PNNL researchers combined deep operator networks with spectral methods to efficiently and accurately solve complex equations.

Gosline works to develop computational algorithms that are uniquely targeted for rare disease work by doing foundational research in model system development. This work can be expanded to all model systems in human disease.

The Public Infrastructure Security Cyber Education System is a university-community-nonprofit collaboration changing cyber education and cybersecurity.

RedEye is a first-of-its-kind tool that was created to improve the operations of red and blue teams.

Findings show method to better prepare human lung tissue for study; it represents the latest mass spectrometry-based omics advances.

The Joint Appointment program at PNNL is one of the most diverse among other U.S. national laboratories, involving nearly 60 universities and research institutions in the United States and abroad.

Space Systems Command and PNNL welcome the University of Texas at El Paso to the Cyber Halo Innovation Research Program.

HiSVSIM enables large-scale quantum simulations through graph partitioning.

PNNL joint appointee Auroop Ganguly uses data science to study the impacts of climate change.

A new web-based tool provides easy-to-understand progress metrics and other data about groundwater cleanup sites overseen by the DOE Office of Environmental Management.

Launching a premier partnership, PNNL and the University of Texas El Paso (UTEP) signed a memorandum of agreement on UTEP’s campus on October 6.

SEA-CROGS is one of four Mathematical Multifaceted Integrated Capability Centers selected for support by the Department of Energy.

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

Proteins from “auxiliary” genes in soil viruses play a role in the carbon cycle and climate, scientists have found.

A process developed at PNNL that converts biomass and waste into a chemical intermediate or into gasoline, diesel, and jet fuel is available for commercial licensing.

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

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

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