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.
Researchers devised a quantitative and predictive understanding of the cloud chemistry of biomass-burning organic gases helping increase the understanding of wildfires.
A new report highlights the results of an assessment PNNL conducted of field-portable detection products used by first responders to detect illicit substances like fentanyl in the field.
PNNL’s Center for the Remediation of Complex Sites convened attendees from around the world to discuss challenges associated with environmental contamination.
Spatial proteomics enables researchers to link protein measurements to features in the image of a tissue sample, which are lost using standard approaches.
A team of scientists at PNNL developed new computational models to predict the behavior of these impurities and reduce the expense and risk related to actinide metal production.
Scientists screen for nanobodies that recognize wild type and mutant functional proteins to develop a framework to disrupt protein interactions that can cause disease.
High fidelity simulations enabled by high-performance computing will allow for unprecedented predictive power of molecular level processes that are not amenable to experimental measurement.
Through collaboration with the Department of Homeland Security Soft Target Engineering to Neutralize the Threat Reality Center of Excellence, PNNL is advancing research and development of tools and methodologies to protect crowded places.
COVID-19 infections at PNNL early in the pandemic were caused by a wide variety of viral sequences, according to a new analysis by Laboratory researchers.