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.

PNNL scientists developed a new, tiny battery and tag to track younger, smaller species, to evaluate behavior and estimate survival during downstream migration.

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

Svitlana Volkova uses natural language processing and AI to reveal how misinformation and disinformation spread through social media.

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

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

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.

The first customized resource of its kind, H-BEST analyzes the indoor environmental quality profile for buildings and helps its users identify the costs and benefits of improvements.

OpenCGRA expedites the design-prototype cycle of computer architecture development.

PNNL’s Framework for Assessment of Complex Environmental Tradeoffs helps navigate and evaluate competing environmental, economic, and social impacts.

PNNL is lending analytics expertise to a new first-of-its-kind electric-vehicle carsharing program being launched in Hood River, Oregon.

PNNL’s infrared pulsed heating technique reveals supercooled water’s weird behavior; opens door to other fluid studies at new Energy Sciences Center.

PNNL’s Data Archive and Portal that stores and disseminates wind energy data recently reached a major milestone: 1,000 users and growing.

U.S. Secretary of Energy Jennifer M. Granholm virtually visits PNNL, one of several national lab visits she is conducting.

PNNL is developing the Digital Twins for Hydropower framework to help the industry to affordably modernize the aging hydropower fleet.

Risk analysis on the plutonium-fueled power system that supplies electricity to the Mars rover answered the “what if” nuclear safety questions for NASA.

Spent nuclear fuel is being recycled to make new fuel through rapid separation and tight control of uranium and plutonium.

A webapp developed by PNNL in collaboration with the University of Washington to help drive efficiencies for urban delivery drivers is now in the prototype stage and ready for testing.

A collaboration among PNNL, Washington State University, and Tsinghua University has led to the discovery of a mechanism behind the decline in performance of an advanced copper-based catalyst.

PNNL has released the first version of ExaGO, an open-source grid modeling software that can take advantage of emerging heterogeneous computing architecture to help grid operators plan ahead for extreme events.