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

New PNNL-developed nanogenerator harnesses the renewable energy in ocean waves to power sensors that provide critical weather and wave information.

PNNL researchers launch a new DOE project focused on advancing GUV technology for improved public health outcomes and decarbonization benefits.

STEM Education programs at DOE and national labs offer environmental management internships; applications are due soon for summer 2023.

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.

For a second year in a row, doctoral intern Jack Watson was awarded the Student Merit Award by the Society for Risk Analysis and the Resilience Analysis Specialty group.

PNNL scientists Daniel Gaspar and Wei Wang were among nine scientists featured in journal article recognizing 2021-2022 ACS award honorees.

PNNL-Sequim team wins ESTCP Project of the Year for their work supporting underwater munition remediation.

PNNL and Georgia Tech launch a joint institute focused on accelerating security for the critical infrastructure community.

Interactions between fronts and the land-sea breeze lead to strong vertical exchange in the northern Gulf of Mexico.

Five staff members from PNNL received awards from the Department of Energy’s Federal Energy Management Program for contributions to projects for the U.S. Army.

Iron-based fertilizer may stimulate plankton to pull carbon dioxide from the ocean, driving a carbon-negative process.

As leaders in AI and machine learning, PNNL experts are sharing their latest findings at the 36th annual Neural Information Processing Systems (NeurIPS) Conference, Nov. 28–Dec. 9, 2022.

PNNL researchers created rugged, adaptable, mass-manufacturable luminescent particle tracers for use in harsh environments.

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

The world's current climate pledges won't limit global warming to 1.5 °C. We will overshoot. A new study shows that more ambitious climate pledges could minimize the overshoot.

PNNL gathered researchers from eight national laboratories plus the U.S. Department of Energy (DOE) to share ideas and build synergy at the Energy Equity and Environmental Justice Summit.

PNNL researchers use machine learning and data analytics to assist with detection of nuclear proliferation and nuclear material trafficking.

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

PNNL’s fall Pathways to Excellence award ceremony celebrated nearly 50 staff for their contributions across science, engineering, operations, and STEM education.