Nineteen PNNL-affiliated researchers have been named to Clarivate’s 2024 list of the world's most highly cited researchers.

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

Klickitat Valley Health's fuel cell and microgrid project boosts rural healthcare, enhancing energy resilience and sustainability for social equity.

A Helios Hydra UX DualBeam, which utilizes a plasma focused ion beam and scanning electron microscope for sample preparation and analysis, was installed at the Grid Storage Launchpad.

PNNL researchers work with industry partners to transform large language models.

University of Washington Professor David Baker won the 2024 Nobel Prize in Chemistry for computational protein design.

The Sodium-ion Alliance for Grid Energy Storage, led by PNNL, is focused on demonstrating high-performance, low-cost, safe sodium-ion batteries tested for real-world grid applications.

Pacific Northwest National Laboratory scientists discussed their materials research at Accelerate’24.

PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.

Three PNNL-supported projects are at the forefront of developing advanced data analytics technologies to enhance the U.S. power grid’s reliability, resilience, and affordability.

This work shows that linear pattern scaling is an effective means of obtaining global-to-local relationships for CMIP6 models, as it has been in past model eras.

PNNL researchers will pursue both fundamental and applied projects with this support from the Department of Energy

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

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.

Cloud and its radiative effect are among the determining processes for the energy balance of the global climate; they are also the most challenging processes for the climate models to simulate.

The Grid Storage Launchpad dedication event was attended by leaders in grid and transportation energy storage, battery innovation, and industry stakeholders working to transform America’s energy system.

At the Joint Statistical Meeting, the largest gathering of statisticians and data scientists in North America, PNNL researchers presented their latest findings and led a workshop on text analysis and natural language processing.

ChemReasoner combines decades of chemistry knowledge with large language models to propose strategies for effective new catalysts.

PNNL staff in the Artificial Intelligence and Data Analytics division were recognized by the TSA’s Innovation Task Force (ITF) for their contributions to cloud capabilities, development strategies, and smart management of cloud resources.

Data from SOSAT web tool informs site selection and management for the subsurface injection of captured carbon dioxide.