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News

A Steely Combination

News

PNNL Wins R&D 100 Awards

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.

Publication

The Youth Are Our Future: Mentor Mariefel Olarte Invests in Interns

PNNL chemical engineer Mariefel Olarte shares passion for mentoring students and the next-generation workforce.

News

From Curb to Doorstep: Driving Efficiencies for Delivering Goods

A webapp developed by PNNL in collaboration with the University of Washington to help drive efficiencies for urban delivery drivers is now in the prototype stage and ready for testing.

News

New Machine Learning Tool Tracks Urban Traffic Congestion

Using public data from the entire 1,500-square-mile Los Angeles metropolitan area, PNNL researchers reduced the time needed to create a traffic congestion model by an order of magnitude, from hours to minutes.

Publication

Friction Stir Processing Gets a Boost from New Machine Learning Model

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

Publication

PNNL and Partners Exhibit the Latest Energy Research at 2025 ARPA-E Energy Innovation Summit

The ARPA-E Energy Innovation Summit brings together researchers, industry leaders, entrepreneurs, and investors to showcase the latest technologies shaping tomorrow’s energy landscape. This year, eight projects led by PNNL were featured.

News

Looking Back, Moving Forward: Reflections from a Decade as PNNL Director

As Laboratory Director Steve Ashby pens his last monthly column, he highlights PNNL’s accomplishments with pride and gratitude.

News

Taming Tomorrow’s Wildfires

As wildfires grow increasingly severe, PNNL researchers are working to slow their spread and mitigate their harmful effects.

News

At PNNL, AI Is Accelerating the U.S. Bioeconomy

Predicting how organisms’ characteristics respond to not only their genes, but also their environments (a nascent field called predictive phenomics), is extraordinarily challenging. Researchers at PNNL are using AI to tackle that challenge.

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