Quantum dots (QDs) are very attractive nanomaterials for analytical chemistry, due to high photostability, large surface area featuring numerous ways of bioconjugation with biomolecules, usually high quantum yield and long decay times. Their broad absorption spectra and narrow, sharp emission spectra of size-tunable fluorescence make them ideal tools for pattern-based sensing. However, almost always they are applied for specific sensing with zero-dimensional (0D) signal reporting (only peak heights or peak shifts are considered), without taking advantage of greater amount of information hidden in 1D signal (emission spectra), or huge amount of information hidden in 2D fluorescence maps (Excitation-Emission Matrixes, EEMs). Therefore, in this work we propose opposite strategy—non-specific interactions of QDs, which are usually avoided and regarded as their disadvantage, were exploited here for 2D fluorescence fingerprinting. Analyte-specific multivariate fluorescence response of QDs is decoded with the use of Partial Least Squares—Discriminant Analysis. Even though only one type of QDs is studied, the proposed pattern-based method enables to obtain satisfactory accuracy for all studied compounds—various neurotransmitters, amino-acids and oligopeptides. This is a proof of principle of the possibility of the identification of various bioanalytes by such fluorescence fingerprinting with the use of QDs.
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