(56e) New Insights On Mechanisms of Backbiting and ?-Scission Reactions in Self-Initiated Polymerization of Methyl Acrylate

At high temperature, secondary reactions such as spontaneous thermal initiation, chain transfer reactions and β-scission reactions can significantly influence the polymerization process and the properties of the formed polymer [1-4]. The backbiting (intra-molecular chain transfer) and β-scission reactions have been studied extensively via various experimental techniques [5-8]. However, first-principles studies of these polymerization reactions have been hindered due to the large computational costs required for modeling polymeric systems of large size.  Density functional theory (DFT) is generally regarded as a cost-effective method [9-14]. The accuracy of DFT depends on the approximation of the exchange-correlation function, and there is no obvious way to decide which density functional is the best for studying a given type of chemical reaction.

In this work, we firstly carry out a benchmark study using G4(MP2)-6X, a composite quantum chemistry method,[15] to predict the thermochemical properties of two representative 1:5 backbiting reactions. We then apply three different functionals (B3LYP, M06-2X and PBE0) and wavefunction-based method, MP2 to identify the mechanisms governing backbiting and β-scission reactions and the species generated by these reactions in high-temperature self-initiated homo-polymerization of methyl acrylate.  Both hindered rotor approximations [16] and harmonic approximations are applied for the estimation of activation entropy.  Four mechanisms of backbiting reactions and two types of β-scission reactions are studied. Our computational results show that the 1:5 backbiting mechanism with a six-membered ring transition state and 1:7 backbiting with an eight-membered ring transition state are energetically more favored than 1:3 backbiting and 1:9 backbiting. Two types of β-scission reactions have nearly equal activation energy and rate constants. The ¹³C-NMR and ¹H-NMR spectrums are simulated and compared with experimental results in order to validate the proposed mechanisms. 

References

[1]      Grady, M. C.; Simonsick, W. J.; Hutchinson, R. A. Macromol. Symp. 2002, 182, 149.

[2]      Quan, C. L.; Soroush, M.; Grady, M. C.; Hansen, J. E.; Simonsick, W. J. Macromolecules 2005, 38, 7619.

[3]      Chiefari, J.; Jeffery, J.; Mayadunne, R. T. A.; Moad, G.; Rizzardo, E.; Thang, S. H. Macromolecules 1999, 32, 7700.

[4]      Zorn, A. M.; Junkers, T.; Barner-Kowollik, C. Macromol. Rapid Commun. 2009, 30, 2028.

[5]      Junkers, T.; Bennet, F.; Koo, S. P. S.; Barner-Kowollik, C. Journal of Polymer Science Part a-Polymer Chemistry 2008, 46, 3433.

[6]      Yamada, B.; Oku, F.; Harada, T. Journal of Polymer Science Part a-Polymer Chemistry 2003, 41, 645.

[7]      Asua, J. M.; Beuermann, S.; Buback, M.; Castignolles, P.; Charleux, B.; Gilbert, R. G.; Hutchinson, R. A.; Leiza, J. R.; Nikitin, A. N.; Vairon, J. P.; van Herk, A. M. Macromol. Chem. Phys. 2004, 205, 2151.

[8]      Wang, W.; Hutchinson, R. A. Chemical Engineering & Technology 2010, 33, 1745.

[9]      Degirmenci, I.; Aviyente, V.; Van Speybroeck, V.; Waroquier, M. Macromolecules 2009, 42, 3033.

[10]   Van Speybroeck, V.; Van Cauter, K.; Coussens, B.; Waroquier, M. ChemPhysChem 2005, 6, 180.

[11]   Furuncuoglu, T.; Ugur, I.; Degirmenci, I.; Aviyente, V. Macromolecules 2010, 43, 1823.

[12]   Srinivasan, S.; Lee, M. W.; Grady, M. C.; Soroush, M.; Rappe, A. M. J. Phys. Chem. A 2010, 114, 7975.

[13]   Liu, S.; Srinivasan, S.; Grady, M. C.; Soroush, M.; Rappe, A. M. J. Phys. Chem. A 2012, 116, 5337.

[14]   Moghadam, N.; Liu, S.; Srinivasan, S.; Grady, M. C.; Soroush, M.; Rappe, A. M.  J. Phys. Chem. A 2013, 117, 2605.

[15]   B. Chan, J. Deng, L. Radom J. Chem. Theory Comput., 7, 112-120 (2011).

[16]   Yu, X. R.; Pfaendtner, J.; Broadbelt, L. J. J. Phys. Chem. A 2008, 112, 6772.