Conversion of Fluorescence Signals into Optical Fingerprints Realizing High-Throughput Discrimination of Anionic Sulfonate Surfactants with Similar Structure Based on a Statistical Strategy and Luminescent Metal-Organic Frameworks.

To date, the effective discrimination of anionic sulfonate surfactants with tiny differences in structure, considered as environmentally noxious xenobiotics, is still a challenge for traditional analytical techniques. Fortunately, a sensor array becomes the best choice for recognizing targets with similar structures or physical/chemical properties by virtue of principal component analysis (PCA, a statistical technique). Herein, because of the beneficial construction of the statistical strategy and use of two types of luminescent metal-organic frameworks (LMOFs, NH