STUDY AND MODELING 4,4'-DIAMINODIPHENYLMETHANE SYNTHESIS

  • Natalia V. Menshutina Mendeleev University of Chemical Technology of Russia
  • Igor V. Lebedev Mendeleev University of Chemical Technology of Russia
  • Evgeniy A. Lebedev Mendeleev University of Chemical Technology of Russia
  • Ratmir R. Dashkin Mendeleev University of Chemical Technology of Russia
  • Mikhail V. Shishanov Mendeleev University of Chemical Technology of Russia
  • Maxim L. Burdeyniy Mendeleev University of Chemical Technology of Russia
Keywords: catalytic reactions, modelling, cellular automata, porous structure

Abstract

The presented work is devoted to reactions of obtaining 4,4´-diaminodiphenylmethane in the presence of a catalyst. The work describes the importance of studying 4,4´-diaminodiphenylmethane obtaining process and possibility of cellular automata approach in modelling chemical reactions. Cellular automata model which allows to predict the kinetic curves of the studied 4,4´-diaminodiphenylmethane-obtaining reaction. Model reflects two processes that are observed in the system under study - the movement of reagents under the stirring and the reaction in the presence of a catalyst. The suggested model does not use complex calculations for operation and can be implemented using high-performance parallel computing, which will speed up calculations and reduce the requirements for computing resources. The developed model was used to carry out computational experiments under various conditions. Since the model contains a number of empirical parameters, first computational experiments were carried out, which made it possible to establish the relationship between the model parameters and real values. Then, computational experiments were carried out to predict the kinetic curves of the studied reactions and were compared with the corresponding experimental data. The suggested model is suitable for predicting 4,4´-diaminodiphenylmethane-obtaining reaction kinetics. Also, model can be the part of complex multiscale modeling from the molecule level to the level of the entire apparatus.

References

Allport D.C., Gilbert D.S., Outterside S.M. MDI, TDI and the Polyurethane Industry. MDI and TDI: Safety, Health and the Environment: A Source Book and Practical Guide. Chichester: Wiley. 2003. 460 p. DOI: 10.1002/0470865687.

Keller T. C., Arras J. R., Wershofen S., Perez-Ramirez J. Design of hierarchical zeolite catalysts for the manufac-ture of polyurethane intermediates. ACS Catalysis. 2014. V. 5. N 2. P. 734-743. DOI: 10.1021/cs5017694.

Tian J., An H., Cheng X., Zhao X., Wang Y. Synthesis of 4, 4′-methylenedianiline catalyzed by SO3H-functionalized ionic liquids. Indust. & Eng. Chem. Res. 2015. V. 54. N 31. P. 7571-7579. DOI: 10.1021/acs.iecr.5b01519.

Menshutina N.V., Kolnoochenko A.V., Lebedev E.A. Cellular Automata in Chemistry and Chemical Engineer-ing. Ann. Rev. Chem. Biomolec. Eng. 2020. V. 11. P. 87-108. DOI: 10.1146/annurev-chembioeng-093019-075250.

Sun B., Fan W., Chakraborty A. Adsorption kinetics emulation with lattice gas cellular automata. Heat Transfer Eng. 2017. V. 38. N 4. P. 409-416. DOI: 10.1080/01457632.2016.1194705.

Hallberg H. Approaches to Modeling of Recrystallization. Metals. 2011. V. 1. N 1. P. 16-48. DOI: 10.3390/met1010016.

Brouwers H.J.H., de Korte A.C.J. Multi-cycle and multi-scale cellular automata for hydration simulation (of Port-land-cement). Comput. Mater. Sci. 2016. V. 111. P. 116-124. DOI: 10.1016/j.commatsci.2015.08.049.

Hoekstra A.G., Kroc J., Sloot P.M.A. Cellular Automata Composition Techniques for Spatial Dynamics Simulation. Berlin: Springer. 2010. 384 p.

Kier L.B., Seybold P.G., Cheng C.K. Cellular Automata Modeling of Chemical Systems. Dordrecht, Amsterdam: Springer. 2005. 175 p.

Campiñez M.D., Caraballo I., Puchkov M., Kuentz M. Novel Polyurethane Matrix Systems Reveal a Particular Sustained Release Behavior Studied by Imaging and Computational Modeling. AAPS PharmSciTech. 2016. V. 18. N 5. P. 1544-1553. DOI: 10.1208/s12249-016-0613-0.

Mitrofanov I., Malysheva I., Kolnoochenko A., Menshutina N. Modelling of Aerogels Structures Using Intelli-gent System «AeroGen Structure». Comp. Aid. Chem. Eng. 2017. V. 40. P. 469-474. DOI: 10.1016/B978-0-444-63965-3.50080-5.

Vertyagina Y., Marrow T.J. 3D Cellular Automata fracture model for porous graphite microstructures. Nucl. Eng. Des. 2017. V. 323. P. 202-208. DOI: 10.1016/j.nucengdes.2016.10.015.

Vertyagina Y., Marrow T.J. A multi-scale three-dimensional Cellular Automata fracture model of radiolytically oxidised nuclear graphite. Carbon. 2017. V. 121. P. 574-590. DOI: 10.1016/j.carbon.2017.06.031.

Kireeva A. Twolayer CA for simulation of catalytic reaction at dynamically varying surface temperature. J. Comput. Sci. 2015. V. 11. P. 317-325. DOI: 10.1016/j.jocs.2015.06.001.

Markova V.P., Sharifulina A.E. Parallel implementation of an asynchronous cellular automaton simulating the reaction of CO oxidation on palladium. Priklad. Diskret. Matem. 2011. N 1. P. 116-126 (in Russian). DOI: 10.17223/20710410/11/8.

Scalise D., Schulman R. Emulating cellular automata in chemical reaction–diffusion networks. Nat. Comput. 2016. V. 15. N 2. P. 197-214. DOI: 10.1007/s11047-015-9503-8.

Svyetlichnyy D.S. Modelling of the microstructure: from classical cellular automata approach to the frontal one. Computat. Mater. sci. 2010. V. 50. N 1. P. 92-97. DOI: 10.1016/j.commatsci.2010.07.011.

Meakin P. Formation of fractal clusters and networks by irreversible diffusion-limited aggregation. Phys. Rev. Lett. 1983. V. 51. N 13. P. 1119. DOI: 10.1103/PhysRevLett.51.1119.

Menshutina N.V., Kolnoochenko A.V., Katalevich A.M. Structure analysis and modeling of inorganic aerogels. Theor. Found. Chem. eng. 2014. V 48. N 3. P. 344-348. DOI: 10.1134/S0040579514030117.

Van der Weeën P., Zimer A.M., Pereira E.C., Mascaro L.H., Bruno O.M., De Baets B. Modeling pitting corro-sion by means of a 3D discrete stochastic model. Corros. Sci. 2014. V. 82. P. 133–144. DOI: 10.1016/j.corsci.2014.01.010.

Published
2021-04-11
How to Cite
Menshutina, N. V., Lebedev, I. V., Lebedev, E. A., Dashkin, R. R., Shishanov, M. V., & Burdeyniy, M. L. (2021). STUDY AND MODELING 4,4’-DIAMINODIPHENYLMETHANE SYNTHESIS. ChemChemTech, 64(4), 100-103. https://doi.org/10.6060/ivkkt.20216404.6314
Section
CHEMICAL TECHNOLOGY (inorganic and organic substances. Theoretical fundamentals)

Most read articles by the same author(s)