A Compositionally Biased Oligourethane Sensor Array To Differentiate Solids by Their Surface Chemistry: An Analogy to the Sense of Touch

Abstract

Array-based differential sensing is inspired by a mammal's sense of taste and smell. The human sense of touch is also array-based; using mechanosensors in the skin that differentiate surfaces by their surface chemistry. Inspired by this, we aimed to develop a rationally biased and randomized oligomer sensor array which differentiates bulk solids by their surface chemistry. Column chromatography mimics this aspect of the sense of touch, as it is traditionally used to physically separate molecules in solution by the strength of their noncovalent interactions with the stationary phase. In this report, we differentiated column chromatography stationary phases (the analyte) by the retention time (the sensor's analytical response) of a vast library of oligomers with statistically biased but random monomer compositions (the sensor array). The use of unsupervised principal component analysis (PCA) validated our sensor array design by differentiating five surfaces with tight replicate clustering and a high degree of cross-reactivity.