Optimal coating selection for the analysis of organic vapor mixtures with polymer-coated surface acoustic wave sensor arrays
- Univ. of Michigan, Ann Arbor, MI (United States)
A method for determining the optimal set of polymer sensor coatings to include in a surface acoustic wave (SAW) sensor array for the analysis of organic vapors is described. The method combines an extended disjoint principal components regression (EDPCR) pattern recognition analysis with Monte Carlo simulations of sensor responses to rank the various possible coating selections and to estimate the ability of the sensor array to identify any set of vapor analytes. A data base consisting of the calibrated responses of 10 polymer-coated SAW sensors to each of six organic solvent vapors from three chemical classes was generated to demonstrate the method. The predicted rate of vapor identification (87%) was experimentally verified, and the vapor concentrations were estimated within 10% of experimental values in most cases. The majority of errors in identification occurred when an individual vapor could not be differentiated from a mixture of the same vapor with a much lower concentration of a second component. The selection of optimal coating sets for several ternary vapor mixtures is also examined. Results demonstrate the capabilities of polymer-coated SAW sensor arrays for analyzing of solvent vapor mixtures and the advantages of the EDPCR-Monte Carlo method for predicting and optimizing performance. 30 refs., 5 figs., 11 tabs.
- Sponsoring Organization:
- USDOE
- OSTI ID:
- 28709
- Journal Information:
- Analytical Chemistry (Washington), Journal Name: Analytical Chemistry (Washington) Journal Issue: 6 Vol. 67; ISSN ANCHAM; ISSN 0003-2700
- Country of Publication:
- United States
- Language:
- English
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Related Subjects
40 CHEMISTRY
44 INSTRUMENTATION
INCLUDING NUCLEAR AND PARTICLE DETECTORS
66 PHYSICS
99 GENERAL AND MISCELLANEOUS
ADSORPTION ISOTHERMS
CALIBRATION
CHEMICAL ANALYSIS
EXPERIMENTAL DATA
MEASURING INSTRUMENTS
MONTE CARLO METHOD
NUMERICAL DATA
ORGANIC COMPOUNDS
PATTERN RECOGNITION
POLYMERS
SOUND WAVES
SURFACE COATING
VAPORS