Rapid Identification of Spent Lithium-ion Batteries Black Powder Types Using Handheld LIBS and Interpretable MobileNet Models

Key Points

• The primary aim is to leverage handheld LIBS and advanced machine learning for quick identification of battery materials.
• Utilized handheld laser-induced breakdown spectroscopy for material analysis.
• Employed a lightweight MobileNet deep learning model for classification.
• Focused on classifying spent lithium-ion battery black powders.
• Successfully identified different types of black powder rapidly.
• Demonstrated high accuracy in classification using the combined techniques.