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Class specific discrimination of volatile organic compounds using a quartz crystal microbalance based multisensor

Stephanie R Vaughan1, Nicholas C Speller2, Pratap Chhotaray3

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Talanta
|July 22, 2018
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Summary
This summary is machine-generated.

Novel phthalocyanine-based GUMBOS (groups of uniformed materials based on organic salts) show high accuracy in discriminating volatile organic compounds (VOCs) using quartz crystal microbalance (QCM) sensor arrays.

Keywords:
GUMBOSPhthalocyanineQCMSensor arrayVOCs

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Area of Science:

  • Chemical Sensors
  • Materials Science
  • Analytical Chemistry

Background:

  • Quartz crystal microbalance (QCM) sensor arrays are increasingly used for analyzing volatile organic compounds (VOCs).
  • Groups of uniformed materials based on organic salts (GUMBOS) offer tunable properties, making them promising recognition elements for QCM sensor arrays.
  • Phthalocyanine-based GUMBOS represent a novel class of materials with potential for enhanced VOC sensing applications.

Purpose of the Study:

  • To investigate the efficacy of four novel phthalocyanine-based GUMBOS as recognition elements in a QCM-based multisensor array (MSA) for VOC sensing.
  • To synthesize and characterize new GUMBOS materials incorporating copper (II) phthalocyaninetetrasulfonate anions with various ammonium and phosphonium cations.
  • To evaluate the performance of the developed QCM-MSA for discriminating common VOCs based on their functional group classes.

Main Methods:

  • Synthesis and characterization of four phthalocyanine-based GUMBOS using ESI-MS, FTIR, and TGA.
  • Fabrication of a QCM-based multisensor array (MSA) utilizing the synthesized GUMBOS as recognition elements.
  • Exposure of the QCM-MSA to a set of common VOCs at varying sample flow rates and analysis of sensor response patterns using principal component and discriminant analyses.

Main Results:

  • The synthesized GUMBOS were successfully characterized, and their thermal properties were investigated.
  • The QCM-MSA demonstrated analyte-specific response patterns upon exposure to different VOCs.
  • The multisensor array achieved a high discrimination accuracy of 98.6% for classifying VOCs into functional group classes (alcohols, chlorohydrocarbons, aromatic hydrocarbons, and hydrocarbons).

Conclusions:

  • Phthalocyanine-based GUMBOS are effective recognition elements for QCM-based MSAs in VOC sensing.
  • The developed QCM-MSA system offers a highly accurate method for discriminating VOCs based on their chemical properties.
  • This research provides valuable insights into the application of tunable GUMBOS materials for advanced chemical sensing technologies.