Engineers at PNNL devised a system that allows radar antennae to maintain stable orientation while mounted on platforms in open water that pitch and roll unpredictably. They were recently invited to participate in DOE's I-Corps program.

Continued studies will deepen scientists’ understanding of virus-host interactions at the molecular level and also pave the way for developing better drugs to fight emerging viruses.

Flexible, high-throughput proteomics approach identifies protein modifications related to pancreatic stress and insulin production.

Scientists map how transitions from day to night control gene regulatory networks in cyanobacteria, revealing key orchestrators of metabolic switching.

Scientists uncover how cyanobacteria's circadian cycle controls carbon and energy metabolism, increasing carbon dioxide-to-bioproducts yields.

PNNL is hosting a scientific conference focused directly on understanding and predicting the collection of an organism’s traits.

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

Circadian rhythms of blue-green microbes offer new window into predictive phenomics—how to predict and control the traits of an organism.

This week at AAAS, PNNL scientists discuss phenomics and the factors that influence DNA instructions to bring about the world around us.

A new report details the potential for floating offshore wind to lower energy costs and enhance the resilience of the nation’s western grid.

A new generation of microelectronics research begins at PNNL.

PNNL was well represented at the NAWEA/WindTech 2024 Conference with 13 PNNL experts at the conference sponsored by the North American Wind Energy Academy.

PNNL scientists use proteomics to unveil how high-density lipoproteins protect against cholesterol accumulation in the artery wall.

Computing and artificial intelligence aid scientists who seek to understand function-driven design and control of biological systems.

Calculating quantum chemistry quickly allows scientists to refine their understanding of complex chemical systems.

The speed and agility of cloud computing opens doors to completing advanced computational chemistry workflows in days instead of months.

Researchers discussed this topic at the 2024 Analog Computing for Science Workshop co-led by Antonino Tumeo.

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.