Three-dimensional fluorescence spectroscopy coupled with parallel factor analysis and neural network was applied to the year discrimination of mild aroma Chinese liquors. The excitation-emission fluorescence matrices (EEMs) of 120 samples with various years were measured by FLS920 fluorescence spectrometer. The trilinear decomposition of the data array was performed and the loading scores of and the excitation-emission profiles of four components were also obtained. The scores were employed as the inputs of the BP neural networks and the PARAFAC-BP identification model was constructed. 10 samples were collected from 10, 20 and 30 years of liquors respectively, and 30 samples were selected as the test sets. The remaining 90 samples were used as the training sets to build the training model. The year prediction of unknown samples was also carried out, and the prediction accuracy was 90%, 100% and 100%, respectively. Meanwhile, the discrimination analysis method and the multi way partial least squares discriminant analysis were compared, namely PARAFAC-BP and NPLS-DA. The results indicated that parallel factor combined with the neural network (PARAFAC-BP) has higher prediction accuracy. The proposed method can effectively extract the spectral characteristics, and also reduce the dimension of the input variables of neural network. A good year discrimination result was finally achieved. 相似文献
Perfluoropolyether (PFPE)‐based thermoplastic fluoropolymers are synthesized by A2 + B2 step‐growth polymerization between PFPE‐diyne and fluorinated diazides. This versatile method allows synthesizing PFPE‐based materials with tunable physicochemical properties depending on the exact nature of the fluorinated segment of the diazide precursor. Semicrystalline or amorphous materials endowed with high thermostability (≈300 °C under air) and low glass transition temperature (≈−100 °C) are obtained, as confirmed by differential scanning calorimetry, thermogravimetry, and rheometry. Step‐growth polymerizations can be copper‐catalyzed but also thermally activated in some cases, thus avoiding the presence of copper residues in the final materials. This strategy opens up new opportunities to easily access PFPE‐based materials on an industrial scale. Furthermore, a plethora of developments can be envisioned (e.g., by adding a third trifunctional component to the formulations for the synthesis of PFPE‐based elastomers).
