PNNL researcher Erol Cromwell uses neural networks to elucidate subsurface permeability.

PNNL computational scientist Diana Bacon’s role as carbon storage associate editor uses her expertise in subsurface modeling and quantitative risk assessment.

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

When training for chemical and biological threats, in-person exercises and drills can be very limited due to the hazardous nature of the agent.

PNNL’s new Hydrogen Energy Storage Evaluation Tool allows users to examine multiple energy delivery pathways and grid applications to maximize benefits.

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.

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.

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.

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

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.

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

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

Researchers used deep learning methods to estimate the subsurface permeability of a watershed from stream discharge measurements.

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

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

A shoe scanner may allow people passing through security screening to keep their shoes on. PNNL built the scanner based on the same technology it used to develop airport scanners. It's licensed to Liberty Defense.

Erol Cromwell and Yan Shi, researchers at PNNL, used their backgrounds in software engineering to provide a platform for atmospheric data analysis.