Publication detail

Molecularly Imprinted Polymer-Based Electronic Nose for Ultrasensitive, Selective Detection, and Concentration Estimation of VOC Mixtures

HASAN, M. ŠKRABÁNEK, P. CHEFFENA, M.

Original Title

Molecularly Imprinted Polymer-Based Electronic Nose for Ultrasensitive, Selective Detection, and Concentration Estimation of VOC Mixtures

Type

journal article in Web of Science

Language

English

Original Abstract

This research introduces a groundbreaking electronic nose (E-Nose) that integrates advanced sensing materials with machine learning (ML). The sensing materials include molecularly imprinted polymers (MIPs) and multiwalled carbon nanotubes (MWCNTs), designed for enhanced performance. An optimized extreme learning machine (ELM) model enables highly selective detection and precise quantification of both individual and multiple volatile organic compounds (VOCs) within complex mixtures. Specifically, with transducers functionalized for specificity toward methanol, ethanol, butanol, and isopropanol, the proposed E-Nose achieved near-perfect estimation with an error of just 0.25% for individual VOCs and negligible error (0.75%-1.5%) for mixtures of two to four VOCs. The developed E-Nose demonstrated linear estimation of target VOC concentrations with high sensitivity and selectivity. Detection limits (DL) for all gases remained below safety thresholds, ensuring suitability for practical VOC sensing at room temperature (RT). Furthermore, the proposed E-Nose platform is adaptable and customizable for detecting and estimating the tested VOCs as well as other VOCs and gases, offering significant potential to revolutionize air quality monitoring.

Keywords

Sensors; Sensitivity; Estimation; Accuracy; Training; Intelligent sensors; Chemical sensors; Transducers; Sensor arrays; Plastics; Air-quality monitoring; butanol; carbon nanotube; electronic nose (E-Nose); ethanol; extreme learning machine (ELM); isopropanol; machine learning (ML); methanol; molecularly imprinted polymer (MIP); volatile organic compound (VOC) sensor

Authors

HASAN, M.; ŠKRABÁNEK, P.; CHEFFENA, M.

Released

7. 4. 2025

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC

Location

PISCATAWAY

ISBN

1558-1748

Periodical

IEEE SENSORS JOURNAL

Year of study

25

Number

10

State

United States of America

Pages from

18277

Pages to

18290

Pages count

14

URL

https://ieeexplore.ieee.org/document/10955118

BibTex

@article{BUT198037,
  author="Mohammad Mahmudul {Hasan} and Pavel {Škrabánek} and Michael {Cheffena}",
  title="Molecularly Imprinted Polymer-Based Electronic Nose for Ultrasensitive, Selective Detection, and Concentration Estimation of VOC Mixtures",
  journal="IEEE SENSORS JOURNAL",
  year="2025",
  volume="25",
  number="10",
  pages="18277--18290",
  doi="10.1109/JSEN.2025.3556500",
  issn="1558-1748",
  url="https://ieeexplore.ieee.org/document/10955118"
}