(618j) A Combined Computational and Experimental Study of Copolymerization Kinetics for Glycidyl Methacrylate and Tert-Butyl Methacrylate | AIChE

(618j) A Combined Computational and Experimental Study of Copolymerization Kinetics for Glycidyl Methacrylate and Tert-Butyl Methacrylate

Authors 

Yu, Y. - Presenter, Northwestern University
Bavarian, M., Drexel University
Pu, Q., Vanderbilt University
Schultz, A., Virginia Tech
Long, T. E., Virginia Tech
Methacrylate families are widely used to prepare photoresists in the semiconductor industry.1 Numerous possible methacrylate polymerization recipes can be formulated to design products with desired properties including molecular weight, molecular weight distribution, and copolymer composition. Demand is growing to develop computational methods that improve the copolymerization product design and help with the product scale-up.2,3 While the reaction kinetics of simple monomers such as methyl methacrylate (MMA) have been studied extensively,3-11 more complex methacrylate monomers have been overlooked. In this work, a combined computational and experimental study on copolymerization kinetics of glycidyl methacrylate (GMA) and tert-butyl methacrylate (tBMA) was conducted to investigate the polymerization propagation kinetics. Density functional theory (DFT) was used to investigate the propagation kinetics and to calculate monomer reactivity ratios. A benchmark test of DFT methods was carried out on GMA self-propagation rate coefficients with experimental support.12 To improve the accuracy in thermochemical calculations, two tiers of treatment of vibrational frequencies were applied and compared, including a harmonic oscillator (HO) model13 and a one-dimensional hindered rotor (1D-HR) model14-18 with scale factors. Our results showed that the 1D-HR model generated a more accurate estimate of pre-exponential factors, rate constants, and reactivity ratios than the HO model. The calculated reactivity ratios and rate constants were then used in a polymerization kinetic model to predict the polymerization reaction rate and molecular weight. The predicted molecular weight was in good agreement with the experimental results.

(1) Bauer, W. In Ullmann's Encyclopedia of Industrial Chemistry; Wiley-VCH Verlag GmbH & Co. KGaA: 2000.

(2) Bebe, S.; Yu, X. R.; Hutchinson, R. A.; Broadbelt, L. J. Macromolecular Symposia 2006, 243, 179.

(3) Zhang, G. Z.; Konstantinov, I. A.; Arturo, S. G.; Yu, D. C.; Broadbelt, L. J. J Chem Theory Comput 2014, 10, 5668.

(4) Matheson, M. S.; Auer, E. E.; Bevilacqua, E. B.; Hart, E. J. J Am Chem Soc 1949, 71, 497.

(5) Beuermann, S.; Buback, M.; Davis, T. P.; Gilbert, R. G.; Hutchinson, R. A.; Olaj, O. F.; Russell, G. T.; Schweer, J.; vanHerk, A. M. Macromol Chem Phys 1997, 198, 1545.

(6) Simal, F.; Demonceau, A.; Noels, A. F. Angew Chem Int Edit 1999, 38, 538.

(7) von Werne, T.; Patten, T. E. J Am Chem Soc 2001, 123, 7497.

(8) Yu, X. R.; Pfaendtner, J.; Broadbelt, L. J. J Phys Chem A 2008, 112, 6772.

(9) Yu, X. R.; Levine, S. E.; Broadbelt, L. J. Macromolecules 2008, 41, 8242.

(10) Degirmenci, I.; Aviyente, V.; Van Speybroeck, V.; Waroquier, M. Macromolecules 2009, 42, 3033.

(11) Degirmenci, I.; Eren, S.; Aviyente, V.; De Sterck, B.; Hemelsoet, K.; Van Speybroeck, V.; Waroquier, M. Macromolecules 2010, 43, 5602.

(12) Wang, W.; Hutchinson, R. A. Macromolecules 2008, 41, 9011.

(13) Merrick, J. P.; Moran, D.; Radom, L. J Phys Chem A 2007, 111, 11683.

(14) Van Speybroeck, V.; Van Neck, D.; Waroquier, M.; Wauters, S.; Saeys, M.; Marin, G. B. J Phys Chem A 2000, 104, 10939.

(15) Van Speybroeck, V.; Vansteenkiste, P.; Van Neck, D.; Waroquier, M. Chem Phys Lett 2005, 402, 479.

(16) Heuts, J. P. A.; Gilbert, R. G.; Radom, L. J Phys Chem-Us 1996, 100, 18997.

(17) Pfaendtner, J.; Yu, X.; Broadbelt, L. J. Theor Chem Acc 2007, 118, 881.

(18) Pfaendtner, J.; Yu, X.; Broadbelt, L. J.; 1.0 ed., available for use free by contacting Linda J. Broadbelt.