Prediction of polyethylene density from FTIR and Raman spectroscopy using multivariate data analysis. (December 2021)
- Record Type:
- Journal Article
- Title:
- Prediction of polyethylene density from FTIR and Raman spectroscopy using multivariate data analysis. (December 2021)
- Main Title:
- Prediction of polyethylene density from FTIR and Raman spectroscopy using multivariate data analysis
- Authors:
- Bredács, M.
Barretta, C.
Castillon, L.F.
Frank, A.
Oreski, G.
Pinter, G.
Gergely, S. - Abstract:
- Abstract: To contribute to the targeted 10 million tons per year of recycled plastic in Europe by 2025 and to improve the mechanical sorting degree of polyethylene (PE) products, density prediction models were developed from Fourier transform infrared-attenuated total reflectance (FTIR-ATR) and Raman spectroscopic data. State-of-the-art sorting in mechanical recycling provides separated polymer classes, however an improved classification with specific chemical and physical features such as density or melt flow rate has not been developed yet. Applying multivariate data analysis (MVDA) on the spectral datasets of 10 different PE materials, one FTIR-ATR and two Raman spectra based partial least square (PLS) density models were developed. However, whereas all three models are applicable to predict PE density accurately, the Raman models have shown some advantages. Firstly, less principle components (PC) are needed and secondly the density can be assessed with higher accuracy, due to the more robust cross-validated PLS model. Moreover, the obtained PC-s indicate that in the FTIR-ATR model the CH3 /CH2 ratio, while in the Raman model the CH2, CH and the crystalline C–C bands can be correlated with the PE density. The most accurate PLS model was obtained from the 1500-1000 cm −1 Raman shift region. The developed models could improve the density based mechanical separation of PE and consequently increase the quality of recycled and reprocessed PE products. Graphical abstract: ImageAbstract: To contribute to the targeted 10 million tons per year of recycled plastic in Europe by 2025 and to improve the mechanical sorting degree of polyethylene (PE) products, density prediction models were developed from Fourier transform infrared-attenuated total reflectance (FTIR-ATR) and Raman spectroscopic data. State-of-the-art sorting in mechanical recycling provides separated polymer classes, however an improved classification with specific chemical and physical features such as density or melt flow rate has not been developed yet. Applying multivariate data analysis (MVDA) on the spectral datasets of 10 different PE materials, one FTIR-ATR and two Raman spectra based partial least square (PLS) density models were developed. However, whereas all three models are applicable to predict PE density accurately, the Raman models have shown some advantages. Firstly, less principle components (PC) are needed and secondly the density can be assessed with higher accuracy, due to the more robust cross-validated PLS model. Moreover, the obtained PC-s indicate that in the FTIR-ATR model the CH3 /CH2 ratio, while in the Raman model the CH2, CH and the crystalline C–C bands can be correlated with the PE density. The most accurate PLS model was obtained from the 1500-1000 cm −1 Raman shift region. The developed models could improve the density based mechanical separation of PE and consequently increase the quality of recycled and reprocessed PE products. Graphical abstract: Image 1 Highlights: FTIR-ATR model correlates the CH3 /CH2 ratio with PE density Raman model applies the CH2, CH and crystalline C–C bands to determine density Deviation of predicted PE density less than 0.3% from Raman and FTIR-ATR spectra The 1500-1000 cm −1 Raman shift based PLS model has the highest accuracy PLS modeling of PE density may help to improve the degree of mechanical recycling … (more)
- Is Part Of:
- Polymer testing. Volume 104(2021)
- Journal:
- Polymer testing
- Issue:
- Volume 104(2021)
- Issue Display:
- Volume 104, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 104
- Issue:
- 2021
- Issue Sort Value:
- 2021-0104-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-12
- Subjects:
- Polyethylene -- Density prediction -- Recycling -- FTIR-ATR and Raman spectroscopy -- Multivariate data analysis -- PCA and PLS models
Polymers -- Testing -- Periodicals
Polymères -- Tests -- Périodiques
620.1920287 - Journal URLs:
- http://www.sciencedirect.com/science/journal/01429418 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.polymertesting.2021.107406 ↗
- Languages:
- English
- ISSNs:
- 0142-9418
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6547.740500
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 20040.xml