quantum information science-enabled discoveries in high energy physics with these awards.

Developing a new scheme to more efficiently solve quantum chemistry problems.

Formal mathematics both reveals what’s inside the black box of AI algorithms and pushes the boundary of what’s possible within math as a discipline.

Researchers have created an algorithm that slashes the calculations necessary to prepare and customize data for quantum computing.

Andrew Gettelman at PNNL elected as president of the Atmospheric Sciences section of the American Geophysical Union.

A potential quantum advantage for fluid dynamics simulations from molecular to atmospheric scales with a new formula for success.

Several Earth system components are at a high risk of undergoing rapid, irreversible qualitative changes or ‘tipping’ with increasing climate warming.

Seawater threatens to intrude into coastal freshwater aquifers that millions of people depend on for drinking water and irrigation. This study investigates sea-level rise impacts on the global coastal groundwater table.

New datasets delineating global urban land support scientific research, application, and policy, but they can produce different results when applied to the same problem making it difficult for researchers to decide which to use.

A tethered balloon system was used at the Southern Great Plains atmospheric observatory in Oklahoma to collect atmospheric particles from ground and aloft levels. Samples were later analyzed for their organic molecular composition.

Better understanding how clouds mix with surrounding dry air is crucial for accurate weather and climate predictions.

Pacific Northwest National Laboratory researchers developed a new theoretical method for studying highly correlated systems.

A recent paper published in Science sheds light on how aerosols—tiny particles in the air—released by industrial activities can trigger downstream snowfall events.

Knowing future snow levels is key for managing the recovery of endangered bighorn sheep. PNNL scientists help to forecast how the sheep could fare.

His expertise in data science and commitment to open science will drive dataset dissemination and advance collaborative global research efforts.