D. Tregubov, L. Trefilova, N. Minska, Yu. Hapon, D. Sokolov. Nonlinearities correlation of n-alkanes and n-alcohols physicochemical properties. Р. 4-24.

 

 Nonlinearities correlation of n-alkanes and n-alcohols physicochemical properties

 

Tregubov Dmytro

National University of Civil Defence of Ukraine

https://orcid.org/0000-0003-1821-822X

 

Trefilova Larisa

National University of Civil Defence of Ukraine

http://orcid.org/0000-0001-9061-4206

 

Minska Natalya

National University of Civil Defence of Ukraine

http://orcid.org/0000-0001-8438-0618

 

Hapon Yuliana

National University of Civil Defence of Ukraine

http://orcid.org/0000-0002-3304-5657

 

Sokolov Dmitry

National University of Civil Defence of Ukraine

http://orcid.org/0000-0002-7772-6577

 

DOI: https://doi.org/10.52363/2524-0226-2024-39-1

 

Keywords: n-alcohols, n-alkanes, physicochemical properties, cluster, model, nonlinearity, calculation convergence

 

Аnnotation

 

Correspondences between the changes nonlinearity in substance physico-chemical parameters and the influence mechanisms on them by the substance supramolecular structure in the calculated dependencies form for n-alkanes and n-alcohols was established. Similarity, change features and correlation between such parameters as melting point, boiling point, flash point, self-ignition, density, solubility in water, viscosity, vaporization heat, surface tension were investigated. The paper obtained 14 calculated dependencies that calculate these parameters on the established similarity basis between them and the lengths of the molecule or cluster with sufficient correlation coefficients. For viscosity, vaporization heat and surface tension, change general dependences are established, but without taking into account oscillatory deviations. Calculated dependences between substance characteristic temperatures were obtained: melting temperatures of alkanes and alcohols, boiling and flash temperatures in homologous series, autoignition and melting temperatures (flash, boiling). This correlation is explained by the fact that supramolecular structures are formed according to a similar principle in matter different states and during the combustion initiation. Such structures modeling for the solid, liquid state, and solubility in water was carried out, taking into account different coordination numbers, globulation, and changes in the clustering place according to the molecule length. On the such modeling basis and the "melting ease" indicator, dependencies have been developed for calculation with the dependencies nonlinearities reflection of alkanes and alcohols density and melting temperature. For the boiling and flash point, vaporization heat of alcohols, the deviation from linearity is taken into account by the cluster length reduction parameter. It is shown that the considered dependencies modulation by the cluster length allows to describe their anomalies and increases the calculation convergence.

 

References

 

