The Rapid Assessment of Platform Technologies to Expedite Response project aims to prepare against future pandemics.

A holistic evaluation of the uncertainty sources that arise from configuring the model to processing the output for global variable-resolution models.

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.

Researchers found a 150-day period in Antarctic circulation, something that many current climate models do not represent accurately.

The award was given at the 29th International Conference on Information, Communication and Automation Technologies.

A crystalline silicate framework forms through a non-classical, multi-step nucleation mechanism based on structurally precise clusters.

A new review describes the insights that may be gained into important electrochemical processes using ion soft landing.

Chun-Long Chen honored for his outstanding contributions in the field of bio-inspired nanomaterials.

Faced with limited data, researchers at PNNL studied different techniques to improve disease prediction in resource-limited settings.

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.

Four PNNL researchers received highly competitive DOE Early Career Research Program awards, providing five continuous years of funding for their projects.

Two teams were recognized for technologies to help the International Atomic Energy Agency verify peaceful use of nuclear material.

Zhijie (Jay) Xu will apply his expertise in multiscale modeling to this editorial role.

Scientists have developed a better way to recognize denial-of-service internet attacks, improving detection by 90 percent.

A new open-source feature tracking package is now available to facilitate advanced model evaluation, model development efforts, and scientific discovery.

PNNL researchers present challenges and opportunities for fusing graph neural networks with deep reinforcement learning.

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.

PNNL recently joined the Department of Homeland Security for two technical meetings exploring national security research spanning the threat realm, from chemical and biological attacks to adversarial artificial intelligence.