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Statistical analysis and Partial Least Square regression as new tools for modelling and understanding the adsorption properties of zeolites

机译:统计分析和偏最小二乘回归是建模和了解沸石吸附特性的新工具

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摘要

Statistical data analysis was applied to examine previously published adsorption enthalpies of linear and branched alkanes on zeolites Na-Y, Na-USY, Mordenite, Beta, ZSM-5 and ZSM-22. The objective was to establish predictive models that correlate the adsorption enthalpies for the six zeolites to simple structural properties or descriptors of the adsorbates. Two sets of descriptors were tested; a first set was chosen from a library of topological descriptors (the Wiener index, the Kier shape indices and the Kier + Hall connectivity indices), the other set was custom-made, by directly parametrizing the number of carbon atoms as well as position and degree of branching. From the set of 17 available adsorbates, training sets of 10 molecules were selected by a clustering analysis and this training set was subjected to a Partial Least Squares (PLS) regression in order to establish a linear relationship between the adsorption enthalpy and the set of descriptors. The model was then applied to predict the adsorption enthalpies of the other molecules. In all cases, predicted and experimental values were in good agreement. The model based on the custom-made descriptors that code the branching of the molecules was less precise, but allowed a more straightforward interpretation of the coefficients of the model, which provides very interesting insights into the adsorption behaviour of the linear and branched alkanes on large and medium pore zeolites.
机译:应用统计数据分析来检查先前公开的直链和支链烷烃在沸石Na-Y,Na-USY,丝光沸石,Beta,ZSM-5和ZSM-22上的吸附焓。目的是建立将六种沸石的吸附焓与简单的结构性质或被吸附物的描述因素相关的预测模型。测试了两组描述符。从拓扑描述符库(维纳指数,基尔形状指数和基尔+霍尔连通性指数)中选择第一组,另一组是通过直接参数化碳原子数以及位置和碳原子数来定制的。分支度。从17种可用吸附质的集合中,通过聚类分析选择10个分子的训练集,并对该训练集进行偏最小二乘(PLS)回归,以建立吸附焓与描述子集之间的线性关系。然后将该模型用于预测其他分子的吸附焓。在所有情况下,预测值和实验值均吻合良好。基于编码分子分支的定制描述符的模型不太精确,但是允许更直接地解释模型的系数,这为线性和支链烷烃在大分子上的吸附行为提供了非常有趣的见解。和中孔沸石。

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