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.

RT3D is a software package for simulating three-dimensional, multi-species, reactive transport of chemical compounds (solutes) in groundwater.

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

This report reviews the current state of the North American lithium battery materials market and will be updated periodically as the industry evolves.

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.

Pacific Northwest National Laboratory supports innovations in data analytics, instrumentation, and experimental techniques for the Northwest (NW) Biopreparedness Research Virtual Environment (BRaVE) Initiative.

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.

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.

PNNL and the United States Geological Survey are partnering to develop a buoy-based radar system capable of measuring bird and bat abundances and behaviors at offshore locations.

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 data scientists and engineers will be presenting at NeurIPS, the Thirty Fourth Conference on Neural Information Processing Systems, and the co-located Women in Machine Learning workshop, WiML.

PNNL computer scientists are presenting the latest research in HPC at SC20.