PNNL’s pioneering CETC project with regional universities demonstrates transactive controls among multiple commercial buildings and devices for energy efficiency and grid reliability.
PNNL is helping communities with significant historical ties to fossil energy understand opportunities and pursue numerous federal resources available to support coal power plant redevelopment.
The Computational and Theoretical Chemistry Institute (CTCI) aspires to establish a premier international center for chemistry and materials science software at extreme scales.
E4D is a 3D geophysical modeling and inversion program designed for subsurface imaging and monitoring using static and time-lapse electrical resistivity tomography (ERT), spectral induced polarization (SIP) and travel-time tomography data.
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 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.
The Isotope Program at PNNL supports scientific advances in the production and use of radioisotopes for research, medicine, and industrial applications.
PNNL is heavily engaged in the development and use of mass spectrometry technology across its science, energy, and security missions, from fundamental research through mature operational capabilities.
PNNL is a testbed for the latest research and technologies in marine carbon dioxide removal (mCDR)—leveraging the ocean’s strength as a natural carbon sink to address pressing climate concerns.
Advancing the understanding and monitoring of nuclear material processing to accelerate development and qualification of new material systems for national security and nuclear energy.
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.
PREPARES demonstrates linkages between climate or weather conditions and human domain systems by combining quantitative geophysical data with qualitative data.
PNNL is working on behalf of the U.S. Department of Energy to create a prototype system that enables homes to help provide services to the power grid while delivering economic benefits to residents.
