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Correlation between the Onset Temperature and Molecular Descriptors of Organic Peroxides

  • CHEMOINFORMATICS AND COMPUTER MODELING
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Abstract

QSPR modeling has been performed on 38 organic peroxides against onset temperature. The molecular structures were optimized and frequencies were computed with DFT/b3lyp and 6-311g(d,p) basis set. Avogadro 1.2 was used to Convert gaussian output files to MDL SDFile format. 5666 molecular descriptors were calculated by Alvadesc software based on MDL SDfiles. The data set is randomly divided into training and test sets, and the number of samples contained in the training and test sets are 30 and 8, respectively. A seven-parameter relationship was established by the stepwise multiple linear regression method. The correlation coefficient reaches 0.9843, and the RMSE for the training and test sets are 5.47 and 5.57, respectively. Student t-value, VIF value and Durbin–Watson value indicate that all the independent variables have significant impact on dependent variable, and there is no multicollinearity between independent variables and no correlation between the residuals, respectively. LOOCV, LMOCV, external validation, Application domain analysis show that the resulting QSPR model is robust and reliable and can be used to predict the thermal decomposition temperature of organic peroxides.

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REFERENCES

  1. Y. Dai, L. Niu, J. Zou, et al., J. Centr. South Univ. 25, 1535 (2018).

    Article  CAS  Google Scholar 

  2. Y. Lu, D. Ng, and M. S. Mannan, Ind. Eng. Chem. Res. 50, 1515 (2011).

    Article  CAS  Google Scholar 

  3. V. Prana, P. Rotureau, G. Fayet, et al., J. Hazard. Mater. 276, 216 (2014).

    Article  CAS  PubMed  Google Scholar 

  4. R. H. Chang, J. M. Tseng, J. M. Jehng, et al., J. Therm. Anal. Calorim. 83, 57 (2006).

    Article  CAS  Google Scholar 

  5. L. C. Tsai, M. L. You, M. F. Ding, et al., Molecules 17, 8056 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. J. Lv, W. Chen, L. Chen, et al., Thermochim. Acta 589, 11 (2014).

    Article  CAS  Google Scholar 

  7. Y. Zhang, Y. Pan, J. Jiang, et al., J. Environ. Chem. Eng. 2, 868 (2014).

    Article  CAS  Google Scholar 

  8. Q. Wang, L. Wang, X. Zhang, and Z. Mi, J. Hazard. Mater. 172, 1659 (2009).

    Article  CAS  PubMed  Google Scholar 

  9. J. Lv, L. Chen, W. Chen, H. Gao, and M. Peng, Thermochim. Acta 571, 60 (2013).

    Article  CAS  Google Scholar 

  10. P. Y. Yeh, C. M. Shu, and Y. S. Duh, Ind. Eng. Chem. Res. 42, 1 (2002).

    Article  Google Scholar 

  11. M. Malow and K. D. Wehrstedt, J. Hazard. Mater. 120, 21 (2005).

    Article  CAS  PubMed  Google Scholar 

  12. T. A. Albahri, Chem. Eng. Sci. 58, 3629 (2003).

    Article  CAS  Google Scholar 

  13. N. Zohari, M. H. Keshavarz, and Z. Dalaei, J. Therm. Anal. Calorim. 125, 887 (2016).

    Article  CAS  Google Scholar 

  14. R. Huoyu, Z. Zhiqiang, L. Zhanggao, et al., Int. J. Quantum Chem. 122, e26950 (2022).

  15. M. Y. Dolomatov, T. M. Aubekerov, O. S. Koledin, K. R. Akhtyamova, E. V. Vagapova, and E. A. Kovaleva, Russ. J. Phys. Chem. A 93, 2388 (2019).

    Article  CAS  Google Scholar 

  16. R. Huoyu, Z. Zhiqiang, J. Guofang, et al., Russ. J. Phys. Chem. A 96, 2329 (2022).

    Article  Google Scholar 

  17. M. Y. Dolomatov, E. A. Kovaleva, N. S. Valeeva, and N. Kh. Paimurzina, Russ. J. Phys. Chem. A 94, 2189 (2020).

    Article  CAS  Google Scholar 

  18. K. Lakzian, S. Hosseiniallahchal, H. J. Salmani, et al., Thermochim. Acta 691, 178719 (2020).

  19. E. Torabian and M. A. Sobati, Thermochim. Acta 672, 162 (2019).

    Article  CAS  Google Scholar 

  20. B. Wang, H. Yi, K. Xu, et al., J. Therm. Anal. Calorim. 128, 399 (2017).

    Article  CAS  Google Scholar 

  21. Y. Gao, Y. Xue, Z. Lü, et al., Process. Safety Environ. Protect. 94, 322 (2015)

    Article  CAS  Google Scholar 

  22. P. He, Y. Pan, and J. Jiang, Proc. Eng. 211, 215 (2018).

    Article  CAS  Google Scholar 

  23. W. Li, G. Song, J. Zhang, et al., Comput. Theor. Chem. 1202, 113324 (2021)

  24. Ö. Ç. Havare, Int. J. Quantum Chem. 121, e26813 (2021).

  25. A. Mauri, in Ecotoxicological QSARs, Ed. by K. Roy (Springer, 2020), p. 801. https://doi.org/10.1007/978-1-0716-0150-1_32

    Book  Google Scholar 

  26. S. Saaidpour, Phys. Chem. Res. 4, 61 (2016).

    Google Scholar 

  27. K. Roy, S. Kar, and R. N. Das, in Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk Assessment (Academic, Boston, 2015), Chap. 7, p. 231.

    Google Scholar 

  28. ENV/JM/MONO(2007)2, OECD Environment Health and Safety Publ., Ser. on Testing and Assessment, No. 69 (OECD,Paris, 2007).

    Google Scholar 

  29. K. Roy, I. Mitra, S. Kar, P. K. Ojha, R. N. Das, and H. Kabir, J. Chem. Inform. Model. 52, 396 (2012). https://doi.org/10.1021/ci200520g

    Article  CAS  Google Scholar 

  30. Sh. Shen, Y. Pan, X. Ji, Yu. Ni, and Ju. Jiang, Int. J. Mol. Sci. 20, 2084 (2019). https://doi.org/10.3390/ijms20092084

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. R. K. Mukherjee, V. Kumar, and K. Roy, Environ. Sci. Technol. 56, 335 (2021).

    Article  PubMed  Google Scholar 

  32. K. Roy and R. N. Das, in Pharmaceutical Sciences: Breakthroughs in Research and Practice (IGI Global, 2017), p. 978.

    Google Scholar 

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Authors and Affiliations

  1. Department of Applied Chemistry, East China University of Technology, 330013, NanChang, JiangXi, China

    Liao Yuting, Jia Fangrui, Rao Huoyu, Le Zhanggao & Xu Zhenzhen

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  1. Liao Yuting
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  2. Jia Fangrui
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  3. Rao Huoyu
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  5. Xu Zhenzhen
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Correspondence to Rao Huoyu.

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Yuting, L., Fangrui, J., Huoyu, R. et al. Correlation between the Onset Temperature and Molecular Descriptors of Organic Peroxides. Russ. J. Phys. Chem. 97, 2550–2558 (2023). https://doi.org/10.1134/S0036024423110195

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  • DOI: https://doi.org/10.1134/S0036024423110195

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