Ampcera has an exclusive licensing agreement with PNNL to commercially develop and license a new battery material for applications such as vehicles and personal electronics.

PNNL chemical engineer Mariefel Olarte shares passion for mentoring students and the next-generation workforce.

PNNL Program Development Office Director Karl Mueller explains how the TEC4 project seeks to make advanced chemical computations accessible to all.

RemPlex and IAEA convene international leaders to tackle recruitment and retention in complex environmental cleanup efforts.

CACTUS provides AI-powered cheminformatics for autonomous science.

A recent paper published in Science sheds light on how aerosols—tiny particles in the air—released by industrial activities can trigger downstream snowfall events.

NASA has awarded $2.5 million to the BioS-ENDURES consortium, led by the University of Washington and including WSU and PNNL, to advance space life sciences research supporting human health in space and Earth-based applications.

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

The demand for energy is growing—and so is the technology supporting it. However, future development of power generation technologies could be affected by a key factor: material supply.

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.

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

PNNL's McDearis and Rod designed a new device—a porous soil stake—that, once installed, enables repeated sampling of a specific soil site at multiple depths, without further disrupting the soil.

A newly funded project will develop the fundamental understanding of phenomena that underpin material properties important for quantum applications.

Francesca Pierobon holds a joint appointment with UW and WSU to advance low-carbon technologies.

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.

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

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.