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.

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

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.

Recovery Simulator and Analysis tool further strengthens PNNL’s short-term resilience planning efforts for Puerto Rico.

ExaGO, a power grid simulation and optimization platform developed at PNNL is the first of its kind to run on Frontier.

The Northwest Connected Communities Summit brought together representatives of five Department of Energy-funded Connected Communities Projects to share ideas and discuss potential collaboration opportunities.

Department of Energy Office of Electricity Assistant Secretary Gene Rodrigues makes his first visit to PNNL.

Department of Energy, Office of Science Director Asmeret Asefaw Berhe visited PNNL to learn about the Lab’s drive to conduct discovery science, commitment to science for an equitable future, and development of a diversified STEM workforce.

A multi-omics analysis provides the framework for gaining insights into the structure and function of microbial communities across multiple habitats on a planetary scale

Report for the Oregon Public Utility Commission highlights innovations and best practices for resilience and utility planning could be helpful to other states as well.

Staff at PNNL recently completed a report highlighting commercial products enabled through projects funded by the Department of Energy’s Building Technologies Office.

The Simple Building Calculator, developed at PNNL, meets a need for a quick, interactive, and economic method to evaluate energy use—and potential savings from efficiency measures—in simple commercial buildings.

Data-driven experiments can help determine best practices for Random Forest machine learning to predict water quality, particularly nitrate levels.

PNNL joint appointee Auroop Ganguly uses data science to study the impacts of climate change.

Across the United States, water moving between the river and riverbed sediments does not overcome localized processes that govern organic matter chemistry.

Eight Office of Science Graduate Student Research join PNNL.

New research simulates power demand, supply, and cost in a hotter, drier climate.

ICON science is a Department of Energy-developed framework to enhance scientific outcomes via more intentional design of research efforts across all domains of science.

New work developed a methodology to generate building temperature setpoint schedules for use by modelers in large-scale building energy simulations.

A new microbial community model reveals previous exposure to hydrologic variation influences a species’ specialized biogeochemical functions.