Modeling of Butadiene Polymerization with a Multicenter Titanium Catalyst Using the Monte Carlo Inversion Algorithm
For butadiene polymerization with the multicenter catalyst TiCl 4 –Al( i -C 4 H 9 ) 3 the inverse kinetic task with identification of the kinetic scheme and determination of the kinetic parameters is solved. The preliminary experimental molecular weight distribution of polybutadiene macromolecules i...
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| Veröffentlicht in: | Polymer science. Series B Jg. 65; H. 2; S. 238 - 246 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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Moscow
Pleiades Publishing
01.04.2023
Springer Nature B.V |
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| ISSN: | 1560-0904, 1555-6123 |
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| Abstract | For butadiene polymerization with the multicenter catalyst TiCl
4
–Al(
i
-C
4
H
9
)
3
the inverse kinetic task with identification of the kinetic scheme and determination of the kinetic parameters is solved. The preliminary experimental molecular weight distribution of polybutadiene macromolecules is approximated by the superposition of Flory distributions. Polymerization is modeled by the Monte Carlo method using a novel fast “inversion” algorithm that enables the time of calculations to be reduced by two orders of magnitude compared with the classical scheme of the method. It is shown that for identification of the kinetic scheme of diene polymerization in the presence of multicenter catalysts coincidence between the experimental and calculated dependences of monomer conversion on time and the dependences of average weights (or average degrees of polymerization) on polymerization time is insufficient. Coincidence between molecular weight distributions at all polymerization times is also required. |
|---|---|
| AbstractList | For butadiene polymerization with the multicenter catalyst TiCl
4
–Al(
i
-C
4
H
9
)
3
the inverse kinetic task with identification of the kinetic scheme and determination of the kinetic parameters is solved. The preliminary experimental molecular weight distribution of polybutadiene macromolecules is approximated by the superposition of Flory distributions. Polymerization is modeled by the Monte Carlo method using a novel fast “inversion” algorithm that enables the time of calculations to be reduced by two orders of magnitude compared with the classical scheme of the method. It is shown that for identification of the kinetic scheme of diene polymerization in the presence of multicenter catalysts coincidence between the experimental and calculated dependences of monomer conversion on time and the dependences of average weights (or average degrees of polymerization) on polymerization time is insufficient. Coincidence between molecular weight distributions at all polymerization times is also required. For butadiene polymerization with the multicenter catalyst TiCl4–Al(i-C4H9)3 the inverse kinetic task with identification of the kinetic scheme and determination of the kinetic parameters is solved. The preliminary experimental molecular weight distribution of polybutadiene macromolecules is approximated by the superposition of Flory distributions. Polymerization is modeled by the Monte Carlo method using a novel fast “inversion” algorithm that enables the time of calculations to be reduced by two orders of magnitude compared with the classical scheme of the method. It is shown that for identification of the kinetic scheme of diene polymerization in the presence of multicenter catalysts coincidence between the experimental and calculated dependences of monomer conversion on time and the dependences of average weights (or average degrees of polymerization) on polymerization time is insufficient. Coincidence between molecular weight distributions at all polymerization times is also required. |
