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

PNNL researchers launch a new DOE project focused on advancing GUV technology for improved public health outcomes and decarbonization benefits.

PNNL’s contributions over the last year span scientific discovery, sustainable energy and national security.

The Simple Building Calculator, developed at PNNL, meets a need for a quick, interactive, and economic method to evaluate energy use—and potential savings from efficiency measures—in simple commercial buildings.

Clarivate recently released the list of Highly Cited Researchers for 2022.

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.

For a second year in a row, doctoral intern Jack Watson was awarded the Student Merit Award by the Society for Risk Analysis and the Resilience Analysis Specialty group.

PNNL scientists Daniel Gaspar and Wei Wang were among nine scientists featured in journal article recognizing 2021-2022 ACS award honorees.

Research published in Journal of Manufacturing Processes demonstrates innovative single-step method to manufacture oxide dispersion strengthened copper materials from powder.

To thwart pathogens, researchers in the epidemiology field of infectious disease (ID) prediction are continuously trying to forecast when, where, and how an ID event will occur.

Five staff members from PNNL received awards from the Department of Energy’s Federal Energy Management Program for contributions to projects for the U.S. Army.

New research findings published in Science Advances (November 2022), help explain the progression of Alzheimer-related dementia in each patient. The findings outline a biological classification system that predicts disease severity.

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.

Multidisciplinary teams from research and industry are brought together using management systems developed by a team of software engineers at PNNL.

Data-driven experiments can help determine best practices for Random Forest machine learning to predict water quality, particularly nitrate levels.

Studying how microorganisms behave in space could facilitate farming in the final frontier and lead to better crops on Earth.

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

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

Organismal contribution and community interaction drive soil organic matter breakdown by microbes.

Direct visualization of metal atoms during shear deformation has broad applications from battery design to vehicle lightweighting.