460061 Estimation of Kinetic Parameters for ATRP Polymerization from MWD Experimental Data Using the Pgf Technique

Monday, November 14, 2016
Grand Ballroom B (Hilton San Francisco Union Square)
Cecilia Fortunatti1, Vivina Hanazumi1, Cristian Vitale2, Andres E. Ciolino1 and Mariano Asteasuain1, (1)Planta Piloto de Ingeniería Química (PLAPIQUI), UNS-CONICET, Bahía Blanca, Argentina, (2)Universidad Nacional del Sur (UNS), Department of Chemistry, Bahía Blanca, Argentina

The discovery of controlled radical polymerization (CRP) allowed producing polymers with unique molecular structures in mild operating conditions. CRP enables the synthesis of new materials with pre-specified properties without the stringent conditions required by anionic polymerizations. This fact motivated a great interest in the scientific and industrial communities. Numerous scientific studies and patents, and several industrial products already developed show this point.[1]

Atom transfer radical polymerization (ATRP) is one of the most popular CRP techniques. Although it employs a transition metal complex as catalyst (that must often be removed from the product), it presents several advantages such as commercial availability of reagents, large range of polymerizable monomers and simple end-functionalization. These advantages have fostered an extensive study of its kinetic mechanism, which has ultimately led to the development of several ATRP variants that allow overcome most of the shortages of this technique.[2]

The production of differentiated materials requires of a fine tuning of the polymer molecular structure. This can only be accomplished with a precise control of operating conditions. In order to implement such a precise control, modeling studies are useful tools that allow manufacturers to find the proper set of operating conditions necessary for synthesizing tailor-made polymers while minimizing the expenditure of resources on trial and error procedures.[3] For this purpose, accurate adjustment of the model kinetic parameters is needed.

Several authors have successfully dealt with the modeling of ATRP polymerization systems.[4-6] In all of these works, the estimation of model parameters was based on experimental data of conversion and/or average molecular weights. However, recent works have shown that the parameter estimation based on molecular weigth distribution (MWD) data may be more accurate due to the higher amount of experimental information for the fitting process.

In this work we present a comprehensive mathematical model of the ATRP variant known as Initiators for Continuous Activator Regeneration (ICAR) ATRP able to predict average molecular properties as well as the full MWD. Average properties are predicted using the well-known method of moments. The MWD is modeled using the probability generating function (pgf) technique. This technique has great potential for parameter estimation from the MWD data. The pgf technique allows selecting arbitrarily, without any loss of accuracy, the number of computed points of the MWD. In this way, the user is free to select an appropriate balance between model size and information fed to the fitting procedure.[7, 8] By means of this approach, the ATRP activation and deactivation kinetic constants of the ATRP of styrene were estimated from experimental data of MWD. The experimental set up involved the synthesis of polystyrene at 110ºC in solution of toluene using CuBr as the transition metal catalyst and hexamethyl-tris(2-aminoethyl)amine (Me6TREN) as ligand. Our results show that the modeled MWD has very good agreement with experimental data.

[1] K. Matyjaszewski and J. Spanswick, Materials Today, 8, 26 (2005).

[2] W. A. Braunecker and K. Matyjaszewski, Prog. Polym. Sci., 32, 93 (2007).

[3] D. R. D'Hooge, D. Konkolewicz, M. F. Reyniers, G. B. Marin and K. Matyjaszewski, Macromol. Theory Simul., 21, 52 (2012).

[4] M. Al-Harthi, L. S. Cheng, J. B. P. Soares and L. C. Simon, J. Polym. Sci., Part A: Polym. Chem., 45, 2212 (2007).

[5] Y. J. Kwark and B. M. Novak, Macromolecules, 37, 9395 (2004).

[6] T. Pintauer, P. Zhou and K. Matyjaszewski, J. Am. Chem. Soc., 124, 8196 (2002).

[7] M. Asteasuain, C. Sarmoria and A. Brandolin, Polymer, 43, 2513 (2002).

[8] C. Fortunatti, C. Sarmoria, A. Brandolin and M. Asteasuain, Comput. Chem. Eng., 66, 214 (2014).

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