New structure-based models using mixture descriptors to predict the flammabiliy temperature of binary organic mixtures

Subject Areas : Modeling

Zohreh Faramarzi ¹ , Fatemeh Abbasitabar ^{2 *} , Vahid Zare-Shahabadi ³

1 - Institute of Mining, Oil and Energy, Mahs.C., Islamic Azad University, Mahshahr, Iran.
2 - Department of Chemistry, Marv. C., Islamic Azad University, Marvdasht, Iran.
3 - Institute of Mining, Oil and Energy, Mahs.C., Islamic Azad University, Mahshahr, Iran.

Received: 2025-07-08 Accepted : 2025-08-14 Published : 2025-09-14

Keywords: QSPR, Flammability point, Memorized-Ant Colony optimization, Mixture descriptors, Multiple linear regression.,

Abstract :

Due to the importance of binary mixtures and their wide application in industry, it is important to estimate their flammability temperature. Therefore, in this study, quantitative structure-property relationship(QSPR) models were developed to predict the flammability point of binary organic mixtures. The biggest challenge in QSPR studies of mixtures is the calculation of a numerical descriptor to describe the property of a mixture. In this study, a set of twenty-two formulas was used to calculate mixture descriptors from molecular descriptors of pure compounds. Memorized Ant Colony(Memorized-ACO) Algorithm along with multivariate linear regression(MLR) was used to select the best subset of descriptors that have a significant contribution to the flammability property. The model based on sqr−fmol−sum descriptor was selected as the best model. R² _training and R²_test of this model were 0.93 and 0.94, respectively. The mean absolute error(MAE) for the training and test datasets was 3.75 and 2.97, respectively. A group model was also obtained through a simple averaging strategy using the models generated by the best descriptors. This improved the statistical quality of the final QSPR model.

References:

