The aim of this study was to develop fast and facile methods for the determination and classification of zeolite samples based on Si/Al ratio by fourier transform infrared spectroscopy (FTIR). The ZSM-5, ZSM-48 and mordenite catalysts spectral data were used for estimation of Si/Al ratio using two approaches according to PLS-R and SVM-R algorithms in whole (600–4000 cm⁻¹) and fingerprint (3000–3800 cm⁻¹) spectral regions. The drift-FTIR spectral data were also analyzed by classification method using the soft independent modelling of class analogies (SIMCA) for mordenite, ZSM-5 and ZSM-48 catalysts classification. Performance of the regression models was adequate with good statistical results. The correlation coefficients (R²) were about 0.99 and 0.96 for SVM and PLS regression models. The results obtained for the SVM model of the MIR spectra was very good and encouraging, since the RMSEP was low (6%) and the quantitative results were in accordance with X-ray fluorescence analysis. Then the samples were classified into three mordenite, ZSM-5 and ZSM-48 classes based on their Si/Al ratio by the SIMCA method using raw and pre-treated spectra. Using SIMCA technique, the 100% of samples were correctly classified in pre-treated spectra. The accurate and stable model was obtained with pre-treated spectra for SIMCA model (100% of sensitivity and 100% of specificity). The results indicated that drift-FTIR spectroscopy in conjunction with multivariate calibration and classification methods is a fast and reliable methodology that can be easily implemented for determination and classification of zeolite catalysts based on their Si/Al ratio.

本研究的目的是开发基于 Si/Al 比的傅里叶变换红外光谱 (FTIR) 测定和分类沸石样品的快速简便方法。ZSM-5、ZSM-48 和丝光沸石催化剂光谱数据用于根据 PLS-R 和 SVM-R 算法整体（600–4000 cm ^-1）和指纹（3000– 3800 cm ^-1 ) 光谱区域。漂移-FTIR 光谱数据也通过分类方法进行分析，使用软独立的类比建模（SIMCA）用于丝光沸石、ZSM-5 和 ZSM-48 催化剂分类。回归模型的性能足够，具有良好的统计结果。相关系数 (R ²) 对于 SVM 和 PLS 回归模型，分别约为 0.99 和 0.96。MIR 光谱的 SVM 模型获得的结果非常好且令人鼓舞，因为 RMSEP 低 (6%) 并且定量结果与 X 射线荧光分析一致。然后，通过 SIMCA 方法，使用原始光谱和预处理光谱，根据样品的 Si/Al 比，将样品分为三个丝光沸石、ZSM-5 和 ZSM-48 类别。使用 SIMCA 技术，100% 的样品在预处理光谱中被正确分类。对SIMCA模型(100%的灵敏度和100%的特异性)用预处理光谱获得准确和稳定的模型。