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.

The search for dark matter includes expertise in radio frequency signal detection, quantum sensing, and high-energy physics at PNNL.

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

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

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.

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

Samrat (Sam) Chatterjee, a PNNL chief data scientist and team leader with the Data Sciences and Machine Intelligence group, was co-author of a CSET workshop report on agentic artificial intellilligence

Joint Appointee Mitra Taheri spoke on the AI in Government episode of the EY Leading into Tomorrow podcast.

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

PNNL computational and data scientist Mark Maupin was the team lead for a paper published in the journal Molecules.

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.

Mengqi Zhao and Chris Vernon were selected to serve in editorial roles at JOSS for Earth science and data science, respectively.

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.

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

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

Ján Drgoňa invited as a speaker at the Grainger Foundation Frontiers of Engineering 2024 Symposium of the National Academy of Engineering.

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