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Analysis of combined mass‐ and volume‐transducing sensor arrays
Author(s) -
Wise Barry M.,
Gallagher Neal B.,
Grate Jay W.
Publication year - 2003
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.792
Subject(s) - volume (thermodynamics) , biological system , least squares function approximation , analyte , inverse problem , inverse , work (physics) , cls upper limits , sensor array , algorithm , computer science , chemistry , thermodynamics , mathematics , physics , chromatography , mathematical analysis , statistics , machine learning , geometry , medicine , estimator , optometry , biology
In prior work it was shown that both mass‐ and volume‐transducing sensor arrays with polymer coatings can be modeled with a classical least squares (CLS)‐type formulation. Given a response vector, this method allows one to solve simultaneously for the vapor descriptors and concentration, even for previously unseen analytes. It has also been shown that inverse least squares (ILS) models can be used in this system to estimate vapor descriptors. A more challenging task is to extract vapor descriptors from sensor arrays which respond to both mass and volume changes simultaneously. This problem is important because surface acoustic wave (SAW) sensors, and probably other types of sensors such as flexural plate wave (FPW) sensors, respond via both mass and volume mechanisms. In this work we show how a closed‐form solution can be obtained to a slightly simplified mass‐and volume‐sensitive system. This solution can be further refined with direct optimization using the full modeling equations. Simulations are performed to evaluate the accuracy of the approximate and refined solutions. This is compared with the accuracy of the known descriptors. Copyright © 2003 John Wiley & Sons, Ltd.