Bradley Crowell with the U.S. Nuclear Regulatory Commission sees advanced materials integrity, radiological measurement, and environmental capabilities on his first visit to PNNL.
Randomly constructed neural networks can learn how to represent light interacting with atmospheric aerosols accurately at a low computational cost and improve climate modeling capabilities.
A success story of applying convergence testing to detect and address issues of numerical discretization in nonlinear representations of turbulence and clouds.
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.
The PNNL-managed Building America Solution Center translates research into actionable considerations for homeowners and builders to provide two solutions in one: increasing energy efficiency while also enhancing disaster resistance.
A new open-source feature tracking package is now available to facilitate advanced model evaluation, model development efforts, and scientific discovery.
PNNL researchers demonstrated a simple method to create stable, identical nanoparticles of PdTe2-like composition, which is known to be superconducting, on a WTe2 TMD support.
IDREAM research shows that keeping only the most important two- and three-body terms in reactive force fields can decrease computational cost by one order of magnitude, while preserving satisfactory accuracy.
This study demonstrated that a large-scale flooding experiment in coastal Maryland, USA, aiming to understand how freshwater and saltwater floods may alter soil biogeochemical cycles and vegetation in a deciduous coastal forest.