PNNL’s ESMI is a Laboratory-funded research and development (R&D) program focused on transforming and accelerating materials development processes for next-generation energy storage technologies.
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.
Pacific Northwest National Laboratory’s (PNNL) Generative AI (GenAI) investment aims to harness this transformative technology to drive innovation across the science, energy, and security research domains.
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
The National Response Framework Policy Landscape Analysis Tool interactively captures and visualizes intricacies of the National Response Framework, a federal guide to national response to all types of disasters and emergencies.
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.
Pacific Northwest National Laboratory has pioneered the use of observational research for evaluating energy efficient technologies in the built environment.
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.
The Pacific Northwest National Laboratory is developing a Port Electrification Handbook—a reference to aid maritime ports nationwide in their clean energy transition.
Our nation’s critical infrastructure supports the security and wellbeing of our society. Maintaining the resilience of important markets and services is vital to upholding our way of life.
PNNL combines AI and cloud computing with damage assessment tools to predict the path of wildfires and quickly evaluate the impact of natural disasters, giving first responders an upper hand.
The RD2C laboratory-directed research initiative seeks to develop resilient, adaptive, and intelligent sensing and control algorithms through the observational understanding and characterization of CPSs under adverse conditions.
