Improving predictability of water quality and nutrient cycling in large river systems.

Developing conceptual models for microbial-environmental–ecosystem interactions is key to enhancing the ability of models to predict future ecosystem function.

Research from the PNNL-led WHONDRS consortium reveals chemistry and spatial gradients of metabolomes from river water and sediments around the globe.

From water purification, to better batteries and tools to foil a cyberattack—a look back at how PNNL helped to invent a brighter and better future over the last year.

A team led by researchers at PNNL demonstrated a new way to monitor deep subsurface fractures.

Human-machine teaming may sound like something from the distant future. In “Human-Machine Teaming: A Vision of Future Law Enforcement” in Domestic Preparedness, Corey Fallon, Kris Cook, and Grant Tietje of PNNL examine this topic.

PNNL engages in expert panels to address emerging policy issues surrounding deep space exploration; forms new partnership with University of Washington Space Policy and Research Center.

The newly created ICON Science Cooperative is a resource enabling an innovative approach to science to generate transferable knowledge and increase equity.

PNNL is rock solid on carbon storage, building on successful demonstration in eastern Washington.

Detailed characterization of molecules in, under, and along the Columbia River reveal potential mechanisms for biogeochemical cycling.

PNNL helped bring together officials from United States and Philippines for a multi-day virtual seminar on strategic trade controls.

Tomorrow’s scientific leaders gain real-world experience contributing to PNNL’s research and development.

PNNL’s Mike Hochella receives Geochemical Society’s Patterson Award and ACS Geochemistry medal for discovery of toxic particles produced during coal combustion.

PNNL researcher Erol Cromwell uses neural networks to elucidate subsurface permeability.

PNNL computational scientist Diana Bacon’s role as carbon storage associate editor uses her expertise in subsurface modeling and quantitative risk assessment.

When training for chemical and biological threats, in-person exercises and drills can be very limited due to the hazardous nature of the agent.

PNNL combines AI and cloud computing with damage assessment tool to predict path of wildfires and quickly evaluate the impact of natural disasters, giving first responders an upper hand.

PNNL provided ultra-low measurements of argon-39 to date groundwater as part of a collaborative study of the aquifer in California’s San Joaquin Valley. PNNL is one of only a few laboratories worldwide with this capability.

A series of internships and course work help prepare PNNL intern Eva Jacroux for prestigious scholarship.

Researchers used deep learning methods to estimate the subsurface permeability of a watershed from stream discharge measurements.