1. L. O. Chemicals. Globally harmonized system of classification and labelling of chemicals (GHS); 10th revised ed (United Nations, 2023).
2. D. A. Crowl, J. F. Louvar. Chemical process safety: fundamentals with applications; 4th ed (Pearson Education, 2019).
3. J. A. Dean, N. A. Lange. Lange's handbook of chemistry; 5th ed (McGraw-Hill, 1999).
4. H. J. Liaw, S. C. Lin. J. Hazard. Mater. 140, 155 (2007).
5. H. J. Liaw, T. P. Lee, J. S. Tsai, W. H. Hsiao, M. H. Chen, T. T. Hsu. J. Loss Prev. Process Ind. 16, 173 (2003).
6. L. Catoire, S. Paulmier, V. Naudet. Process Saf. Prog. 25, 33 (2006).
7. E. Torabian, M. A. Sobati. Thermochim. Acta 672, 162 (2019).
8. Y. Pan, J. Cheng, X. Song, G. Li, L. Ding, J. Jiang. J. Loss Prev. Process Ind. 34, 56 (2015).
9. H. J. Liaw, T. P. Tsai. Fluid Phase Equilib. 345, 45 (2013).
10. H. J. Liaw, H. Y. Chen. Industrial & Engineering Chemistry Research 52, 7579 (2013).
11. H. J. Liaw, C. L. Tang, J. S. Lai. Comb. Flame. 138, 308 (2004).
12. B. Nazari, M. H. Keshavarz, A. Hassanzadeh. Process Saf. Environ. Prot. 132, 134 (2019).
13. F. A. Carroll, C. Y. Lin, F. H. Quina. Industrial & Engineering Chemistry Research 50, 4796 (2011).
14. X. Liu, Z. Liu. Journal of Chemical & Engineering Data 55, 2943 (2010).
15. G. Fayet, P. Rotureau, V. Prana, C. Adamo. In 14. International Symposium on Loss Prevention and Safety Promotion in the Process Industry, 31, 925 (2013).
16. L. Jiao, X. Zhang, Y. Qin, X. Wang, H. Li. Chemometr. Intell. Lab. Syst. 156, 211 (2016).
17. H. J. Liaw, Y. Y. Chiu. J. Hazard. Mater. 101, 83 (2003).
18. Z. Faramarzi, F. Abbasitabar, V. Zare-Shahabadi, H. J. Jahromi. J. Mol. Liq. 296, 111854 (2019).
19. W. A. Affens, G. W. McLaren. J. Chem. Eng. Data 17, 482 (1972).
20. T. Gaudin, P. Rotureau, G. Fayet. Fire Saf. J. 74, 61 (2015).
21. M. Vidal, W. Rogers, M. Mannan. Process Saf. Environ. Prot. 84, 1 (2006).
22. T. Gaudin, P. Rotureau, G. Fayet. Industrial & Engineering Chemistry Research 54, 6596 (2015).
23. D. Wu, R. Finkelman. In Abstracts of Papers of the American Chemical Society, 175, 12 (1978).
24. H. J. Liaw, W. H. Lu, V. Gerbaud, C. C. Chen. J. Hazard. Mater. 153, 1165 (2008).
25. H. J. Liaw, V. Gerbaud, Y. H. Li. Fluid Phase Equilib. 300, 70 (2011).
26. H. J. Liaw, V. Gerbaud, H. T. Wu. J. Chem. Eng. Data 55, 3451 (2010).
27. H. J. Liaw, V. Gerbaud, C. Y. Chiu. J. Chem. Eng. Data 55, 134 (2010).
28. M. Mitu, E. Brandes, D. Pawel. Rev. Chim. 57, 770 (2006).
29. M. Noorollahy, A. Z. Moghadam, A. A. Ghasrodashti. Chem. Eng. Res. Des. 88, 81 (2010).
30. D.-M. Ha, S. Lee. Korean J. Chem. Eng. 28, 1161 (2011).
31. A. Z. Moghaddam, A. Rafiei, T. Khalili. Fluid Phase Equilib. 316, 117 (2012).
32. A. Donaldson, S. Al-Sharafi. Eng. J. Qatar Univ. 7, 27 (1994).
33. M. Hristova. Cent. Eur. J. Chem. 11, 57 (2013).
34. M. Hristova, D. Damgaliev. Cent. Eur. J. Chem. 11, 388 (2013).
35. Ultra, ChemDraw; Cambridge soft corporation, Cambridge, USA: 2001. 36. Koala-Software for kohonen artificial neural networks; Milano chemometrics and QSAR research group: 2007.
37. E. N. Muratov, E. V. Varlamova, A. G. Artemenko, P. G. Polishchuk, V. E. Kuz'min. Mol. Inform. 31, 202 (2012).
38. T. Gaudin, P. Rotureau, G. Fayet. Ind. Eng. Chem. Res. 54, 6596 (2015).
39. S. Khorsand Ahmadi, M. Mahmoodian Moghadam, P. Mokaberi, M. Reza Saberi, J. Chamani. J. Biomol. Struct. Dyn. 33, 1880 (2015).
40. M. Shamsipur, V. Zare-Shahabadi, B. Hemmateenejad, M. Akhond. Anal. Chim. Acta 646, 39 (2009).
41. F. Abbasitabar, V. Zare-Shahabadi. SAR QSAR Environ. Res. 23, 1 (2012).
42. V. Zare‐shahabadi, F. Abbasitabar. J. Comput. Chem. 31, 2354 (2010).
43. M. Jalali-Heravi, H. Ebrahimi-Najafabadi, A. Khodabandehloo. QSAR Comb. Sci. 28, 1432 (2009).
44. F. Abbasitabar, V. Zare-Shahabadi. Chemosphere 172, 249 (2017).
45. V. Zare-Shahabadi. Med. Chem. Res. 25, 2787 (2016).
46. D. Baumann, K. Baumann. J. Cheminform. 6, 47 (2014).
47. D. Massart, B. Vandeginste, L. Buydens, S. de Jong. Handb. Chemom. Qualimetr., 379 (1997).
48. K. Roy, S. Kar, P. J. C. Ambure, I. L. Systems. 145, 22 (2015).
49. V. Zare-Shahabadi, F. Abbasitabar, M. Akhond, M. Shamsipour. J. Braz. Chem. Soc. 24, 1561 (2013).
39. S. Khorsand Ahmadi, M. Mahmoodian Moghadam, P. Mokaberi, M. Reza Saberi, J. Chamani. J. Biomol. Struct. Dyn. 33, 1880 (2015).
40. M. Shamsipur, V. Zare-Shahabadi, B. Hemmateenejad, M. Akhond. Anal. Chim. Acta 646, 39 (2009).
41. F. Abbasitabar, V. Zare-Shahabadi. SAR QSAR Environ. Res. 23, 1 (2012).
42. V. Zare‐shahabadi, F. Abbasitabar. J. Comput. Chem. 31, 2354 (2010).
43. M. Jalali-Heravi, H. Ebrahimi-Najafabadi, A. Khodabandehloo. QSAR Comb. Sci. 28, 1432 (2009).
44. F. Abbasitabar, V. Zare-Shahabadi. Chemosphere 172, 249 (2017).
45. V. Zare-Shahabadi. Med. Chem. Res. 25, 2787 (2016).
46. D. Baumann, K. Baumann. J. Cheminform. 6, 47 (2014).
47. D. Massart, B. Vandeginste, L. Buydens, S. de Jong. Handb. Chemom. Qualimetr., 379 (1997).
48. K. Roy, S. Kar, P. J. C. Ambure, I. L. Systems. 145, 22 (2015).
49. V. Zare-Shahabadi, F. Abbasitabar, M. Akhond, M. Shamsipour. J. Braz. Chem. Soc. 24, 1561 (2013).