Laser-induced breakdown spectroscopy applied to the rapid identification of different types of polyethylene used for toy manufacturing

Author(s)

Costa, Vinicius Camara ; Pereira, Fabiola Manhas Verbi

• Document type: Journal article
• Source: JOURNAL OF CHEMOMETRICS; v. 34, n. 12, p. 8-pg., 2020-04-27.

Abstract

The identification of plastics is of great importance to recycling companies, as the littering of plastic wastes has rapidly increased because of the extensive use of plastics. To maintain the economics of recycling extremely large volumes of waste materials, rapid and accurate identification of these plastics is crucial. In this study, we demonstrate the efficacy of laser-induced breakdown spectroscopy (LIBS) in the rapid identification of high-density polyethylene (HDPE) and low-density polyethylene (LDPE) used for toy manufacturing. For data analysis of the LIBS spectra, multivariate data analysis using principal component analysis (PCA) was utilized. The analyses of the data clearly showed that the elemental and molecular information obtained from LIBS is effective in the identification of three types of polyethylene. The proposed method was successfully applied and can be used as an alternative to the traditional methods used for analyses of plastics. (AU)

• FAPESP's process: 16/01513-0 - Laser-Induced Breakdown Spectroscopy (LIBS) application in the analyses of electronic waste (printed circuit boards and polymers), food and difficult preparation liquid samples
• Grantee: Edenir Rodrigues Pereira Filho
• Support Opportunities: Regular Research Grants
• FAPESP's process: 19/01102-8 - Multi-user equipament approved in grant 2018/18212-8: X-Ray Fluorescence spectrometer
• Grantee: Fabiola Manhas Verbi Pereira
• Support Opportunities: Multi-user Equipment Program
• FAPESP's process: 18/18212-8 - Development of chemometric models for determination of solid impurities in raw sugarcane using energy dispersive X-ray fluorescence
• Grantee: Fabiola Manhas Verbi Pereira
• Support Opportunities: Regular Research Grants