To download article.DOI: 10.15507/2658-4123.033.202303.388-402
Evaluating the Efficiency of the Tube Turbulent Apparatus Influence on Kinetics of Polymer Production Processes
Eldar N. Miftakhov
Cand.Sci. (Phys.-Math.), Senior Researcher, Ufa University of Science and Technology (32 Zaki Validi St., Ufa 450076, Russian Federation), ORCID: https://orcid.org/0000-0002-0471-5949, Researcher ID: AAA-5885-2019, Scopus ID: 56178153800, This email address is being protected from spambots. You need JavaScript enabled to view it.
Sofya I. Mustafina
Junior Researcher, Ufa University of Science and Technology (32 Zaki Validi St., Ufa 450076, Russian Federation), ORCID: https://orcid.org/0000-0001-8036-3001, Scopus ID: 57204930367, This email address is being protected from spambots. You need JavaScript enabled to view it.
Nikolay D. Morozkin
Dr.Sci. (Phys.-Math.), Professor, President of the Ufa University of Science and Technology (32 Zaki Validi St., Ufa 450076, Russian Federation), ORCID: https://orcid.org/0009-0002-5051-7094, Scopus ID: 6603118906, This email address is being protected from spambots. You need JavaScript enabled to view it.
Ildus Sh. Nasyrov
Cand.Sci. (Chemistry), Deputy General Director for Development (for Science), Join Stock Company Sintez Rubber (14 Tekhnicheskaya St., Sterlitamak 453110, Russian Federation), ORCID: https://orcid.org/0000-0001-8273-3651, Scopus ID: 6603373003, This email address is being protected from spambots. You need JavaScript enabled to view it.
Svetlana A. Mustafina
Dr.Sci. (Phys.-Math.), Professor, Vice-Rector for Branch Network Development, Head of the Department of Mathematical Modeling, Ufa University of Science and Technology (32 Zaki Validi St., Ufa 450076, Russian Federation), ORCID: https://orcid.org/0000-0002-6363-1665, Researcher ID: AAC-3926-2020, Scopus ID: 6603592002, This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract
Introduction. Because of high demand for polymer products, there are constantly modernized the technological aspects of their production, a huge share of which is based on the use of microheterogeneous catalytic systems. Physicochemical properties of polymer products can be improved through targeted hydrodynamic effect in turbulent flows. The study of physicochemical patterns of polymer product synthesis in the presence of modified catalytic systems is of great interest.
Aim of the Article. The article is aimed at evaluating the efficiency of hydrodynamic influence in turbulent flows on the type of catalyst heterogeneity and the kinetics of polymer production processes.
Materials and Methods. In the study of polymer synthesis processes, there is used a simulation approach to the system model description that is based on the idea of reproducing various scenarios of uninterrupted production and conducting the necessary empirical analysis. Parallel programming and cloud computing technologies are used in simulation modeling to increase computational speed.
Results. A methodology for solving inverse problems has been developed to determine the influence of external factors on the kinetic activity and heterogeneity of active centers on the basis of known physicochemical information. The use of simulation modeling with the application of cloud computing technology makes it possible to unambiguously determine the type of kinetic heterogeneity in the conditions of averaging the reactive capacity of active centers.
Discussion and Conclusion. Approbation of the new simulation approach to the solution of the inverse problem allowed evaluating the efficiency of the influence of the tube turbulent apparatus on the kinetics of producing polyisoprene in the presence of titanium catalyst and identifying the presence of two active centers: type ATi − lnM = 13.4, type BTi − lnM = 11.7, while the proportion of active centers type ATi is 0.91; type BTi – 0.09. Based on the data obtained, it becomes possible to formulate and solve inverse problems of identifying kinetic parameters for further model description of the system.
Keywords: synthetic rubber, polymer, tube turbulent apparatus, hydrodynamic action, mathematical modeling
Acknowledgments: This research was funded by the Ministry of Science and Higher Education of the Russian Federation (scientific code FZWU-2023-0002).
Conflict of interest: The authors declare no conflict of interest.
For citation: Miftakhov E.N., Mustafina S.I., Morozkin N.D., Nasyrov I.Sh., Mustafina S.A. Evaluating the Efficiency of the Tube Turbulent Apparatus Influence on Kinetics of Polymer Production Processes. Engineering Technologies and Systems. 2023;33(3):388‒402. https://doi.org/10.15507/2658-4123.033.202303.388-402
Authors contribution:
E. N. Miftakhov – developing methods and algorithms for solving direct problems, conducting computational experiments, writing the text of the article.
S. I. Mustafina – programming of computational methods for organization of calculations N. D. Morozkin – analyzing the results of the study, reviewing of literary sources.
I. Sh. Nasyrov – planning and organization of the necessary laboratory experiments.
S. A. Mustafina – setting the goal and objectives of the study, planning the necessary computational experiments, analyzing the results.
All authors have read and approved the final manuscript.