| Author | Styazhkin, D. V. Mingaleev, V. Z. Yanborisov, V. M. Zakharov, V. P. |
| Author_xml | – sequence: 1 givenname: V. M. surname: Yanborisov fullname: Yanborisov, V. M. email: yanborisovvm@mail.ru organization: Ufa University of Science and Technology – sequence: 2 givenname: D. V. surname: Styazhkin fullname: Styazhkin, D. V. organization: Ufa Institute of Chemistry, Ufa Federal Research Center, Russian Academy of Sciences – sequence: 3 givenname: V. Z. surname: Mingaleev fullname: Mingaleev, V. Z. organization: Ufa Institute of Chemistry, Ufa Federal Research Center, Russian Academy of Sciences – sequence: 4 givenname: V. P. surname: Zakharov fullname: Zakharov, V. P. organization: Ufa University of Science and Technology |
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| Cites_doi | 10.3390/pr9050821 10.1016/j.jiec.2013.03.029 10.1002/mren.201300169 10.3390/catal8100442 10.1002/marc.200800592 10.1002/cjce.24406 10.1002/mren.201500075 10.1134/S0023158416010109 10.1002/cjce.24471 10.1002/mren.201300188 10.1002/mren.202000010 10.1021/acs.iecr.9b02277 10.1002/masy.200450206 10.1002/macp.201800522 10.2298/CICEQ111214038S 10.1002/mren.200900040 10.1002/mame.200500086 10.1021/acs.macromol.1c00004 10.1002/mren.202000043 10.1016/j.ces.2007.08.069 10.1002/mren.201600003 10.1002/mren.201800054 10.1002/mren.201700056 10.1002/mren.202200009 10.1002/asia.200900749 10.1002/aic.12705 10.1002/mren.201100032 10.1021/acscatal.9b03226 |
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| Copyright | Pleiades Publishing, Ltd. 2023. ISSN 1560-0904, Polymer Science, Series B, 2023, Vol. 65, No. 2, pp. 238–246. © Pleiades Publishing, Ltd., 2023. ISSN 1560-0904, Polymer Science, Series B, 2023. © Pleiades Publishing, Ltd., 2023. Russian Text © The Author(s), 2023, published in Vysokomolekulyarnye Soedineniya, Seriya B, 2023, Vol. 65, No. 2, pp. 151–160. Pleiades Publishing, Ltd. 2023. |
| Copyright_xml | – notice: Pleiades Publishing, Ltd. 2023. ISSN 1560-0904, Polymer Science, Series B, 2023, Vol. 65, No. 2, pp. 238–246. © Pleiades Publishing, Ltd., 2023. ISSN 1560-0904, Polymer Science, Series B, 2023. © Pleiades Publishing, Ltd., 2023. Russian Text © The Author(s), 2023, published in Vysokomolekulyarnye Soedineniya, Seriya B, 2023, Vol. 65, No. 2, pp. 151–160. – notice: Pleiades Publishing, Ltd. 2023. |
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KulajanpengK.SheibatothmanN.TanthapanichakoonW.McKennaT.Can. J. Chem. Eng.202210025051:CAS:528:DC%2BB38Xhs12gsb7N10.1002/cjce.24471 MonakovYu.SigaevaN.UrazbaevV.Active Sites of Polymerization. Multiplicity: Stereospecific and Kinetic Heterogeneity2005LeidenBrill Vivaldo-LimaE.MohammadiY.PenlidisA.Processes20219110.3390/pr9050821 Zh. Guan (10370_CR3) 2010; 5 (10370_CR5) 2018 P. Pladis (10370_CR10) 2014; 8 S. R. Rafikov (10370_CR38) 1963 K. Kulajanpeng (10370_CR15) 2022; 100 J. P. B. Soares (10370_CR19) 2001; 51 10370_CR29 J. P. B. Soares (10370_CR17) 2022; 100 K. Huang (10370_CR21) 2014; 20 (10370_CR1) 2008 G. Dompazis (10370_CR14) 2008; 63 K. Chen (10370_CR30) 2016; 10 S. Anantawaraskul (10370_CR20) 2004; 206 Zheng-Hong Luo (10370_CR22) 2010; 4 10370_CR24 10370_CR26 D. J. Walsh (10370_CR4) 2019; 9 10370_CR25 J. B. P. Soares (10370_CR11) 