PNNL's E-COMP initiative is helping unleash American energy innovation with advanced theories, models, and software tools to better operate power systems that rely heavily on high-speed power electronic control.
The Generator Scorecard, developed by PNNL in partnership with BPA, automates generator evaluations, reducing engineering workloads and improving grid reliability.
The National Transmission Planning Study presents several transmission expansion scenarios that would reliably support the growing demand for energy across the nation.
Recycling polyolefin materials is challenging. One waste management strategy is plastic upcycling. New work demonstrates a single-step upcycling route coupling cracking and alkylation, recycling carbon and keeping valuable resources active.
PNNL’s patented Shear Assisted Processing and Extrusion (ShAPE™) technique is an advanced manufacturing technology that enables better-performing materials and components while offering opportunities to reduce costs and energy consumption.
PNNL computing experts Robert Rallo and Court Corley contribute their knowledge to a recent DOE report on applications of AI to energy, materials, and the power grid.
ChatGrid™ is a practical application of the Department of Energy’s exascale computing efforts and offers a new experience in easy, intuitive, and interactive data interaction.
Spatial proteomics enables researchers to link protein measurements to features in the image of a tissue sample, which are lost using standard approaches.
PNNL receives a 2023 Federal Laboratory Consortium Far West Regional Award for a technological innovation that could help make the U.S. a producer of critical minerals used in electronics and energy production.
A PNNL innovation uses steam to recover heat from the high-temperature reactor effluent in the HTL process, substantially reducing the propensity for fouling and potentially reducing costs.
Zhenyu (Henry) Huang acts as guest editor in an upcoming special issue on “Climate Change Mitigation and Adaptation in Power and Energy Systems." The special edition is published by Elsevier.
New research findings published in Science Advances (November 2022), help explain the progression of Alzheimer-related dementia in each patient. The findings outline a biological classification system that predicts disease severity.