4.7 Article

Rapid and accurate quality assessment method of recycled food plastics VOCs by electronic nose based on Al-doped zinc oxide

期刊

JOURNAL OF CLEANER PRODUCTION
卷 418, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2023.138042

关键词

Plastics; Polymer odors assessment; Al-doped zinc oxide; Electronic nose; Machine learning protocols

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In order to address the increasing volume of plastic, plastic recycling technologies are being actively developed and implemented. These technologies require new analytical tools to control the quality of the recycled polymers for further integration into production processes. In this study, a rapid and selective quality assessment method for high-density polyethylene polymer materials is proposed, using an electronic nose with aluminum doped zinc oxide sensing material in combination with the RandomForestClassifier machine learning tool. The electronic nose demonstrated a good correlation between vector signal and emitted volatile compounds, with an accuracy of over 98.5% when discriminating between primary and secondary plastics. The addition of zeolites to recycled plastic was found to decrease the occurrence of off-odors.
Plastic recycling technologies are being actively developed and implemented to cope with increasing volume of plastic. Such technologies require new analytical tools able to control the quality of the recycled polymers to be further integrated in production processes. Here, we propose a rapid and selective quality assessment method for polymer materials made of high-density polyethylene using electronic nose with aluminum doped zinc oxide sensing material in combination with the RandomForestClassifier machine learning tool. We test total content of volatile organic compounds both odor-active responsible for the smell and odorless of primary and secondary plastics, and evaluate corresponding organic vapors emitted by the plastics by headspace gas chromatography and mass-spectrometry at optimized conditions like sample temperature, sensor signal recovery time. The electronic nose demonstrated the good correlation of vector signal with the emitted volatile compounds with an accuracy more than 98.5% when discriminating between primary and secondary plastics. Addition of zeolites to the recycled plastic is shown to decrease the appearance of off-odors.

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