Skip to main content
Log in

Real-time, Economical Identification of Microplastics Using Impedance-based Interdigital Array Microelectrodes and k-Nearest Neighbor Model

  • Research Paper
  • Published:
Biotechnology and Bioprocess Engineering Aims and scope Submit manuscript

Abstract

Microplastic, being a direct carrier of many pollutants, has caused grave concern and become a public issue. This gives rise to the need of a quick method for quantifying and identifying microplastics in the environment. This study uses impedance spectroscopy, particularly the imaginary part of impedance, for detection and identification of sample microplastics. Two type of common microplastic contaminants, Polyethylene and Polystyrene, diameter 20 µm and 150 µm, were chosen for this study. The results confirm accurate identification of microplastic material in question, by using self-normalized ratio between two characteristic frequencies of 7 MHz and 8.9 MHz, Z′f=7 MHz/Z′f=8.9 MHz. 3-kNN classifier built with the ratio Z′f=7 MHz/Z′f=8.9 MHz, and Z′f=8 MHz/Z′f=8.9 MHz, demonstrates accuracy upto 90% for the identification of single or both microplastic types in samples. These results confirm impedance spectroscopy, permitting rapid identification of microplastic without labeling and skillful techniques, as a potential rapid sensor.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Zhao, Y., Z. Bao, Z. Wan, Z. Fu, and Y. Jin (2020) Polystyrene microplastic exposure disturbs hepatic glycolipid metabolism at the physiological, biochemical, and transcriptomic levels in adult zebrafish. Sci. Total Environ. 710: 136279.

    Article  CAS  PubMed  Google Scholar 

  2. Prokić, M. D., T. B. Radovanović, J. P. Gavrić, and C. Faggio (2019) Ecotoxicological effects of microplastics: examination of biomarkers, current state and future perspectives. Trends Analyt. Chem. 111: 37–46.

    Article  Google Scholar 

  3. Prokić, M. D., B. R. Gavrilović, T. B. Radovanović, J. P. Gavrić, T. G. Petrović, S. G. Despotović, and C. Faggio (2021) Studying microplastics: lessons from evaluated literature on animal model organisms and experimental approaches. J. Hazard. Mater. 414: 125476.

    Article  PubMed  Google Scholar 

  4. Thompson, R. C., Y. Olsen, R. P. Mitchell, A. Davis, S. J. Rowland, A. W. John, D. McGonigle, and A. E. Russell (2004) Lost at sea: where is all the plastic? Science 304: 838.

    Article  CAS  PubMed  Google Scholar 

  5. Embrandiri, A., S. Quaik, M. I. Emmanuel, M. Rahma, P. F. Rupani, M. H. Jamaludin, and M. A. Naim (2019) “Microplastics”: the next threat to mankind? pp. 106–122. In: A. C. Affam and E. H. Ezechi (eds.). Handbook of Research on Resource Management for Pollution and Waste Treatment. IGI Global, Hershey, PA, USA.

    Google Scholar 

  6. Li, D., Y. Shi, L. Yang, L. Xiao, D. K. Kehoe, Y. K. Gun’ko, J. J. Boland, and J. J. Wang (2020) Microplastic release from the degradation of polypropylene feeding bottles during infant formula preparation. Nat. Food 1: 746–754.

    Article  CAS  PubMed  Google Scholar 

  7. Yin, R., H. Ge, H. Chen, J. Du, Z. Sun, H. Tan, and S. Wang (2021) Sensitive and rapid detection of trace microplastics concentrated through Au-nanoparticle-decorated sponge on the basis of surface-enhanced Raman spectroscopy. Environ. Adv. 5: 100096.

    Article  CAS  Google Scholar 

  8. Meyers, N., A. I. Catarino, A. M. Declercq, A. Brenan, L. Devriese, M. Vandegehuchte, B. De Witte, C. Janssen, and G. Everaert (2022) Microplastic detection and identification by Nile red staining: towards a semi-automated, cost- and time-effective technique. Sci. Total Environ. 823: 153441.

    Article  CAS  PubMed  Google Scholar 

  9. Vermeiren, P., C. Muñoz, and K. Ikejima (2020) Microplastic identification and quantification from organic rich sediments: a validated laboratory protocol. Environ. Pollut. 262: 114298.

