PNNL mathematician Aaron Luttman contributed to the organizing committee for workshop exploring robust machine learning and artificial intelligence systems for the U.S. Army.

PNNL’s contributions over the last year span scientific discovery, sustainable energy and national security.

Clarivate recently released the list of Highly Cited Researchers for 2022.

The Joint Appointment program at PNNL is one of the most diverse among other U.S. national laboratories, involving nearly 60 universities and research institutions in the United States and abroad.

Researchers developed a machine learning model that can analyze chemical reactions as they happen in an electron microscope.

Steven Spurgeon’s research is featured in the cover of the MRS Bulletin along with his team’s invited perspective on the future of machine learning for electron and scanning probe microscopy.

To thwart pathogens, researchers in the epidemiology field of infectious disease (ID) prediction are continuously trying to forecast when, where, and how an ID event will occur.

New research findings published in Science Advances (November 2022), help explain the progression of Alzheimer-related dementia in each patient. The findings outline a biological classification system that predicts disease severity.

As leaders in AI and machine learning, PNNL experts are sharing their latest findings at the 36th annual Neural Information Processing Systems (NeurIPS) Conference, Nov. 28–Dec. 9, 2022.

Data-driven experiments can help determine best practices for Random Forest machine learning to predict water quality, particularly nitrate levels.

Studying how microorganisms behave in space could facilitate farming in the final frontier and lead to better crops on Earth.

Silicone wristbands could be more convenient option for collecting exposure data.

Organismal contribution and community interaction drive soil organic matter breakdown by microbes.

PNNL researchers use machine learning and data analytics to assist with detection of nuclear proliferation and nuclear material trafficking.

PNNL computational neuroscientist Rogene Eichler West honored with the International Society for Neuroregulation & Research Joseph and Ann Marie Horvat Distinguished Service Award.

A new deep learning approach allows researchers to rapidly analyze three-dimensional representations of multi-component catalysts.

Using electrocatalysis offers a different path for reactions involving polar groups.

Where molybdenum dopants sit within catalytic material affects catalysis at a mechanistic level.

A new discovery simultaneously reduces the need for rare and expensive platinum and improves its ability to speed up economically important chemical reactions.

Scientists can detect the virus that causes COVID-19 by using a bubble that spills its contents like a piñata when encountering the virus.