The Joint Appointment program at PNNL is one of the most diverse among other U.S. national laboratories, involving nearly 60 universities and research institutions in the United States and abroad.

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

To thwart pathogens, researchers in the epidemiology field of infectious disease (ID) prediction are continuously trying to forecast when, where, and how an ID event will occur.

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.

Silicone wristbands could be more convenient option for collecting exposure data.

Organismal contribution and community interaction drive soil organic matter breakdown by microbes.

Identifying a novel gene function on soil viruses.

Study shows coastal plants are dying from hydraulic failure and carbon starvation.

Biochemical preservation and mineral association retain carbon in grassland soils, resulting in consistent molecular composition across ecosystems.

Across the United States, water moving between the river and riverbed sediments does not overcome localized processes that govern organic matter chemistry.

Microbes and viruses play key roles in carbon and nitrogen cycling in riverbed sediments.

Proteins from “auxiliary” genes in soil viruses play a role in the carbon cycle and climate, scientists have found.

A new study shows how organic molecules respond to global change varies according to functional traits and ecological processes.

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

A process developed at PNNL that converts biomass and waste into a chemical intermediate or into gasoline, diesel, and jet fuel is available for commercial licensing.

A novel combination of temperature and four-dimensional geophysical sensors revealed otherwise unseeable hydrologic dynamics below riverbed sediments.

Forms of nitrogen released by nitrogen-fixing bacteria differ across sampling scales and in structured environments.

Dominant and functionally important soil microbes show strong, predictable, and distinctly different associations with continental-scale gradients in climate, vegetation, and soil moisture.

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