Three research teams led by PNNL organizers achieve journal publications following the Mathematics Research Communities program.

PNNL showcased its expertise in AI, machine learning, and related domains at the International Conference on Machine Learning.

Dušan Veličković, a PNNL mass spectrometry imaging scientist received a $2.1 million grant to develop techniques to understand how changes in carbohydrate structure affect human health.

Expanding the nation’s largest wind power plant time series database; helping grid planners navigate a resilient energy future with better data.

PNNL has created and licensed a system that sniffs out trace levels of fentanyl, other drugs and explosives through the air.

PNNL researchers have published their paper, “Introducing Molecular Hypernetworks for Discovery in Multidimensional Metabolomics Data,” in the Journal of Proteome Research.

Researchers can now quantify uncertainty in trained AI models aimed at solving difficult chemistry, biology and materials science problems.

Researchers have created an algorithm that slashes the calculations necessary to prepare and customize data for quantum computing.

Over the next four years, PNNL and University of Arizona will develop open-source computational tools to better identify and characterize the viruses associated with the human microbiome.

Scientists are exploring how web search engine technology might also keep the lights on, the water running and the trains moving.

Researchers developed a robust, cost-effective, and easy-to-use cap-based technique for spatial proteome mapping, addressing the lack of accessible proteomics technologies for studying tissue heterogeneity and microenvironments.

Scientists are developing ways to detect previously unseen forms of fentanyl as well as other synthetic opioids known as nitazenes.

A team of researchers at PNNL is developing a new approach to explore the higher-dimensional shape of cyber systems to identify signatures of adversarial attacks.

Scientists plumbed the depths of nearly 3,000 soil samples from around the globe to compile the heftiest atlas of soil viruses ever created.

A cross-institutional team of scientists developed PeakQC, a new software tool for automated quality control of mass spectrometry data.

Three PNNL researchers will receive five continuous years of funding for projects through highly competitive DOE Early Career Research Program awards.

The Department of Energy’s Vehicle Technologies Office recognized Livewire’s outstanding teamwork and technical expertise.

Despite the widespread presence of RNA viruses in soils, little is known about the relative contributions and interactions of biological and environmental factors shaping the composition of soil RNA viral communities.

Ljiljana Paša-Tolić, a PNNL fellow, is the recipient of the 2024 International Mass Spectrometry Foundation’s Jochen Franzen Award. 

Scientists have developed a way to detect tiny amounts of hard-to-detect explosives more than eight feet away.