The popular approach of organizing soil bacteria into fast- or slow-growing groups is problematic because most bacteria grow at comparable rates in soil.
To overcome high-performance computing bottlenecks, a research team at PNNL proposed using graph theory, a mathematical field that explores relationships and connections between a number, or cluster, of points in a space.
Three PNNL authored papers were accepted as posters to the ICLR 2023 Workshop on Physics for Machine Learning and Workshop on Mathematical and Empirical Understanding of Foundation Models.
Variations in burn severity are a key control on the chemical constituents of dissolved organic matter delivered to streams within a single burn perimeter.
Department of Energy, Office of Science Director Asmeret Asefaw Berhe visited PNNL to learn about the Lab’s drive to conduct discovery science, commitment to science for an equitable future, and development of a diversified STEM workforce.
A multi-omics analysis provides the framework for gaining insights into the structure and function of microbial communities across multiple habitats on a planetary scale
A rich and largely untapped reservoir of lipids in soil environments was used to examine microorganisms’ physiological responses to drying-rewetting cycles.
