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

The Center for Continuum Computing at PNNL aims to integrate cloud platforms, high-performance computing, and edge devices into a seamless ecosystem that accelerates scientific discovery.

PNNL’s Center for Cloud Computing is addressing challenges in data management and hybrid cloud solutions with industry and academic partnerships.

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

In a recent publication in Nature Communications, a team of researchers presents a mathematical theory to address the challenge of barren plateaus in quantum machine learning.

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

In the latest issue of the Domestic Preparedness Journal, Ashley Bradley and Kristin Omberg share how new research is shedding light on the scientific and technological challenges with detecting fentanyl.

New research sheds light on the biomolecular dangers of night shift work.

PNNL contributes to a nationwide research consortium investigating the molecular mechanisms triggered by endurance training.

A new report highlights the results of an assessment PNNL conducted of field-portable detection products used by first responders to detect illicit substances like fentanyl in the field.

A streamlined informatics workflow that automatically processes complex data and provides the locations of double bonds in lipids.

Hi-C metagenomics-informed phage-host infection networks detected in soil pre- and post-drying.

Scientists have developed a better way to recognize denial-of-service internet attacks, improving detection by 90 percent.

PNNL researchers outline open problems in different scientific areas in the Journal of Combinatorics.

Metabolomics analysis revealed differences in metabolome profiles for two distinct modes of fungal wood decay.

Researchers have knitted together three large databases of information to help cybersecurity experts detect and prevent attacks.

Scientists have taken a key step toward harnessing a form of AI known as deep reinforcement learning to protect computer networks.

HiSVSIM enables large-scale quantum simulations through graph partitioning.

James Ang, John Feo, and Marco Minutoli organized a high performance computing workshop at the prestigious ISC High Performance 2022 conference.

Data from increasingly complex mass spectrometry instruments met with adaptable data analysis solution.