ABSTRACT Global efforts to decarbonize have led to rapid electrification across industries, including land transport, energy and maritime, enabled by the increasing adoption of high-power battery systems. Thus, there is an urgent need for sustainable management of retired batteries. For repurposing retired EV batteries to second-life applications, rapid and accurate grading of lithium-ion battery (LiB) performance is critical for its functionality and reliability. On the other hand, the safety issue of retired battery is a big concern. However, there is currently no widely accepted standards for assessing the safety of second-life batteries. Structural defects in lithium-ion batteries—such as electrode delamination, lithium plating, and gas-induced swelling—are critical safety risks that often evade detection until catastrophic failure occurs. Traditional monitoring methods (e.g., voltage/temperature tracking) lack sensitivity to these hidden threats. This work introduces a non-contact laser ultrasound (NCLIUS) platform integrated with machine learning to quantify defect severity and establish a standardized safety-grading system for batteries. This framework bridges a critical gap in battery safety by: • Enabling in-line, non-destructive screening of structural health, • Providing actionable safety metrics for OEMs and recyclers, • Mitigating risks in high-stakes applications (e.g., EVs, aerospace). REFERENCES [1] Y. Wang, X. Lai, Q. Chen, X. Han, L. Lu, M. Ouyang, and Y. Zheng. Progress and challenges in ultrasonic technology for state estimation and defect detection of lithium-ion batteries. Energy Storage Materials, Vol. 69, 103430, 2024. [2] D. Tang, C. Xu, G. Xu, S Cui, and S. Zhang. Non-Contact Laser Ultrasound Detection of Internal Gas Defects in Lithium-Ion Batteries. Sensors, 25(7):2033, 2025