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.

PNNL has developed performance assessment guidance for remediation of volatile contaminants in the vadose zone, inorganic contaminant remediation in the vadose zone, and pump-and-treat of groundwater contaminant plumes.

PNNL's River Corridor Hydrobiogeochemistry Scientific Focus Area works to transform understanding of spatial and temporal dynamics in river corridor hydrobiogeochemical functions from molecular reaction to watershed and basin scales.

PNNL seeks students with diverse backgrounds who can apply their skills to international nuclear safeguards challenges.

The Salish Sea Model (SSM) is a predictive coastal ocean model for estuarine research, restoration planning, water-quality management, and climate change response assessment.

Powered by few-shot learning, the Sharkzor AI-driven, scalable web application makes it possible to quickly characterize and sort electron microscopy images used to analyze radioactive materials.

The Suite Of Comprehensive Rapid Analysis Tools for Environmental Sites online tools provide rapid data analytics and visualization of environmental data supporting remedy decisions, optimization, and exit strategies.

Advancing our understanding of how soil microbial communities respond to—and affect—changing environmental conditions

PNNL’s Space Science, Technology, and Policy activities draw on diverse technical expertise and research capabilities from across the Laboratory.

STOMP is a suite of numerical simulators for solving problems involving coupled flow and transport processes in the subsurface. The suite of STOMP simulators is distinguished by application areas and solved mathematical equations.

The SEAHORCE project aims to improve the ability of the Energy Exascale Earth System Model to model oceans at higher fidelity than currently possible.

The TRAC web tool displays the environmental remediation status—and metrics about progress toward closure—for cleanup sites overseen by the DOE Office of Environmental Management.

To support strategic trade control and global security, PNNL has developed advanced capabilities in trade data analytics to help better detect and counter illicit trade.

PNNL has developed a tool suite of interactive analytics that can be rapidly integrated into analyst workflows to empirically analyze and gain qualitative understanding of AI model performance jointly across dimensions.