PNNL researchers Marisa Decillis and Luke Richards contributed to a Center for Security and Emerging Technology report, “Securing Critical Infrastructure in the Age of AI.”

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

Research that modeled increased heat pump adoption alongside climate change impacts in Texas showed that high-efficiency heat pumps buffer the strain that electric heating might put on the power grid.

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

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

Secretary Granholm praises heat pump workforce development efforts at this year's instructor training program.

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.

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

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

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.

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.

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

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.