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.

PNNL recently worked with Purdue University to host a Cybersecurity Summit for PNNL researchers to find out more about the research at Purdue’s Center for Education and Research in Information Assurance and 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 materials scientist Dongsheng Li looks forward to using a co-located collection of advanced research equipment in the new Energy Sciences Center.

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

Svitlana Volkova, chief scientist for decision intelligence and analytics at PNNL, was invited as a panelist at the SIAM International Conference on Data Mining

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.

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.

When the COVID-19 pandemic halted all travel for in-person inspections, a team at PNNL knew they needed to find a way to perform assessments virtually. Their solution—a portable kit that could be shipped to locations.

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.

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

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

PNNL data scientists Svitlana Volkova and Emily Saldanha, along with former PNNL intern Pamela Bilo Thomas, will publish their research on online information spread in Nature's Scientific Reports.