Amani Shahin, Garmarudi Amir Bagheri, Khanmohammadi Mohammadreza, Yaripour Fereydoon
Department of Chemistry, Faculty of Science, Imam Khomeini International University Qazvin Iran
Catalysis Research Group, Petrochemical Research & Technology Company NPC Tehran Iran.
RSC Adv. 2018 Oct 10;8(61):34830-34837. doi: 10.1039/c8ra03244k.
Evaluation of porosity type of zeolites is one of the critical topics in catalysis science. The relationship between external surface area and diffuse reflectance (DR) spectra in the near-infrared spectral region has been employed to propose a method for estimation of micro or mesoporosity in ZSM-5 zeolite samples. Linear discriminant analysis (LDA) was utilized to estimate degree of porosity based on near-infrared diffuse reflectance spectra. The textural properties (surface area and pore volume) of micro and mesoporous ZSM-5 samples were measured using N adsorption/desorption technique at 77 K and external surface area was calculated by -plot as a reference method in this work. Several porous ZSM-5 samples with only microporous channels or mesoporous besides them were classified in terms of external surface area and meso pore volume derived from -plot as "Micro" or "Micro + Meso" type samples. It was concluded that LDA using the PCA for feature selection is capable of generalization and could precisely predict the type of porosity in ZSM-5 zeolites.
评估沸石的孔隙类型是催化科学中的关键课题之一。已利用近红外光谱区域中外表面面积与漫反射(DR)光谱之间的关系,提出了一种估算ZSM-5沸石样品中微孔或介孔率的方法。基于近红外漫反射光谱,利用线性判别分析(LDA)来估算孔隙率。在这项工作中,使用77K下的N吸附/脱附技术测量了微孔和介孔ZSM-5样品的织构性质(表面积和孔体积),并通过t-plot计算外表面面积作为参考方法。根据t-plot得出的外表面面积和介孔体积,将几个仅具有微孔通道或除微孔外还具有介孔的多孔ZSM-5样品分类为“微孔”或“微孔+介孔”型样品。得出的结论是,使用主成分分析(PCA)进行特征选择的LDA具有泛化能力,能够精确预测ZSM-5沸石的孔隙类型。