The Biodefense Policy Landscape Analysis Tool (B-PLAT), captures and presents a slew of information about U.S. efforts to protect its citizens and others around the world from diverse threats.
Cyber, physical, and blended cyber-physical threats are real, ubiquitous, and expensive to deal with. Private companies, government institutions, and critical infrastructures struggle to implement viable solutions as technology evolves.
PNNL is a leader in the integration of aberration-corrected electron microscopy, in-situ techniques, and atom probe tomography to address challenges in nuclear materials, environmental remediation, energy storage, and national security.
PNNL is heavily engaged in the development and use of mass spectrometry technology across its science, energy, and security missions, from fundamental research through mature operational capabilities.
The Pacific Northwest Advanced Compound Identification Center (PNACIC) brings together innovations in integrated chemistry and advanced instrumentation to create a platform for comprehensive, unambiguous identification of metabolites.
Physics Informed Machine Learning (PIML) is a modeling approach that harnesses the power of machine learning and big data to improve the understanding of coupled, dynamic systems.
PNNL data scientists and engineers will be presenting at NeurIPS, the Thirty Fourth Conference on Neural Information Processing Systems, and the co-located Women in Machine Learning workshop, WiML.
PNNL's Subsurface Biogeochemical Research Scientific Focus Area works to transform understanding of spatial and temporal dynamics in river corridor hydrobiogeochemical functions from molecular reaction to watershed and basin scales.
A software suite for working with neutron activation rates measured in a nuclear fission reactor, an accelerator-based neutron source, or any neutron field to determine the neutron flux spectrum using a generalized least-squares approach.
PNNL creates immersive software experiences to meet a variety of challenges. One such challenge in science, technology, engineering, and mathematics (STEM) education is providing quality computer science education for all students.
