The size of graphene oxide sheets affects the ability of assembled membranes and adsorbents to separate rare earth elements.

PNNL recently hosted a training exercise that immersed the U.S. Coast Guard 2013 Cyber Protection Team in a lifelike simulation of a cyberattack on a U.S. port terminal.

Scientists have tapped AI and powerful computing to speed up how quickly officials are able to learn important details about nuclear events.

CESER and PNNL convened a three-day summit with more than 100 state officials, cybersecurity experts, and industry leaders across 35 states to advance energy security planning, cyber risk assessment, and fortify protections against attacks.

Danny Herrera, a systems engineer and leader in the National Security Directorate at PNNL, has been named the new co-director of the Institute for Cybersecurity and Resilient Infrastructure Studies.

A PNNL team has developed an energy- and chemical-efficient method of separating valuable critical minerals from dissolved solutions of rare earth element magnets.

PNNL was recognized for its significant contributions to projects at the Secretary’s Honor Awards Ceremony in Washington, D.C.

Surface manganese mining from nodules in South Dakota is now possible with a new scalable selective precipitation process.

Scientists are exploring how web search engine technology might also keep the lights on, the water running and the trains moving.

By combining computational modeling with experimental research, scientists identified a promising composition that reduces the need for a critical material in an alloy that can withstand extreme environments.

Cobalt substitution for magnesium in a model mafic mineral dramatically slows reaction with carbon dioxide to form a cobalt-doped carbonate.

The Testing Risks of AI for National Security Taskforce will address critical safety and security concerns related to artificial intelligence.

Precipitation with sodium hydroxide in a flow-gel device enables the rapid extraction of magnesium from seawater in a new scalable process.

Protecting critical systems such as the electrical grid from cyber-based risks to the supply chain is the focus of a new PNNL conference.

PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.

Operators of critical infrastructure are trained to respond to cyberattacks using scale models of water treatment plants, freight rail yards, and more.

Ryan Eddy, director of homeland security programs at PNNL, was recognized as one of 50 trailblazers by Homeland Security Today.

At PNNL, researchers are taking a wider look at the system through the supply chain’s lifecycle and subcomponents to determine the big-picture risks.

The atomic-level distribution of nickel and cobalt in forsterite depends on the concentration of the different elements.

The surface oxygen functionality of graphene oxide may be tuned using ultraviolet light, affecting how differently charged ions move through the material.