Submitted 05.07.2023; revised 01.08.2023;
accepted 20.08.2023.
REFERENCES
1. Zaikov G., Monakov Y., Sigaeva N., Urazbaev V. Active Sites of Polymerization. Multiplicity: Stereospecific and Kinetic Heterogeneity. London: CRC Press; 2005.
2. Tanaka R., Sogo K., Komaguchi K., Ae K., Nakayama Y., Shiono T. Impact of Methylaluminoxane Oxidation on the Ethylene Polymerization Using Ni Catalysts. Organometallics. 2022;41(21):3024–3031. https://doi.org/10.1021/acs.organomet.2c00440
3. Miftakhov E.N., Nasyrov I.S., Mustafina S.A., Zakharov V.P. Study of Kinetics of Isoprene Polymerization in the Presence of Neodymium-Containing Catalytic Systems Modified in Turbulent Flows. Russian Journal of Applied Chemistry. 2021;94(1):77–83. (In Russ.) https://doi.org/10.1134/S1070427221010110
4. Mustafina S., Miftakhov E., Akimov A., Podvalny S., Gabelashvili K. Assessing the Hydrodynamic Effect on the Molecular Parameters of the Isoprene Polymerization Product in the Presence of a Neodymium–Based Catalytic System. ACS Omega. 2022;7(21):17652–17657. https://doi.org/10.1021/acsomega.2c00469
5. Nasyrov I.Sh., Zhavoronkov D.A., Shurupov O.K., Zakharova E.M., Vasiliev V.A., Zakharov V.P. Characteristics of Stereoregular cis-1,4-Polyisoprene Obtained under the Conditions of a Large-Tonnage Production Process on Titanium and Lanthanide Catalysts Modified in Turbulent Flows. Russian Journal of Applied Chemistry. 2021;94(6):741–747. (In Russ.) https://doi.org/10.1134/S1070427221060070
6. Berlin A.A., Patlazhan S.A., Kravchenko I.V., Prochukhan K.Yu., Prochukhan Yu.A. Intensification of Fast Chemical Processes at Interfaces of Two-Component Liquid Media in Tubular Turbulent Reactors. Russian Journal of Physical Chemistry. 2019;38(1):19–26. (In Russ.) https://doi.org/10.1134/S0207401X19010059
7. Roshchin D.E., Patlazhan S.A., Berlin A.A. Free-Radical Polymerization in a Droplet with Initiation at the Interface. European Polymer Journal. 2023;190:112002. https://doi.org/10.1016/j.eurpolymj.2023.112002
8. Mansuri A., Völkel M., Feuerbach T., Winck J., Vermeer A., Hoheisel W., Thommes M. Modified Free Volume Theory for Self-Diffusion of Small Molecules in Amorphous Polymers. Macromolecules. 2023;56(8):3224–3237. (In Russ.) https://doi.org/10.1021/acs.macromol.2c02451
9. Edeleva M., Arraez F., Wu Y., Xie L., Figueira F., Marien Y. [et al.]. Multiscale Theoretical Tools for in Silico Macromolecular Chemistry and Engineering. In: In-Silico Approaches to Macromolecular Chemistry. 2023. p. 17–69. https://doi.org/10.1016/b978-0-323-90995-2.00012-6
10. Tereshchenko K.A., Ulitin N.V., Shiyan D.A., Almetova G.F., Zakharova E.M., Nasyrov I.Sh., [et al.]. Kinetics of Isoprene Polymerization in the Presence of the Catalytic System NdCl3 NCH3CH(OH)CH3-Al(i-C4H9)3-Piperylene. Russian Journal of Physical Chemistry. 2019;13:170–176. (In Russ.) https://doi.org/10.1134/S1990793119010299
11. Minsker K.S., Zakharov V.P., Sadykov I.V., Ionova I.A., Berlin A.A., Monakov Yu.B. Hydrodynamic Effect on the TiCl4-Al(i-C4H9)3 Catalytic System During Isoprene Polymerization. Bulletin of the Bashkir University. 2003;8(3–4):29–31. (In Russ.)
12. Zakharov V.P., Sadykov I.V., Minsker K.S., Berlin A.A., Monakov Yu.B. Molecular Characteristics of cis-1,4-Polyisoprene during the Formation of the TiCl4-Al(i-C4H9)3 Catalytic System in the Turbulent Regime. High Molecular Compounds. Series: B. 2004;46(10):1765–1769. (In Russ.)
13. Usmanov T.S., Yagola A.G., Usmanov S.M., Monakov Y.B. Determination of Catalyst Active Sites Distributions in Ionic Polymerization. Inverse Problems in Science and Engineering. 2005;13:101–107. (In Russ.) https://doi.org/10.1080/10682760410001697822
14. Miftakhov E.N., Mustafina S.A. [Solution of the Inverse Problem of Forming a Molecular Weight Distribution by A.N. Tikhonovʼs Regularization Method: Certificate of State Registration of the Program]. No. 2021618232; dec. 05.11.2021; publ. 25.05.2021. (In Russ.)
