Abstract
This review summarizes the current status of development in photoluminescent probes, multidimensional photoluminescence detection, and multivariate data analysis methods. It then highlights reports featuring multivariate analysis of multidimensional measurements of photoluminescent probes published between June 2015 and June 2022, emphasizing work in the last 5 years. Important trends include the development of probe arrays, which provide fingerprint responses to the analyte(s) of interest and facilitate the analysis of complex samples; the application of neural networks and deep learning to pattern recognition and feature selection in photoluminescence images; and the application of multiway multivariate analysis to mining matrices, three-way arrays, and higher-order measurements, including hyperspectral intensity and lifetime images. These examples illustrate the increase in information extraction provided by the combination of multidimensional measurements and multivariate analysis.
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