Chain conformation and intramolecular crosslinking of poly(dimethylaminoethyl methacrylate-co-methyl methacrylate-co-butyl methacrylate) in the presence of mono- or dicarboxylic acids: a dilute solution viscometry study

2012 ◽  
Vol 20 (1) ◽  
Author(s):  
Maryam Babaie ◽  
Mohammad Imani ◽  
Hamed Azizi
2011 ◽  
Vol 284-286 ◽  
pp. 1707-1712 ◽  
Author(s):  
Yong Sheng Chen ◽  
Jiang Nan Shen ◽  
Jun Hong Qiu

Miscibility of ternary polymer blends composed of poly(ethyleneimine) (PEI), poly(ethylene glycol) (PEG), and carboxymethyl chitosan (CMCS) was investigated by dilute-solution viscometry, FTIR spectrum, and scanning electron microscope (SEM) techniques. The results of these measurements indicate that PEG is immiscible in the ternary CMCS/PEI/PEG polymer blend.


1966 ◽  
Vol 44 (2) ◽  
pp. 153-156 ◽  
Author(s):  
S. Brownstein ◽  
D. M. Wiles

The high resolution proton magnetic resonance spectra of five samples of poly(methyl methacrylate) in chloroform solution have been measured with 100 Mc/s equipment. The widths of the absorption lines arising from the protons of the α-methyl and the methoxyl groups have been compared. The widths are greater when the polymer is predominantly syndiotactic than when it is predominantly isotactic. It is concluded that isotactic samples have the more extended conformation in chloroform solution. An analogy with dilute solution viscosity measurements is outlined in support of this conclusion. Differences between the widths of the lines of the methylene protons in a completely isotactic poly(methyl methacrylate) sample are attributed to long range spin coupling.


2021 ◽  
Author(s):  
Baranitharan Sanmuga Sundaram

Optimal control policies are determined for the free radical polymerization of three different polymerization processes, in a non-isothermal batch reactor as follows: (1) bulk polymerization of n-butyl methacrylate; (2) solution polymerization of methyl methacrylate with monofunctional initiator; (3) solution polymerization of methyl methacrylate with bifunctional initiator. Four different optimal control objectives are realized for the above three processes. The objectives are: (i) maximization of monomer conversion in a specified operation time, (ii) minimization of operation time for a specified, final monomer conversation, (iii) maximization of monomer conversion for a specified, final number average polymer molecular weight, and (iv) maximization of monomer conversion for a specified, final weight average polymer molecular weight. The realization of these objectives is expected to be very useful for the batch production of polymers. To realize the above four different optimal control objectives, a genetic algorithms-based optimal control method is applied, and the temperature of heat exchange fluid inside reactor jacket is used as a control function. Necessary equations are provided in the above three processes to suitably transform the process model in the range of a specified variable other than time, and to evaluate the elements of Jacobian to help in the accurate solution of the process model. The results of this optimal control application reveal considerable improvements in the performance of the batch polymerization processes.


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