Electrical engineer Aditya Ashok and cybersecurity researcher Thomas Edgar win best paper award for their work to create a new high-fidelity dataset that will help advance cybersecurity solutions for critical infrastructure protection.
Developed at PNNL, Shear Assisted Processing and Extrusion, or ShAPE™, uses significantly less energy and can deliver components like wire, tubes and bars 10 times faster than conventional extrusion, with no sacrifice in quality.
PNNL has received 119 R&D 100 Awards since 1969, when the laboratory began submitting entries in the contest that recognizes top 100 inventions each year.
An energy-efficient method to extrude metal components wins Association of Washington Business Green Manufacturing Award. PNNL’s Shear Assisted Processing and Extrusion™ technology consumes less energy and enhances material properties.
Rotational Hammer Riveting, developed by PNNL, joins dissimilar materials quickly without preheating rivets. The friction-based riveting enables use of lightweight magnesium rivets and also works on aluminum and speeds manufacturing.
Researchers developed two solutions for air-conditioning—a novel, energy-efficient dehumidification system and a technology to detect refrigerant leaks. Both help increase energy-efficiency and reduce costs.
PNNL cybersecurity engineer Penny McKenzie was selected from hundreds of national laboratory mentors to join Secretary of Energy Jennifer Granholm on multi-laboratory DOE internship panel for summer interns.
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, chief scientist for decision intelligence and analytics at PNNL, was invited as a panelist at the SIAM International Conference on Data Mining
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.
PNNL computer scientists joined international leaders in machine learning to present research to detect and address potential cybersecurity threats and devise epidemic interventions.
For the second straight year, PNNL researchers are featured in a special edition of the Journal of Information Warfare. This issue explores the topic of macro cyber resiliency.