Literature DB >> 24554126

2D-QSPR/DFT studies of aryl-substituted PNP-Cr-based catalyst systems for highly selective ethylene oligomerization.

Siyang Tang1, Zhen Liu, Xingwen Zhan, Ruihua Cheng, Xuelian He, Boping Liu.   

Abstract

1-Hexene and 1-octene are important comonomers for the synthesis of high performance polyolefins. Recently, various N-substituted Cr-bis(diphenylphosphino)amine (PNP-Cr) catalysts show the potential as excellent candidates for highly selective ethylene trimerization/tetramerization. In this work, a series of aryl-substituted PNP-Cr catalysts were studied by two-dimensional quantitative structure-property relationship (QSPR) method based on density functional theory (DFT) calculations. The heuristic method (HM) and best multi-linear regression (BMLR) were used to establish the best linear regression models to describe the relationship between selectivities and catalyst structures. Both Cr(I) and Cr(II) active site models for ethylene trimerization/tetramerization were considered. It was found that 1) the relativity and stability of the models were increased by using self-defined descriptors based on DFT calculations; 2) Cr(I)/Cr(III) centers were the most plausible active sites for ethylene trimerization, while Cr(II)/Cr(IV) active sites were most possibly responsible for ethylene tetramerization; and 3) the skeleton structures of the PNP-Cr system with good complanation and symmetry were crucial for achieving excellent catalytic selectivity of 1-octene, while the PNP-Cr backbone with a large steric effect on N atom would benefit ethylene trimerization. Six new PNP ligands with high selectivity toward ethylene trimerization/tetramerization were predicted based on descriptor analysis and the best linear regression models providing a good basis for further development of novel catalyst systems with better performance.

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Year:  2014        PMID: 24554126     DOI: 10.1007/s00894-014-2129-4

Source DB:  PubMed          Journal:  J Mol Model        ISSN: 0948-5023            Impact factor:   1.810


  16 in total

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Authors:  Werner Janse van Rensburg; Petrus J Steynberg; Wolfgang H Meyer; Megan M Kirk; Grant S Forman
Journal:  J Am Chem Soc       Date:  2004-11-10       Impact factor: 15.419

6.  Ethylene tetramerization: a new route to produce 1-octene in exceptionally high selectivities.

Authors:  Annette Bollmann; Kevin Blann; John T Dixon; Fiona M Hess; Esna Killian; Hulisani Maumela; David S McGuinness; David H Morgan; Arno Neveling; Stefanus Otto; Matthew Overett; Alexandra M Z Slawin; Peter Wasserscheid; Sven Kuhlmann
Journal:  J Am Chem Soc       Date:  2004-11-17       Impact factor: 15.419

7.  Prediction of polyamide properties using quantum-chemical methods and BP artificial neural networks.

Authors:  Jinwei Gao; Xueye Wang; Xiaobing Li; Xinliang Yu; Hanlu Wang
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8.  Quantitative structure-activity relationships of ruthenium catalysts for olefin metathesis.

Authors:  Giovanni Occhipinti; Hans-René Bjørsvik; Vidar R Jensen
Journal:  J Am Chem Soc       Date:  2006-05-31       Impact factor: 15.419

9.  Ethylene tri- and tetramerization: a steric parameter selectivity switch from X-ray crystallography and computational analysis.

Authors:  Nicoline Cloete; Hendrik G Visser; Ilana Engelbrecht; Matthew J Overett; William F Gabrielli; Andreas Roodt
Journal:  Inorg Chem       Date:  2013-02-08       Impact factor: 5.165

10.  QSPR modeling of thermal stability of nitroaromatic compounds: DFT vs. AM1 calculated descriptors.

Authors:  Guillaume Fayet; Patricia Rotureau; Laurent Joubert; Carlo Adamo
Journal:  J Mol Model       Date:  2010-01-05       Impact factor: 1.810

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  3 in total

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Journal:  Sci Rep       Date:  2021-02-25       Impact factor: 4.379

Review 2.  Towards operando computational modeling in heterogeneous catalysis.

Authors:  Lukáš Grajciar; Christopher J Heard; Anton A Bondarenko; Mikhail V Polynski; Jittima Meeprasert; Evgeny A Pidko; Petr Nachtigall
Journal:  Chem Soc Rev       Date:  2018-11-12       Impact factor: 54.564

3.  Quantum-mechanical transition-state model combined with machine learning provides catalyst design features for selective Cr olefin oligomerization.

Authors:  Steven M Maley; Doo-Hyun Kwon; Nick Rollins; Johnathan C Stanley; Orson L Sydora; Steven M Bischof; Daniel H Ess
Journal:  Chem Sci       Date:  2020-08-21       Impact factor: 9.825

  3 in total

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