  1. Tregubov, D., Trefilova, L., Slepuzhnikov, E., Sokolov, D., Trehubova, F. (2023). Correlation of properties in hydrocarbons homologous series. Problems of Emergency Situations, 2(38), 96–118. doi: 10.52363/2524-0226-2023-38-7
  2. Tregubov, D., Tarakhno, O., Deineka, V., Trehubova, F. (2022). Oscillation and Stepwise of Hydrocarbon Melting Temperatures as a Marker of their Cluster Structure. Solid State Phenomena, 334, 124–130. doi: 10.4028/p-3751s3
  3. Jovanović, J., Grozdanić, D. (2010). Reliable prediction of heat of vaporization of n-alkanes at 298.15 K. Journal of the Serbian Chemical Society. J. Serb. Chem. Soc., 75(7), 997–1003. doi: 10.2298/JSC091123067J
  4. Santos, R., Leal, J. (2012). A Review on Prediction Methods for Molar Enthalpies of Vaporization of Hydrocarbons: The ELBA Method as the Best Answer. J. of Physical and Chemical Reference Data, 41, 043101. doi: 10.1063/1.4754596
  5. Wan,, Song, J., Yang, Y., Gao, L., Fanga, W. (2021). Development of coarse-grained force field for alcohols: an efficient meta-multilinear interpolation parameterization algorithm. Physical Chemistry Chemical Physics, 23, 1956–1966. doi: 10.1039/d0cp05503d
  6. Yaxin, A., Karteek, K. B., Sanket, A. D. (2018). Development of New Transferable Coarse-Grained Models of Hydrocarbons. J. Phys. Chem., 122, 28, 7143–7153. doi: 10.1021/acs.jpcb.8b03822
  7. Dai, L., Chakraborty, S., Wu, G., Ye, J, La, Y., Ramanarayan, H. (2022). Molecular simulation of linear octacosane via a CG10 coarse grain scheme. Physical Chemistry Chemical Physics, 24(9), 5351–5359. doi: 1039/D1CP05143A
  8. Song, J., Wan, M., Yang, Y., Gao, L., Fang, W. (2021). Development of accurate coarse-grained force fields for weakly polar groups by an indirect parameterization strategy. Physical Chemistry Chemical Physics, 23(11), 6763–6774. doi: 10.1039/D1CP00032B
  9. Conway, O., An, Y., Bejagam, K. K., Deshmukh, S. A. (2020). Development of transferable coarse-grained models of amino acids. Mol. Syst. Des. Eng., 5, 675. doi: 10.1039/C9ME00173E
  10. Pervaje, A. K., Walker, Ch. C., Santiso, E. E. (2019). Molecular simulation of polymers with a SAFT-γ Mie approach. Molecular Simulation, 45(14–15), 1223–1241. doi: 10.1080/08927022.2019.1645331
  11. Laguna, (2008). Modern Supramolecular Gold Chemistry: Gold-Metal Interactions and Applications. Weinheim: Wiley-VCH. doi: 10.1002/9783527623778
  12. Kahwaji, S., White, M. (2021). Organic Phase Change Materials for Thermal Energy Storage: Influence of Molecular Structure on Properties. Molecules, 26, 6635. doi: 10.3390/molecules26216635
  13. Doroshenko, I. Yu. (2017). Spectroscopic study of cluster structure of n-hexanol trapped in an argon matrix. Low Temperature Physics, 3(6), 919–926. doi: 1063/1.4985983
  14. Millet, D. B. et al. (2015). Sources and sinks of atmospheric formic acid. Atmos. Chem. Phys, 15, 6283–6304. doi: 10.5194/acp-15-6283-2015
  15. Tregubov, D., Sharshanov, A., Sokolov, D., Tregubova, F. (2022). Forecasting the smallest super molecular formations for alkanes of normal and isomeric structure. Problems of Emergency Situations, 35, 63–75. doi: 10.52363/2524-0226-2022-35-5
  16. Tregubov, D., Tarahno, O., Kireev, О. (2018). Influence of cluster structure of liquids technical mixtures on the value of characteristic temperatures. Problems of Emergency Situations, 2(28), 99–110. doi: 10.5281/zenodo.2598054
  17. Boot, M., Tian, M., Hensen, E., Mani, S. (2017). Impact of fuel molecular structure on autoignition behavior: design rules for future high performance gasolines. Progress in Energy and Combustion Science, 60, 1–25. doi: 10.1016/j.pecs.2016.12.001
  18. Tarakhno, O. V., Trehubov, D. H., Zhernoklʹov, K. V., Kovrehin, V. V. (2020). Osnovni polozhennya protsesu horinnya. Kharkiv: NUTSZ Ukrayiny, Retrieved from: http://repositsc.nuczu.edu.ua/handle/123456789/11382
  19. Tregubov,, Slepuzhnikov, E., Chyrkina, M., Maiboroda, A. (2023). Cluster Mechanism of the Explosive Processes Initiation in the Matter. Key Engineering Materials, 952, 131–142. doi: 10.4028/p-u0fBZB
  20. Search for Species Data by Chemical Name. NIST Chemistry WebBook. U. Department of Commerce. doi: https://doi.org/10.18434/T4D303
  21. Quickly find chemical information from authoritative sources. Pubchem. U. National Library of Medicine. Retrieved from: https://pubchem.ncbi.nlm.nih.gov/
  22. Reichel, M., Krumm, B., Vishnevskiy, Yu., Blomeyer, S., Schwabedissen, J., Stammler, H.-G., Karaghiosoff, K. (2019). Solid-State and Gas-Phase Structures and Energetic Properties of Dangerous Methyl and Fluoromethyl Nitrates. Angewandte Chemie International Edition, 58(51), 18557–18561. doi: 10.1002/anie.201911300
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