S. N. Abdulmadjid - Department of Physics, Faculty of Mathematics and Natural Sciences Universitas Syiah Kuala, Banda Aceh, Indonesia
B. S. Hartadi - Department of Physics, Faculty of Mathematics and Natural Sciences Universitas Syiah Kuala, Banda Aceh, Indonesia
R. Mitaphonna - Graduate School of Mathematics and Applied Sciences, Universitas Syiah Kuala, Banda Aceh, Indonesia
M. Iqhrammullah - Graduate School of Mathematics and Applied Sciences, Universitas Syiah Kuala, Banda Aceh, Indonesia

Growing plastic waste emission as a planetary threat urges the development of a rapid and efficient recycling process, especially during the classification process. Herein, we aimed to solve the problem by employing laser-induced breakdown spectroscopy (LIBS) in combination with principal component analysis (PCA) as means for automated plastic waste classification. Samples used in the study were plastic wastes derived from beverage, food, and stationery products of different brands. The Nd:YAG laser was shot to the sample surface without a pre-treatment and under an open-air system (laser energy= ۵۴ mJ; time delay= ۱-۲ μs). The spectral profile of each plastic waste revealed the presence of metal components such as those indicated by Ca II ۳۹۶.۸۵ nm, Al I ۳۹۵.۹۲ nm, Mg I ۳۸۳.۸۳ nm, and Fe I ۴۰۴.۸۵ emission lines. Peak intensities of organic material-related emission lines (C I ۲۴۷.۸۶ nm, O II ۷۷۷.۳۲ nm, O I ۸۴۴.۴۸ nm, H I ۶۶۶.۲۲ nm, N II ۸۱۸.۸۳ nm, and N II ۸۲۱.۶۲ nm) were revealed fluctuating, suggesting that a mere LIBS spectral analysis could not discriminate the plastic waste. PCA analysis revealed that C۲ molecular band ۴۹۰—۵۲۰ nm had the most discriminative properties against polyethylene terephthalate (PET) and polypropylene (PP). The molecular band was generated differently between PET and PP because of their contrast thermal behavior. In conclusion, molecular LIBS-PCA could be used to distinguish PET and PP in a simple and rapid way.

Molecular Laser-induced Breakdown Spectroscopy, Plastic Waste, Polyethylene terephthalate, polypropylene, Principal component analysis