Work

Classification of black plastic types by hyperspectral imaging based on long-wave infrared emission spectroscopy

Year: 2024

Type: article

Abstract: Identification of black plastics poses a significant challenge in recycling due to the absorptive nature of carbon black additives. This work introduces a method where hyperspectral imaging in the long-wave infrared regime is used to distinguish between twelve samples of commercially available black plastics encompassing nine distinct polymer types. The spectral scanner comprises a scanning Fabry-Pérot interferometer and a thermal camera based on an uncooled microbolometer detector sensitive to wavelengths from 8 μm to 15 μm. A principal component model is combined with k-nearest neighbors to differentiate between plastic samples in hyperspectral images. The model successfully classifies five (PET, POM, PMMA, PA6, and PA66) out of nine black polymers, and the overall accuracy of the model is A=73.1 %.

Source: Polymer Testing

DOI: 10.1016/j.polymertesting.2024.108629

Authors: Mads Nibe Larsen, Anders Løchte Jørgensen, Victor Petrunin, Jakob Kjelstrup-Hansen, Bjarke Jørgensen, Mogens Hinge

Institutions: University of Southern Denmark, Aarhus University

Language: English

Topic: Spectroscopy and Chemometric Analyses

Subfield: Analytical Chemistry

Field: Chemistry

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,580

Funders: Aarhus Universitet, Innovationsfonden