The Biodefense Policy Landscape Analysis Tool (B-PLAT), captures and presents a slew of information about U.S. efforts to protect its citizens and others around the world from diverse threats.
PNNL’s pioneering CETC project with regional universities demonstrates transactive controls among multiple commercial buildings and devices for energy efficiency and grid reliability.
The Computational and Theoretical Chemistry Institute (CTCI) aspires to establish a premier international center for chemistry and materials science software at extreme scales.
PNNL is developing open-source, equitable, standardized methods to quantify the environmental impacts of building system technologies and reduce barriers for the industry to participate in data-driven sustainability practices.
A multi-institution research team led by PNNL is addressing curb usage management challenges in large urban areas by developing a city-scale dynamic curb use simulation tool and an open-source curb management platform.
PNNL is a leader in the integration of aberration-corrected electron microscopy, in-situ techniques, and atom probe tomography to address challenges in nuclear materials, environmental remediation, energy storage, and national security.
The Grid Storage Launchpad (GSL) is a national capability for energy storage research funded by the Department of Energy Office of Electricity and located on the Pacific Northwest National Laboratory (PNNL) campus in Richland, Washington
PNNL and collaborators have established a national heat pump and heat pump water heater partnership to help drive adoption of these energy-saving technologies in both residential and commercial buildings.
The Institute for Integrated Catalysis (IIC) at Pacific Northwest National Laboratory explores and develops the chemistry and technology of catalyzed processes that enable a carbon-neutral future.
PNNL is leading a consortium that provides funding opportunities to the automotive industry for accelerating new lightweight technologies in on-highway vehicles.
FEMP's operations and maintenance (O&M) resources offer federal agencies technology- and management-focused guidance to improve energy and water efficiency and ensure safer and more reliable operations.
Physics-informed machine learning (PIML) is a modeling approach that harnesses the power of machine learning and big data to improve the understanding of coupled, dynamic systems.