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Rapid standoff spectroscopic characterization of plastic waste using quartz tuning fork

  • Yaoli Zhao
  • , Kyle Leatt
  • , Patatri Chakraborty
  • , Leqi Lin
  • , K. Prabakar
  • , Thomas Thundat
  • SUNY Buffalo
  • Indira Gandhi Centre for Atomic Research

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Standoff molecular identification of chemicals finds immense applications in homeland security, forensic investigation and plastic recycling industries. Although, standoff detection using mid-infrared radiation offers excellent molecular selectivity, sensitive detection of mid-IR radiation using inexpensive detectors is a challenge. In the present work, we show commercially available inexpensive Quartz Tuning Fork (QTF) can be effectively used for rapid standoff detection of solid samples using mid-IR radiation. In this method, a plastic sample placed 40 cm away was excited with tunable infrared (IR) radiation pulsed at the resonance frequency of the QTF. The IR radiation scattered off the plastic sample was used for exciting the QTF into resonance. Plotting the QTF resonant amplitude as a function of irradiating IR wavelength represents the unique IR spectrum of the plastic sample under study. The resolution of spectra recorded using QTF was found to be superior to those collected with ATR-FTIR and the technique based on QTF was 103 times faster than microcantilever-based photothermal deflection techniques. By combining simple machine learning algorithms with QTF standoff resonance IR spectra, various plastic samples can be effectively classified with 100% accuracy. Also, this technique was found to be capable of identifying black plastics without any further sample preparation requirements.

Original languageEnglish
Article number135927
JournalSensors and Actuators B: Chemical
Volume414
DOIs
StatePublished - Sep 1 2024

Keywords

  • Machine learning
  • Mid-infrared spectroscopy
  • Plastic classification
  • Quartz tuning fork
  • Standoff detection

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