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

Under an optical field, nanoparticle attachment in a model system heavily depends on surface roughness.

Researchers at PNNL advised elementary and middle school student teams with their problem-solving research for the FIRST® LEGO® League robotics competitions.

Jingshan Du, a postdoctoral scientist at PNNL whose research focuses on crystallization pathways of water and other materials, was named a 2025 CAS Future Leader.

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.

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

Machine learning and autonomous experimentation are poised to revolutionize how scientists grow very thin films on surfaces, important for technologies like microelectronics and quantum computing.

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

Chromium cations better adapt to changes in oxygen stoichiometry than iron cations.

A new generation of microelectronics research begins at PNNL.

Using interfacial charge transfer to control cation charges in oxide superlattices offers insights for designing functional heterostructures.

Calcium carbonate mineralization occurs through a multi-step process that begins with a dense liquid phase.

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

Postdoctoral scientist Jingshan Du received the Nanoscale Science and Technology Division Early Career Award from AVS.

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

Graduate student Ying Xia has been selected as a Graduate Student Award Finalist for the 2024 Materials Research Society Fall Meeting.

A new digital twin platform can help hydropower dam operators by providing accurate and predictive models of physical turbines that improve facilities and enhance reliability.