Application of hyperspectral imaging and chemometrics for classifying plastics with brominated flame retardants
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Application of hyperspectral imaging and chemometrics for classifying plastics with brominated flame retardants. / Caballero, Daniel; Bevilacqua, Marta; Amigo, José Manuel.
In: Journal of Spectral Imaging, Vol. 8, a1, 2019.Research output: Contribution to journal › Review › Research › peer-review
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TY - JOUR
T1 - Application of hyperspectral imaging and chemometrics for classifying plastics with brominated flame retardants
AU - Caballero, Daniel
AU - Bevilacqua, Marta
AU - Amigo, José Manuel
PY - 2019
Y1 - 2019
N2 - Most plastics need to incorporate flame retardants to meet fire safety standards requirements. The amount and the type of flame retardants can differ, so that in waste plastics a large variety of polymers and flame retardants can be found. The recycling of plastics containing flame retardants is increasing. However, only plastics of the same polymer type and the same additive content can be recycled together. Three models based on different chemometrics techniques applied to hyperspectral imaging in the near infrared range were developed [partial least square-discriminant analysis, decision tree (DT) and hierarchical model (HM)]. Optimal results were obtained for all classification techniques. HM shows the highest error at all levels due to the noisy spectra of the black plastics. However, DT classification gave outstanding results, considering that the sensitivity was higher than 0.9 in all cases. Thus, the application of DT with hyperspectral imaging could be used to sort plastic samples with respect to the type of polymer and the flame retardant used with a high degree of accuracy in an automated way. These findings are highly valuable for the plastic and waste management industries.
AB - Most plastics need to incorporate flame retardants to meet fire safety standards requirements. The amount and the type of flame retardants can differ, so that in waste plastics a large variety of polymers and flame retardants can be found. The recycling of plastics containing flame retardants is increasing. However, only plastics of the same polymer type and the same additive content can be recycled together. Three models based on different chemometrics techniques applied to hyperspectral imaging in the near infrared range were developed [partial least square-discriminant analysis, decision tree (DT) and hierarchical model (HM)]. Optimal results were obtained for all classification techniques. HM shows the highest error at all levels due to the noisy spectra of the black plastics. However, DT classification gave outstanding results, considering that the sensitivity was higher than 0.9 in all cases. Thus, the application of DT with hyperspectral imaging could be used to sort plastic samples with respect to the type of polymer and the flame retardant used with a high degree of accuracy in an automated way. These findings are highly valuable for the plastic and waste management industries.
KW - Decision tree
KW - Flame retardants
KW - Hierarchical classification
KW - NIR hyperspectral imaging
KW - Partial least square-discrimination analysis
KW - Plastics recycling
KW - Polymer
KW - Waste recycling
U2 - 10.1255/jsi.2019.a1
DO - 10.1255/jsi.2019.a1
M3 - Review
AN - SCOPUS:85070597134
VL - 8
JO - Journal of Spectral Imaging
JF - Journal of Spectral Imaging
SN - 2040-4565
M1 - a1
ER -
ID: 228375124