Review of Bioplastics Characterisation by Terahertz Techniques in the View of Ensuring a Circular Economy

Author:

Abina Andreja1,Korošec Tjaša1,Puc Uroš12ORCID,Zidanšek Aleksander134ORCID

Affiliation:

1. Jožef Stefan International Postgraduate School, Jamova cesta 39, 1000 Ljubljana, Slovenia

2. Institute of Computational Physics, Zurich University of Applied Sciences (ZHAW), Technikumstrasse 71, 8400 Winterthur, Switzerland

3. Jozef Stefan Institute, Jamova cesta 39, 1000 Ljubljana, Slovenia

4. Faculty of Natural Sciences and Mathematics, University of Maribor, Koroška cesta 160, 2000 Maribor, Slovenia

Abstract

The increasing scarcity of natural resources, worsening global climate change, environmental degradation, and rising demand for food are forcing the biotechnology and plastics industries to seek and apply circular economy models that would lead to a sustainable transition in the production and use of bioplastics. Circular economy models can improve the economic productivity of bio-based plastics and have a positive impact on the environment by reducing conventional plastic waste and the consumption of petrochemical feedstocks for plastic production. In addition, some agricultural wastes that have the potential to be used as bioplastics can be reused. Terahertz (THz) systems are already used in the plastics and rubber industries for non-destructive testing, detection, imaging, and quality control. Several reports have highlighted the potential applications of THz spectroscopy and imaging in polymer analysis and plastics characterisation. This potential is even greater with chemometric methods and artificial intelligence algorithms. In this review, we focus on applications that support the transformation of the biotechnology sector to the circular economy, particularly via the transition from conventional plastics to bioplastics. In this review, we discuss the potential of THz systems for the characterisation and analysis of bioplastics and biopolymers. The results of previous studies on biopolymers in the THz frequency range are summarised. Furthermore, the potential of using artificial intelligence approaches such as machine learning as advanced analytical methods in THz spectroscopy and imaging, in addition to the conventionally used chemometric methods, is discussed. The results of this review highlight that THz technology can contribute to closed technological circles in important areas of biotechnology and the related plastics and rubber industries.

Funder

ARRS Programme

project “New imaging and analytic methods”

Publisher

MDPI AG

Subject

Radiology, Nuclear Medicine and imaging,Instrumentation,Atomic and Molecular Physics, and Optics

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