Excitation Wavelength as Additional Dimension in Cross-Reactive Sensor Arrays

Abstract Cross-reactive sensor arrays have powerful abilities in distinguishing multiple analytes. The larger the effective data volume is, the better the detection performance is. However, current collected data volume depends heavily on the amount of sensing materials involved. It is data-inefficient for each material and causes heavy workload to prepare materials. Herein, by introducing the dimension of excitation wavelength, we report a cross-reactive sensor array by using only one fluorescent material (β-cyclodextrin-modified quantum dots, QD-β-CD). The newly added dimension is demonstrated by collecting emission signals under four excitation wavelengths. Through machine learning algorithms, the cross-reactive sensor array can be used for the detection of single nitrophenol (NP) isomer (e.g. a superior detectability with a classification accuracy of 94.9 % for 0.01 μM p-nitrophenol), and concurrent quantitative analysis of complex binary/ternary NP mixtures in environment analysis. Our results indicate that the additional dimension of excitation wavelength can provide an effective way to increase the differences of multiple analytes in the design of cross-reactive sensor array. The idea of adding an extra dimension can be generally applicable for the fields of multidimensional information collection.