Three recent doctoral graduates are beginning their research careers at Pacific Northwest National Laboratory after completing the WSU-PNNL Distinguished Graduate Research Program this spring.

Seeking a deeper understanding of when, where, and why large wildfires occur using explainable artificial intelligence.

Local ionic strength within zeolite pores tailors the chemical potential of reacting molecules, leading to high cyclohexanol dehydration activity

PNNL senior electrical engineer, Amy Qiao, tapped to serve IEEE Photonics Society Emerging Technologies Task Force.

Urban pollution greatly increases the number of particles over the Amazon, mainly through new particle formation controlled by biogenic gases.

PNNL dose reconstruction expert Bruce Napier reviews report on public exposure to ionizing radiation for the United Nations.

Federal and industry-matched funding will move 11 technologies closer to commercialization where they could one day help bolster U.S. competitiveness.

Researchers have increased the lifetime of a promising electric vehicle battery to a record level.

Materials scientist Shuttha Shutthanandan has been named an American Vacuum Society fellow.

Kristin Burnum-Johnson presented at two virtual events in June on proteome mapping.

A high-resolution dataset captures a more complete view of the global distribution and characteristics of strong storms called mesoscale convective systems.

Rising greenhouse gases and declining aerosols have triggered an approximate four-day delay in rainfall over tropical land and the Sahel.

PNNL combines AI and cloud computing with damage assessment tool to predict path of wildfires and quickly evaluate the impact of natural disasters, giving first responders an upper hand.

At PNNL, women in engineering tackle some of the world’s most complex problems in environmental science, sustainable energy, and national security.

Researchers to design their own computer accelerators for faster analysis of large datasets.

PNNL provided ultra-low measurements of argon-39 to date groundwater as part of a collaborative study of the aquifer in California’s San Joaquin Valley. PNNL is one of only a few laboratories worldwide with this capability.

Machine learning techniques are accelerating the development of stronger alloys for power plants, which will yield efficiency, cost, and decarbonization benefits.

PNNL’s energy-efficient dehumidifier may reduce energy consumption by up to 50% in residential A/C systems and increase the range of electric vehicles by up to 75%. The system has been licensed to Montana Technologies.

Stanford-bound aspiring scientist gained valuable national laboratory research experiences through the Community College Internship program at PNNL.

PNNL materials scientist Dongsheng Li looks forward to using a co-located collection of advanced research equipment in the new Energy Sciences Center.