PNNL and The University of Texas at El Paso expand their premier partnership to include the Cyber Halo Innovation Research Program.

Under Secretary for Science and Innovation at the Department of Energy Geri Richmond visited PNNL.

Advances in understanding the nature of the chemical bond are featured in this special issue of The Journal of Chemical Physics.

Deep learning helps make predictions on the effects of the El Niño-Southern Oscillation on river flows more accurate.

Machine learning models help identify important environmental properties that influence how often extreme rain events occur with critical intensity and duration.

PNNL researchers combined deep operator networks with spectral methods to efficiently and accurately solve complex equations.

Data-driven autonomous technology to rapidly design and deliver antiviral interventions targeting SARS-CoV-2 to reduce drug discovery timeline and advance bio preparedness capabilities.

The work by the team at PNNL takes a critical step in leveraging ML to accelerate advanced manufacturing R&D, specifically for manufacturing techniques without access to efficient, first-principles simulations.

Microbes that were previously frozen in soils are becoming more active. This study demonstrates the diverse RNA viral communities found in thawed permafrost.

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

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.

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

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.

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

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.

A novel ecological measurement uncovered interactions between river corridor organic matter assemblages and microbial communities, highlighting potentially important microbial taxa and molecular formula types.

Measurements of forest after an anomalous seawater exposure event reveals carbon starvation as dominant process underlying deaths.