A rich and largely untapped reservoir of lipids in soil environments was used to examine microorganisms’ physiological responses to drying-rewetting cycles.
In new work, PNNL researchers find that 10 gigatons of carbon dioxide may need to be pulled from Earth's atmosphere and oceans annually to limit global warming to 1.5 degrees. A diverse suite of carbon dioxide removal methods will be key.
Machine learning models help identify important environmental properties that influence how often extreme rain events occur with critical intensity and duration.
Gosline works to develop computational algorithms that are uniquely targeted for rare disease work by doing foundational research in model system development. This work can be expanded to all model systems in human disease.
Report for the Oregon Public Utility Commission highlights innovations and best practices for resilience and utility planning could be helpful to other states as well.
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.
Data scientist Jung Lee accepted the position of review editor for Frontiers in Computational Neuroscience after serving as a guest editor for a special issue.
A team from the Environmental Molecular Sciences Laboratory published research, demonstrating that the soil microbes were directly involved in the stabilization of soil organic carbon and mineral weathering.
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.