The Generator Scorecard, developed by PNNL in partnership with BPA, automates generator evaluations, reducing engineering workloads and improving grid reliability.
In a recent publication in Nature Communications, a team of researchers presents a mathematical theory to address the challenge of barren plateaus in quantum machine learning.
PNNL and collaborators developed new models—recently approved by the U.S. Western Electricity Coordinating Council (WECC)—to help utilities understand how new grid-forming inverter technology will enhance grid stability.
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.
PNNL led one of five Pathway Summer School programs nationwide, with a specific focus on engaging students from Native American or Indigenous backgrounds.
A combined experimental and theoretical study identified multiple interactions that affect the performance of redox-active metal oxides for potential electrochemical separation and quantum computing applications.
PNNL researchers developed a hybrid quantum-classical approach for coupled-cluster Green’s function theory that maintains accuracy while cutting computational costs.