Selection of polymeric sensor arrays for quantitative analysis

A novel method has been developed to optimize the selection of polymeric materials to be used within a chemiresistor array for anticipated samples without preliminary experiments. It is based on the theoretical predicted responses of chemiresistors and the criterion of minimizing the mean square error (MSE) of the chemiresistor array. After the number of chemiresistor to be used in an array and anticipated sample chemistry are determined, the MSE values of all combinations of the candidate chemiresistors are calculated. The combination which has the minimum MSE value is the best choice. This can become computationally intensive for selection of polymers for large arrays from candidates in a large database. The number of combination can be reduced by using the branch and bound method to save computation time. This method is suitable for samples at low concentrations where thermodynamic multi-component interactions are linear.