Researchers found that specific landscape metrics consistently outperform traditional population downscaling methods.

Researchers developed a machine learning model that can analyze chemical reactions as they happen in an electron microscope.

Interactions between fronts and the land-sea breeze lead to strong vertical exchange in the northern Gulf of Mexico.

As leaders in AI and machine learning, PNNL experts are sharing their latest findings at the 36th annual Neural Information Processing Systems (NeurIPS) Conference, Nov. 28–Dec. 9, 2022.

Data-driven experiments can help determine best practices for Random Forest machine learning to predict water quality, particularly nitrate levels.

PNNL researchers teamed up with SambaNova to enhance artificial intelligence for scientific computing.

PNNL researchers design an artificial intelligence-guided electron microscope in a Laboratory Directed Research and Development study.

A climate change study co-authored by PNNL scientist Hailong Wang inspired an artist to create an exhibit based on the research.

New report takes a comprehensive look at offshore aquaculture as a market for marine energy.

Soil transplant experiment gives new insights into coastal forest resilience, rising seas, and increasing storms.

ICON science is a Department of Energy-developed framework to enhance scientific outcomes via more intentional design of research efforts across all domains of science.

Soil pores are reorganized when newly thawed permafrost soils experience freeze-thaw cycling.

A multi-institutional team has developed a deep learning framework to identify novel molecules as drug candidates.

Ocean biogeochemical modeling software now available as open source to help researchers predict impacts of pollution, sea level rise, and climate change.

Principles derived from coastal wetlands to describe wetland channel cross-sections were applicable to the Columbia River estuary, but not the tidal river.

Researchers developed a new tool that combines artificial intelligence and microscopy data to rapidly test new materials for fusion reactor use.

Contributions from researchers across Pacific Northwest National Laboratory (PNNL) were recently recognized in the preliminary findings of a Secretary of Energy Advisory Board (SEAB) report.

Pacific Northwest marsh carbon stocks are twice the global average. Long-term sea-level rise impacts will likely decrease ecosystem carbon stocks.

Scientists are exploring ways to derive more accurate predictions that can help with preparations for changing sea levels