    Article  CAS  PubMed  Google Scholar 

  10. Goedecke, C., D. Dittmann, P. Eisentraut, Y. Wiesner, B. Schartel, P. Klack, and U. Braun (2020) Evaluation of thermoanalytical methods equipped with evolved gas analysis for the detection of microplastic in environmental samples. J. Anal. Appl. Pyrolysis 152: 104961.

    Article  CAS  Google Scholar 

  11. Zhu, C., Y. Kanaya, M. Tsuchiya, R. Nakajima, H. Nomaki, T. Kitahashi, and K. Fujikura (2020) Optimization of a hyperspectral imaging system for rapid detection of microplastics down to 100 µm. MethodsX 8: 101175.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Tagg, A. S., M. Sapp, J. P. Harrison, C. J. Sinclair, E. Bradley, Y. Ju-Nam, and J. J. Ojeda (2020) Microplastic monitoring at different stages in a wastewater treatment plant using reflectance micro-FTIR imaging. Front. Environ. Sci. 8: 145.

    Article  Google Scholar 

  13. Tagg, A. S., M. Sapp, J. P. Harrison, and J. J. Ojeda (2015) Identification and quantification of microplastics in wastewater using focal plane array-based reflectance micro-FT-IR imaging. Anal. Chem. 87: 6032–6040.

    Article  CAS  PubMed  Google Scholar 

  14. Rivoira, L., M. Castiglioni, S. M. Rodrigues, V. Freitas, M. C. Bruzzoniti, S. Ramos, and C. M. R. Almeida (2020) Microplastic in marine environment: reworking and optimisation of two analytical protocols for the extraction of microplastics from sediments and oysters. MethodsX 7: 101116.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Colson, B. C. and A. P. M. Michel (2021) Flow-through quantification of microplastics using impedance spectroscopy. ACS Sens. 6: 238–244.

    Article  CAS  PubMed  Google Scholar 

  16. Kuo, Y. C., C. K. Lee, and C. T. Lin (2018) Improving sensitivity of a miniaturized label-free electrochemical biosensor using zigzag electrodes. Biosens. Bioelectron. 103: 130–137.

    Article  CAS  PubMed  Google Scholar 

  17. Kuo, Y.-C., C.-S. Chen, K.-N. Chang, C.-T. Lin, and C.-K. Lee (2014) Sensitivity improvement of a miniaturized label-free electrochemical impedance biosensor by electrode edge effect. J. Micro. Nanolithogr. MEMS MOEMS 13: 033019.

    Article  Google Scholar 

  18. Laibinis, P. E. and G. M. Whitesides (1992) ω-Terminated alkanethiolate monolayers on surfaces of copper, silver, and gold have similar wettabilities. J. Am. Chem. Soc. 114: 1990–1995.

    Article  CAS  Google Scholar 

  19. Laibinis, P. E., G. M. Whitesides, D. L. Allara, Y. T. Tao, A. N. Parikh, and R. G. Nuzzo (1991) Comparison of the structures and wetting properties of self-assembled monolayers of n-alkanethiols on the coinage metal surfaces, copper, silver, and gold. J. Am. Chem. Soc. 113: 7152–7167.

    Article  CAS  Google Scholar 

  20. Phan, T. L., N. V. Hieu, T. S. Li, K. C. Tsao, and C. T. S. Ching (2021) Noninvasive and real-time in vivo characterization of Inflammation skin. A feasibility of animal study. Skin Res. Technol. 27: 846–853.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

This work was supported by grant from the National Chung Hsing University and the Show Chwan Memorial Hospital, Taiwan, Republic of China. This work was also supported in part by grants (109-2313-B-005-007-, 111-2221-E-005-018-) from the Ministry of Science and Technology, Taiwan, Republic of China.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Yung-Kai Lin or Thien Luan Phan.

Ethics declarations

The authors declare no conflict of interest.

Neither ethical approval nor informed consent was required for this study.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ching, C.T.S., Lee, PY., Hieu, N.V. et al. Real-time, Economical Identification of Microplastics Using Impedance-based Interdigital Array Microelectrodes and k-Nearest Neighbor Model. Biotechnol Bioproc E 28, 459–466 (2023). https://doi.org/10.1007/s12257-022-0262-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12257-022-0262-y

Keywords

Navigation