Three research teams led by PNNL organizers achieve journal publications following the Mathematics Research Communities program.

Expanding the nation’s largest wind power plant time series database; helping grid planners navigate a resilient energy future with better data.

This study used historical data, remote sensing, and aquatic sensors to measure how far wildfire impacts propagated through the watershed after the 2022 Hermit’s Peak/Calf Canyon fire, New Mexico’s largest wildfire in history.

The Coastal Observations, Mechanisms, and Predictions Across Systems and Scales: Field, Measurements, and Experiments project established a network of observational field sites across Chesapeake Bay and western Lake Erie.

Two new publications provide emergency response agencies with critical insights into commercially available unmanned ground vehicles used for hazardous materials response.

PNNL researchers have published their paper, “Introducing Molecular Hypernetworks for Discovery in Multidimensional Metabolomics Data,” in the Journal of Proteome Research.

A team from PNNL contributed several articles to the Domestic Preparedness Journal showcasing recent efforts to explore the emergency management and artificial intelligence research and development landscape.

A team of researchers recently coordinated a series of international workshops aimed at enhancing chemical research security and fostering collaboration among scientists and academic researchers from both countries.

Over the past three years, PNNL’s Know Your Collaborator (KYC) workshop series has engaged hundreds of academic partners and institutional researchers internationally on the topic of research security.

Erich Hsieh, Deputy Assistant Secretary for OE’s Energy Storage Division, shared insights about the Grid Storage Launchpad and energy storage innovations .

PNNL advisors joined a panel of Washington State emergency management personnel to discuss how partnerships with national laboratories are enabling science and technology solutions.

Researchers created a methodology to design custom network topologies that improve the execution time for scientific applications.

PNNL researchers helped design and conduct an international exercise hosted by the Ministry of Finance of Finland to help improve financial sector resilience.

Researchers unveil user-friendly software to keep complex projects on budget and on schedule.

The diversity and function of organic matter in rivers at a large scale are influenced by factors, such as the types of vegetation covering the land, the energy characteristics, and the breakdown potential of the molecules.

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

The Forefront23 workshop convened researchers, scientists, and engineers who are just that: at the forefront of cybersecurity and nuclear nonproliferation.

PNNL researchers outline open problems in different scientific areas in the Journal of Combinatorics.

Methods review suggests ways to use artificial intelligence and machine learning to handle missing data when integrating two or more omics approaches.

PNNL is the newest member of the CONsortium on Nuclear sECurity Technologies (CONNECT).