PNNL's accomplishments in FY 2024 help address the remaining challenges the wind industry faces.

EZBattery Model allows energy storage researchers to more quickly and easily identify the best performing battery designs without the need for extensive physical prototyping or computationally expensive simulations.

The Testing Risks of AI for National Security Taskforce will address critical safety and security concerns related to artificial intelligence.

PNNL will analyze current and projected transportation fuel dynamics, supply chain risks, and risk comparators with relevant sectors, such as transportation electrification.

PNNL's new energy storage facility now houses the Lab's vehicle battery research programs, which have more lab space and a slew of new capabilities.

Pacific Northwest National Laboratory researchers developed a new theoretical method for studying highly correlated systems.

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

PNNL researchers co-organized a workshop on fusion commercialization with partners from industry and academia

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.

PNNL introduces students to career opportunities in energy sciences through Pathway Summer School programs.

Pasco School District educators joined Pacific Northwest National Laboratory for an immersive learning experience through the RENEW STEM Institute.

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.

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.

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

PNNL will engage with transmission planners and other regional partners through technical assistance and listening sessions with the goal of exploring opportunities to integrate equity into transmission planning.

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.