Innovative cement and concrete technologies at PNNL enhance durability and performance through self-healing formulations and cost-effective, high-performance materials derived from waste, enabling more resilient, reliable infrastructure.

The Center for Understanding Subsurface Signals and Permeability (CUSSP) Energy Earthshot Research Center (EERC) is working to develop the ability to predict and control fluid flow through fracture networks in enhanced geothermal systems.

PNNL’s pioneering CETC project with regional universities demonstrates transactive controls among multiple commercial buildings and devices for energy efficiency and grid reliability.

Pacific Northwest National Laboratory, supported by the Department of Energy’s Grid Deployment Office, is leading a technical assistance initiative to help utilities test and deploy alternate GPS timing solutions.

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.

PNNL administers two research buoys for the U.S. Department of Energy that allows collection of wind meteorological and oceanographic data off the nation's coasts.

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.

Research efforts at PNNL to co-locate marine energy with aquaculture developments for more sustainable operations.

PNNL is a leader in multiple areas of shore power and port electrification research related to maritime ports, inland ports, and airports.

The Nereus Project aims to collect and analyze comprehensive environmental monitoring data around operational marine energy sites and devices in the United States.

PNNL's Ocean Dynamics Modeling group studies coastal processes such as marine-hydrokinetic energy, coastal circulations, storm surge and extreme waves, tsunamis, sediment transport and nutrient-macroalgal dynamics.

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.

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.