PNNL Report Benchmarks Digital Twins for Chemistry-informed AI in Energy Storage
January 10, 2026
January 10, 2026
WASHINGTON, Jan. 10 (TNSLrpt) -- Pacific Northwest National Laboratory has issued report PNNL-33781 titled 'Chemistry-Informed Digital Twin Framework for Predicting Degradation in Energy Storage Systems,' authored by Jeffrey S. Gross, Xiaowei Wang, Megan N. Smith, Jonathan D. Baker and colleagues and prepared for the U.S. Department of Energy under Contract DE-AC05-76RL01830. The October 2024 report presents a digital twin architecture that combines physics-based electrochemical models . . .