Relationship of Surface Acoustic Wave Vapor Sensor Responses to Thermodynamic Parameters for Gas Solubility: Polymer/Gas Partition Coefficients for Fluoropolyol.

Abstract

Surface acoustic wave (SAW) devices coated with a thin film of a stationary phase sense chemical vapors in the gas phase by detecting the mass of the vapor which distribute into the stationary phase. This distribution can be described by the partition coefficient, which gives the ratio of the concentration of the vapor in the stationary phase to the concentration of the vapor in the gas phase. An equation is presented which allows partition coefficients to be calculated from SAW vapor sensor frequency shifts. Partition coefficients for nine vapors into SAW coating fluoropolyol have been determined by this method, using both 112 MHz and 158 MHz SAW devices. Partition coefficients have also been determined independently by GLC and the results are is good agreement. The relationship between SAW frequency shifts and partition coefficients allows SAW sensor responses to be predicted if the partition coefficient has been measured by GLC, or if the partition coefficient can be estimated by various correlation methods being developed. Keywords: Surface acoustic wave, Microsensor, Vapor sensor, Fluoropolyol, Partition coefficient, Gas liquid chromatography.

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Document Details

Document Type
Technical Report
Publication Date
Jul 29, 1987
Accession Number
ADA183694

Entities

People

  • Arthur Snow
  • David S. Ballantine
  • Hank Wohltjen
  • Jay W. Grate
  • Michael H. Abraham

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Acoustic Waves
  • Chemistry
  • Classification
  • Detectors
  • Equations
  • Films
  • Frequency
  • Frequency Shift
  • Materials
  • Measurement
  • Plastic Explosives
  • Surface Acoustic Wave Devices
  • Surface Acoustic Waves
  • Surface Waves
  • Thin Films
  • Transducers
  • Waves

Readers

  • Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.
  • Mathematical Modeling and Probability Theory.
  • Spectroscopy.