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.

PNNL's Rich Ozanich, project manager of opioids standards and equipment testing, served on an expert panel about opioid detection as part of a Department of Homeland Security S&T research and development showcase.

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

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

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

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

Scientists have created a cybersecurity technology that stops hackers from doing damage by feeding them illusory tidbits of success.

The multi-year project funded by DOE’s High Energy Physics program will focus on using machine learning to prevent power outages.

The DOE Early Career Research Program supports exceptional researchers during the crucial early years of their careers and helps advance scientific discovery in fundamental sciences

A new report finds small modular reactors could provide competitively priced electricity in Washington state's future electricity market.

Researchers delivering new solutions to speed development and deployment of advanced reactor concepts.

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

Analytical chemist shares passion for STEM, innovation and nuclear fuel

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

Marcel Baer is a computational scientist working in PNNL’s Physical Sciences Division with a prominent effort in materials science and physical bioscience.

New computational modeling research provides insights into biological processes and metabolic regulation.

In the face of the COVID-19 pandemic, PNNL pivoted to online learning approaches to conduct critical national security training across the globe.

PNNL computer scientists joined international leaders in machine learning to present research to detect and address potential cybersecurity threats and devise epidemic interventions.

With quantum chemistry, researchers led by PNNL computational scientist Simone Raugei are discovering how enzymes such as nitrogenase serve as natural catalysts that efficiently break apart molecular bonds to control energy and matter.