2019 Sh. Ahmad (10370_CR12) 2013; 19 10370_CR28 (10370_CR35) 2006 (10370_CR2) 2019 G. Ricci (10370_CR7) 2021; 54 V. M. Yanborisov (10370_CR39) 2010; 22 V. Z. Mingaleev (10370_CR41) 2016; 57 V. M. Yanborisov (10370_CR37) 2012 M. Visseaux (10370_CR6) 2018; 8 V. Touloupidis (10370_CR16) 2014; 8 K. Chen (10370_CR31) 2016; 10 S. Anantawaraskul (10370_CR27) 2011; 5 W-Ch. Yan (10370_CR18) 2012; 58 G. V. Manuiko (10370_CR33) 2022; 23 Yu. Monakov (10370_CR34) 2005 N. Sharma (10370_CR9) 2019; 58 G. Dompazis (10370_CR13) 2005; 290 G. Dompazis (10370_CR23) 2005; 290 10370_CR32 E. Vivaldo-Lima (10370_CR8) 2021; 9 10370_CR36 V. M. Yanborisov (10370_CR40) 2016; 28 |
| References_xml | – reference: A. Krallis, M. Al. Ali, and V. Kanellopoulos, Macromol. React. Eng. 2200009 (2022). – reference: V. Touloupidis, A. Albrecht, and J. P. B. Soares, Macromol. React. Eng. 12 (2), 1700056 (2018). – reference: DompazisG.KanellopoulosV.KiparissidesC.Macromol. Mat. Eng.20052905251:CAS:528:DC%2BD2MXlslCgs7s%3D10.1002/mame.200500086 – reference: MonakovYu.SigaevaN.UrazbaevV.Active Sites of Polymerization. Multiplicity: Stereospecific and Kinetic Heterogeneity2005LeidenBrill – reference: NuykenO.Neodymium Based Ziegler Catalysts. Fundamental Chemistry2006HeidelbergSpringer – reference: YanborisovV. M.YanborisovE. V.SpivakS. I.Formation of Molecular-Weight Distribution in the Polymerization of Dienes in the Presence of Multicenter Catalytic Systems2012UfaIzd. Ufimsk. Gos. Akad. Ekonomiki Servisa – reference: Ch. Hornchaiya, S. Anantawaraskul, J. P. B. Soares, and S. Mehdiabadi, Macromol. Chem. Phys. 220 (6), 1800522 (2019). – reference: YanborisovV. M.SultanovaA. A.KolesovS. V.Matem. Modelir.2016283 – reference: RicciG.PampaloniG.SommazziA.MasiF.Macromolecules20215458791:CAS:528:DC%2BB3MXhsVelt7zP10.1021/acs.macromol.1c00004 – reference: E. Saldivar-Guerra, Macromol. React. Eng. 14 (4), 2000010 (2020). – reference: TouloupidisV.Macromol. React. Eng.201485081:CAS:528:DC%2BC2cXjtVGqsrc%3D10.1002/mren.201300188 – reference: SoaresJ. B. P.TouloupidisV.Multimodal Polymers with Supported Catalysts2019ChamSpringer Nature Switzerland – reference: MingaleevV. Z.Kinet. Katal.2016575410.1134/S0023158416010109 – reference: SoaresJ. P. B.McKennaT. F. L.Can. J. Chem. Eng.202210024321:CAS:528:DC%2BB38XhtFyhtrnL10.1002/cjce.24406 – reference: YanborisovV. M.YanborisovE. V.SpivakS. I.Matem. Modelir.20102215 – reference: HuangK.XieR.J. Ind. Eng. Chem.2014203381:CAS:528:DC%2BC3sXmt1Omu7c%3D10.1016/j.jiec.2013.03.029 – reference: B. Liu, B. Liu, and J. P. B. Soares, Macromol. React. Eng. 12 (6), 1800054 (2018). – reference: ManuikoG. V.BronskayaV. V.AminovaG. 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4
–Al(
i
-C
4
H
9
)
3
the inverse kinetic task with identification of the kinetic scheme and... For butadiene polymerization with the multicenter catalyst TiCl4–Al(i-C4H9)3 the inverse kinetic task with identification of the kinetic scheme and... |
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| SubjectTerms | Algorithms Butadiene Catalysts Catalytic polymerization Chemistry Chemistry and Materials Science Kinetics Molecular structure Molecular weight Molecular weight distribution Monte Carlo simulation Parameter identification Polybutadiene Polymer Sciences Polymerization Polymers Polyolefins Sensors Theory and Simulation |
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| Title | Modeling of Butadiene Polymerization with a Multicenter Titanium Catalyst Using the Monte Carlo Inversion Algorithm |
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