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

P Ganga Raju Achary,Sanija Begum,Alla P Toropova,Andrey A Toropov

doi:10.1016/j.md.2016.12.003

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

P Ganga Raju Achary, Sanija Begum + Show 2 more

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https://doi.org/10.1016/j.md.2016.12.003

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Journal: Materials Discovery	Publication Date: Aug 1, 2016
Citations: 13	License type: cc-by

Affiliation: Siksha O Anusandhan University, Mario Negri Institute for Pharmacological Research

#QSPR Model #Adsorption Energy + Show 8 more

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Abstract

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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