journal article·2026-02-13Open access

Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling as Catalysts for Next-Generation Breakthroughs

Yucheng Fu, Jinxia Fu, Ruozhu Feng, Jie Bao, Shijing Sun, David G. Kwabi, Jingbo Louise Liu

ACS Energy Letters· Volume 11· Issue 2

Abstract

Meeting, hosted by the President's Office and Energy and Fuels Division, American Chemical Society (ACS) in Washington, DC, brought together a diverse group of chemists, engineers, and materials scientists from academia, industry, and national laboratories working in battery materials and systems, automation, and artificial intelligence.The accelerating demand for high-performance, scalable, and sustainable energy storage has catalyzed a paradigm shift in how materials are discovered, devices are engineered, and systems are optimized.This Presidential Symposium, entitled "Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling Driving Next-Gen Breakthroughs", brought together global leaders to discuss transformative strategies anchored in the AAA framework: Artificial Intelligence, Automation, and Advanced Modeling.Artificial Intelligence is redefining the frontiers of energy storage by enabling predictive design, real-time optimization, and intelligent control across diverse chemistries and device architectures.Automation is streamlining the synthesis, characterization, and testing of battery materials, dramatically accelerating innovation cycles and unlocking scalable solutions for grid and mobility applications.Advanced Modeling, spanning atomic to system-level scales, provides unprecedented insight into electrochemical processes, degradation pathways, and thermal behavior, particularly when coupled with physics-informed machine learning and digital twin technologies.Digital twins, in turn, leverage the AAA framework by integrating real-time data, physics-based models, and AI predictions into dynamic virtual replicas, enabling proactive diagnostics, optimization, and system resilience.Together, these pillars are not only reshaping the fundamental science of energy storage but also forging a new era of reproducible, rapid, and resilient energy storage innovation.This symposium highlights the growing convergence of computational intelligence and experimental rigor, charting the course for next-generation breakthroughs in lithium-ion, solid-state, and flow battery technologies.The leadership of the ACS, including Drs.Dorothy Phillips, Rigoberto Hernańdez, and staff members from the President's office, provided comprehensive guidance to ensure the smooth operation of this PRES event (Figure 1).Guided by the strategic vision of ACS Presidents, this symposium achieved seamless execution and fostered a dynamic, collaborative environment.Their leadership was pivotal in convening global experts to address urgent challenges in energy storage.The AI, Automation, and Advanced Modeling (AAA) framework served as the symposium's cornerstone.Together, these pillars
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Research context

OpenAlex topics: Hybrid Renewable Energy Systems · Integrated Energy Systems Optimization · Microgrid Control and Optimization

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Affiliations

Pacific Northwest National Laboratory, 902 Battelle Boulevard, Richland, Washington 99354, United States

Fuel & Chemical Airworthiness Certification Center, The Second Research Institute of Civil Aviation Administration of China, No. 17, South Section 2, Second Ring Road, Wuhou District, Chengdu, Sichuan Province 610042, China

Department of Mechanical Engineering

University of Washington

Department of Chemical and Environmental Engineering

Yale University

Department of Chemistry, Texas A&M University−Kingsville, 700 University Blvd, Kingsville, Texas 78363, United States

Texas A&M Energy Institute, Frederick E. Giesecke Engineering Research Building, 1617 Research Pkwy, College Station, Texas 77845, United States

References (2)

Show source-provided references
1. 10.1039/D5DD00017C10.1039/D5DD00017C ↗
2. 10.1002/batt.20240038510.1002/batt.202400385 ↗