Steven Spurgeon, a materials scientist and microscopy researcher at PNNL, has accepted an affiliate associate professorship at the University of Washington Department of Physics.

PNNL’s Jie Xiao and Yuyan Shao are serving two-year terms on the executive committee of the Pacific Northwest section of The Electrochemical Society, which was chartered in October 2020.

Researchers have been investigating if machine learning techniques could be used to help create novel beers.

A multi-institutional team has developed a deep learning framework to identify novel molecules as drug candidates.

Human-machine teaming may sound like something from the distant future. In “Human-Machine Teaming: A Vision of Future Law Enforcement” in Domestic Preparedness, Corey Fallon, Kris Cook, and Grant Tietje of PNNL examine this topic.

The Battery500 Consortium, led by PNNL, has been awarded $75 million for advancing battery technologies over the next five years.

Artificial intelligence-based decision tool enables grid operators to respond more quickly and effectively to grid emergencies.

PNNL is highlighting scientific and technical experts in the national security domain who were recently promoted to scientist and engineer Level 5, one of PNNL’s most senior research roles.

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.

One effort toward better batteries for electric vehicles is hitting overdrive, thanks to new findings about the desirable silicon anode.

A new model offers more accurate predictions of how intensely hurricanes may strike.

PNNL data scientists are refining their artificial intelligence tools with COVID-19 data to advance therapeutics and treatments for a future pandemic.

PNNL data scientist was invited to give the first big-picture talk about autonomous control systems at the Autonomous Discovery in Science and Engineering Workshop.

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.

A team of PNNL researchers are looking at how to evaluate robustness and accountability, fairness, and transparency of artificial intelligence models used to detect and quantify deceptive content online.

A Q&A with Lauren Charles, veterinarian and PNNL data scientist, on zoonotic diseases and the role biosurveillance plays in mitigating the growing threat to global health.

More than 30 PNNL interns contributed to the Airport Risk Assessment Model, a web-based tool that helps airport security stakeholders prioritize resource allocations.

PNNL’s data-infused approach to electron microscopes’ use in scientific experimentation will help researchers and industry interpret large data streams and drive down costs.