基于准SMILES的丙烯聚合Ziegler−Natta催化剂吸附能预测的QSPR方法

P. Ganga Raju Achary , Sanija Begum , Alla P. Toropova , Andrey A. Toropov
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引用次数: 9

摘要

QSPR模型是众所周知的物理化学性质的可靠预测。内部供体分子的准SMILES编码来源于邻苯二甲酸酯、1,3-二醚和丙二酸酯的不同分子片段。吸附能已经用从这种准SMILES代码导出的最优描述符进行了建模。QSPR模型成功地应用于ZN催化丙烯聚合设计了24种具有较好吸附能的新型内给体。准QSPR模型的科学性不足以作为一个抽象,因此本文对其进行了详细的描述,以便人们了解如何开发基于准SMILES的模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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A quasi-SMILES based QSPR Approach towards the prediction of adsorption energy of Ziegler − Natta catalysts for propylene polymerization

QSPR models are well known for reliable prediction of physicochemical properties. The quasi-SMILES code of the internal donor molecules are derived from the different molecular fragments of phthalates, 1,3-diethers and malonates. The adsorption energy has been modeled with the optimal descriptor derived from such quasi-SMILES codes. QSPR model was successfully applied for designing 24 new internal donors for the ZN catalyzed propylene polymerization with better adsorption energies. The science of quasi-QSPR model is not sufficient for an abstract, therefore described in detail in the paper so that one can learn how to develop the quasi-SMILES based models.

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