Former PNNL intern Michael Hewitt was recognized by DOE as an Outstanding Intern for the research he performed alongside PNNL physical chemist Dr. Grant Johnson.
New mathematical tools developed at PNNL hold promise to transform the way we operate and defend complex cyber-physical systems, such as the power grid.
Red teaming for CPS, the process of challenging systems, involves a group of cybersecurity experts to emulate end-to-end cyberattacks following a set of realistic tactics, techniques, and procedures.
A new review paper led by senior research scientist Chun-Long Chen and featured on the cover of Accounts of Chemical Research summarizes advances by PNNL scientists in developing sequence-defined peptoids.
Beginning in 2021, PNNL chemical physicist Bruce Kay begins a three-year term as an AVS trustee, part of a six-member committee responsible for overseeing the administration of student scholarships and major society awards.
A special issue of the Marine Technology Society Journal, titled “Utilizing Offshore Resources for Renewable Energy Development,” focuses on research and development efforts including those at Pacific Northwest National Laboratory (PNNL).
In a new video series, PNNL is highlighting six scientific and technical experts in the national security domain throughout the fall. Each was promoted to scientist and engineer level 5 earlier this year.
PNNL researchers developed two web-based tools to assess and mitigate cyberthreats to utilities—inside and outside their firewalls. Both are low cost and can be used by control room operators who are not cybersecurity experts.
PNNL researchers established an Internet of Things Common Operating Environment (IoTCOE) laboratory to explore the risks associated with IoT connectivity to the internet, the energy grid and other critical infrastructures.
The Facility Cybersecurity toolkit, developed by PNNL, is designed for federal facilities to help implement the presidential executive order on cybersecurity, but it is also available for commercial facilities without charge.
PNNL has three small-scale spectroscopy devices that are speeding up the testing and analysis of candidate novel materials used in energy storage research and environmental remediation.
Pacific Northwest National Laboratory researchers used machine learning to explore the largest water clusters database, identifying—with the most accurate neural network—important information about this life-essential molecule.