15. Miftakhov E.N., Mustafina S.A., Nasyrov I.S., Faizova V.Y. Kinetic Heterogeneity of the Catalytic System Based on Gadolinium Chloride Solvate in 1,4-cis-polyisoprene Production. Russian Journal of Applied Chemistry. 2022;95(3):423–429. (In Russ.) https://doi.org/10.31857/S004446182203010
16. Zakharov V.P., Mingaleev V.Z., Berlin A.A., Nasyrov I.Sh., Zhavoronkov D.A., Zakharova E.M. Kinetic Inhomogeneity of Titanium- and Neodymium-Based Catalysts for the Production of cis-1,4-polyisoprene. Russian Journal of Physical Chemistry. 2015;9:300–305. (In Russ.) https://doi.org/10.7868/S0207401X15030139
17. Bigaeva L.A., Usmanov A.S., Gaisin F.R., Usmanov S.M. Inverse Problem of Molecular Mass Distribution and Analysis of Distribution Functions. Bashkir Chemical Journal. 2014;21(2):65–69. (In Russ.)
18. Ziganshina A., Shiyan D., Ganiev G., Tereshchenko K., Zakharov V., Ulitin N. Controlling the Activity of Particles of TiCl4–Al(i-C4H9)3 Catalytic System by Changing Their Dispersion Composition in the Process of Producing Low-Molar-Mass Polybutadiene – a Component of Sticky Glue. Polymer Science. Series: D. 2020;13:365–371. https://doi.org/10.1134/s199542122004022x
19. Miftakhov E.N., Mustafina S.A., Nasyrov I.Sh., Mustafina S.I. Modified Method for Solving Inverse Problems of the Formation of Molecular Mass Distribution under the Conditions of the Interval Nature of the Initial Experimental Data. Bulletin of the Tver State University. Series: Chemistry. 2022;1(47):102–112. (In Russ., abstract in Eng.) https://doi.org/10.26456/vtchem2022.1.10
20. Miftakhov E., Mustafina S., Nasyrov I., Daminov A. Kinetic Heterogeneity of Polymer Products Obtained in the Presence of Microheterogenic Catalytic Systems Based on Gel Chromatograms. Periódico Tchê Química. 2021;18(38):27–37. https://doi.org/10.52571/PTQ.v18.n38.2021.03_MIFTAKHOV_pgs_27_37.pdf
21. Bigaeva L.A., Latypov I.I., Usmanov S.M., Nabiullin A.R., Shiyan D.A., Ulitin N.V. On the Problem of Solving the Inverse Ill-posed Problem in the Chemical Technology of Polymers: Interpretation of Gel Chromatograms. Bulletin of the Kazan Technological University. 2015;18(3):86–92. (In Russ.)
22. Bello S., Oyedele L., Akinadé O., Bilal M., Davila D., Akanbi L., [et al.]. Cloud Computing in Construction Industry: Use Cases, Benefits and Challenges. Automation in Construction. 2020;122:103441. https://doi.org/10.1016/j.autcon.2020.103441
23. Mustafa C., Zeebaree S. Sufficient Comparison among Cloud Computing Services: IaaS, PaaS, and SaaS: A Review. 2021;5:17–30. http://dx.doi.org/10.5281/zenodo.4481415
24. Gabriel D., Pedro L., Fernanda P., Daniel L., Scheila A. A Survey of Biological Data in a Big Data Perspective. Big Data. 2022;10(4):279–297. https://doi.org/10.1089/big.2020.0383
25. Miftakhov E., Mustafina S., Akimov A., Larin O., Gorlov A. Developing Methods and Algorithms for Cloud Computing Management Systems in Industrial Polymer Synthesis Processes. Emerging Science Journal. 2021;5(6):964–972. https://doi.org/10.28991/esj-2021-01324
26. Daminov A., Miftakhov E., Mustafina S. SaaS is the Service for Solving Problems of Chemical Kinetics. In: 2021 International Conference on Information Technology and Nanotechnology (ITNT). 2021. p. 1–4. https://doi.org/10.1109/ITNT52450.2021.9649017
27. Arantes P., Polêto M., Pedebos C., Ligabue-Braun R. Making it Rain: Cloud-Based Molecular Simulations for Everyone. Journal of Chemical Information and Modeling. 2021;61:4852–4856. https://doi.org/10.26434/chemrxiv-2021-9f2m5
28. Carsten K., Christian K., Austin C., Ludvig N., Helmut G., Bert L., et al. GROMACS in the Cloud: A Global Supercomputer to Speed Up Alchemical Drug Design. Journal of Chemical Information and Modeling. 2022;62(7):1691–1711. https://doi.org/10.1021/acs.jcim.2c00044
This work is licensed under a Creative Commons Attribution 4.0 License.
