Multimodal Operando Characterization Platform for Monitoring Lithium-ion Battery Pouch-Cell

Despite considerable efforts devoted to the design and modification of advanced battery materials, lithium-ion batteries, especially those with high energy density, still face critical challenges such as safety risks and complex failure mechanisms. To tackle these issues, we developed a multimodal operando characterization platform for operating lithium-ion pouch cells. This platform combines several advanced operando diagnostic techniques, including infrared imaging, X-ray technologies, ultrasonic scanning, mass spectrometry, and gas chromatography-mass spectrometry. It allows nondestructively comprehensive and dynamic tracking of key operational parameters, such as temperature distribution, mechanical evolution, and gas evolution behavior. Moreover, we innovatively propose a concept of AI-driven closed-loop framework for battery operation, structured as "operando monitoring-data analysis-intelligent control", to efficiently process large amounts of data and deliver intelligent feedback. This work successfully achieves the real-time and nondestructive detection of various evolution behaviors during the operation of pouch lithium-ion batteries.