A breakthrough in electron microscopy based on deep learning can automatically visualize and identify areas of interest, helping to speed advances in materials science.
PNNL computing experts Robert Rallo and Court Corley contribute their knowledge to a recent DOE report on applications of AI to energy, materials, and the power grid.
Three PNNL-affiliated researchers have been named fellows of the American Association for the Advancement of Science, the world’s largest multidisciplinary scientific society.
Sequencing of microbiome and characterization of metabolome revealed significantly different functions of fine root systems from four temperate tree species in a 26-year-old common garden forest.
PNNL recently partnered with Amazon Web Services for AWS GameDay, a gamified learning event that challenges participants to use AWS solutions to solve real-world technical problems in a team-based setting.
Catalysts that efficiently transfer hydrogen for storage in organic hydrogen carriers are key for more sustainable generation and use of hydrogen. New research identifies activity descriptors that can accelerate novel catalyst development.
Researchers used a combination of sophisticated laboratory incubations and field measurements to determine the role of microbial production and consumption of methane in soils with different exposure to tidal inundation
Steven Spurgeon, materials scientist supporting the National Security Directorate at PNNL, was recently named lead machine learning editor for the journal Microscopy and Microanalysis.
Scott Baker, the Functional and Systems Biology Group leader at PNNL, has been named to the American Institute for Medical and Biological Engineering's Class of 2024 Fellows.
A new AI model developed at PNNL can identify patterns in electron microscope images of materials without requiring human intervention, allowing for more accurate and consistent materials science.
PNNL is supporting the Department of Homeland Security Science and Technology Directorate's Chemical Security Analysis Center in improving capabilities to enhance detection and analysis of chemical threats.