Neural Network Modeling Applied to Polyacrylamide Based Hydrogels Synthetized By Single Step Process

This paper presents a series of experimental data obtained from the synthesis of polyacrylamide-based hydrogels and a general neural network methodology that accomplishes the modeling and optimization of the polymerization process. Using direct neural network modeling, the variation of the main para...

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Bibliographic Details
Published inPolymer-plastics technology and engineering Vol. 47; no. 10; pp. 1061 - 1071
Main Authors Curteanu, Silvia, Dumitrescu, Anca, Mihăilescu, Camelia, Simionescu, Bogdan
Format Journal Article
LanguageEnglish
Published Philadelphia, PA Taylor & Francis Group 01.10.2008
Taylor & Francis
Subjects
Applied sciences
direct and inverse neural network modeling
Exact sciences and technology
hydrogels, modeling and optimization strategy
Organic polymers
Physicochemistry of polymers
Properties and characterization
Solution and gel properties
swelling degree
Swelling
modeling and optimization strategy; swelling degree
Neural network
Experimental study
Property processing relationship
Modeling
Optimization
Colloidal gel
Free radical polymerization
direct and inverse neural network modeling; hydro-gels
Preparation
Acrylamide polymer
Hydrogel
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Summary:This paper presents a series of experimental data obtained from the synthesis of polyacrylamide-based hydrogels and a general neural network methodology that accomplishes the modeling and optimization of the polymerization process. Using direct neural network modeling, the variation of the main parameters in the synthesis of polyacrylamide-based hydrogels (polymerization yield and maximum swelling degree) was modeled in correlation with reactant concentrations, temperature, and reaction time. The predictions of the network, verified against initial training data and other testing data in the domain of the reaction conditions, were quite precise. Inverse neural modeling determines, in a facile manner and with good results, the initial reaction conditions, which lead to a preestablished reaction yield and maximum swelling degree. This optimization method is more advantageous compared to a difficult classical procedure that requires a good mathematical model and an optimization solving technique.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0360-2559
1525-6111
DOI:10.1080/03602550802355750