Smith, P. orcid.org/0000-0003-3001-0245, McLauchlin, A., Franklin, T. orcid.org/0000-0002-5152-6235 et al. (8 more authors) (2024) A data-driven analysis of HDPE post-consumer recyclate for sustainable bottle packaging. Resources, Conservation and Recycling, 205. 107538. ISSN 0921-3449
Abstract
The packaging industry faces mounting demand to integrate post-consumer recyclate (PCR). However, the complex structure-property relationships of PCRs often obscure their performance compared to virgin equivalents, posing challenges in selecting suitable PCRs for applications. Focused on extrusion blow moulding grade high-density polyethylene (HDPE), this study presents the most extensive characterisation of HDPE PCR to date, encompassing 23 resins (3 virgin, 20 PCR). Employing Fourier-transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), rheology, colour analysis, and mechanical testing, we established a feature-rich dataset with 56 distinctive characteristics. Utilising a data science approach based on principal component analysis, with the virgin samples as a benchmark, we identified that combining FTIR, TGA and mechanical testing provided effective identification of PCRs that closely match the properties of virgin HDPE. The pipeline created can be utilised for new PCRs to determine suitability as a replacement for virgin plastic in a desired application.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | Post-consumer recyclate (PCR); Plastics recycling; High-density polyethylene; Datadriven analysis; Polymer characterization; Circular economy |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Chemical and Biological Engineering (Sheffield) |
Funding Information: | Funder Grant number Engineering and Physical Sciences Research Council EP/S019367/1 Engineering and Physical Sciences Research Council EP/R00661X/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 08 Aug 2024 15:50 |
Last Modified: | 09 Aug 2024 00:38 |
Status: | Published |
Publisher: | Elsevier BV |
Refereed: | Yes |
Identification Number: | 10.1016/j.resconrec.2024.107538 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:215404 |