Big Data processing tools have become increasingly powerful and have been applied to the area of personal chemical monitoring by companies such as Plume Labs and Rubix, requiring low-cost, capable sensors. The ubiquity of cell phone imagers has allowed for a revisiting of colorimetry as a viable chemical detection method. There has been a great deal of effort put into making colorimetric sensor arrays that can discriminate between a variety of analytes, but mainly in a qualitative sense with limited discussion regarding improving the performance of the sensor as a whole. However, these imaging devices have inherent limitations on their ultimate sensitivity. Other sensor configurations are being evaluated that can greatly enhance the sensitivity to a color change. Dye development continues in an effort to increase the specificity of the sensing event using currently available readout mechanisms, but what has been lacking has been a critical analysis of the readout mechanism for these molecular transducers. This work takes a quantitative approach to encourage a more rational design of colorimetric sensors with specific targets.
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