PNNL is working with the Port of Seattle and Seattle City Light to assess the risks of long-term hydrogen storage that can bring clean power for decarbonization.

Data-driven autonomous technology to rapidly design and deliver antiviral interventions targeting SARS-CoV-2 to reduce drug discovery timeline and advance bio preparedness capabilities.

Harnessing the sea for decarbonized energy is the focus of a new collaboration between PNNL and the University of Guam.

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

A PNNL team developed and used a model framework to understand the performance and structural reliability of a state-of-the-art solid oxide electrolysis cell design.

Silicone wristbands could be more convenient option for collecting exposure data.

Tailoring hydrogen-based energy storage solutions to specific real-world applications.

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.

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.

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 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.

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.

Researchers have developed a new technique to visualize the activity and distribution of enzymes that mobilize phosphate around plant roots.