Yazar "Kabasakal, Osman S." seçeneğine göre listele

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    Modeling of Swelling Behaviors of Acrylamide-Based Polymeric Hydrogels by Intelligent System
    (Taylor & Francis Inc, 2015) Boztepe, Cihangir; Solener, Musa; Yuceer, Mehmet; Kunkul, Asim; Kabasakal, Osman S.
    Hydrogels based on acrylamide (AAm) were synthesized by free radical polymerization in an aqueous solution using N, N'-methylenebisacrylamide (MBAAm) as crosslinker. To obtain anionic hydrogels, 2-acrylamido-2-methylpropanesulfonic acid sodium salt (AMPS) and acrylic acid (AAc) were used as comonomers. The swelling behaviors of all hydrogel systems were modeled using an artificial neural network (ANN) and compared with a multivariable least squares regression (MLSR) model and phenomenal model. The predictions from the ANN model, which associated input parameters, including the amounts of crosslinker (MBA) and comonomer, and swelling values with time, produce results that show excellent correlation with experimental data. The parameters of swelling kinetics and water diffusion mechanisms of the hydrogels were calculated using the obtained experimental data. Model analysis indicated that the ANN models could accurately describe complex swelling behaviors of highly swellable hydrogels.
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    Prediction of the deswelling behaviors of pH- and temperature-responsive poly(NIPAAm-co-AAc) IPN hydrogel by artificial intelligence techniques
    (Springer, 2020) Boztepe, Cihangir; Yuceer, Mehmet; Kunkul, Asim; Solener, Musa; Kabasakal, Osman S.
    One of the most important fields of interest in respect of stimuli-responsive hydrogels is modeling and simulation of their deswelling behavior. The problem mentioned above plays an important role regarding diffusion of fluid from hydrogel to media, what is very useful in biomedical applications, such as controlled drug delivery systems, biomaterials or biosensors. In this study, the pH- and temperature-responsive poly(N-isopropylacrylamide-co-acrylic acid) interpenetrating polymer network (poly(NIPAAm-co-AAc) IPN) hydrogel was synthesized by free radical solution polymerization method. In order to improve the deswelling rate of the conventional poly(NIPAAm-co-AAc) hydrogels, their IPN structure was synthesized by using poly(NIPAAm-co-AAc) microgels. The chemical structure and surface morphology of poly(NIPAAm-co-AAc) IPN hydrogels were characterized by FT-IR and SEM analysis techniques. The synthesized poly(NIPAAm-co-AAc) IPN hydrogel has high swelling capacity (112 g water/g dry polymer at 20 degrees C and pH 7) and exhibited fast and multivariable deswelling behaviors dependent on pH and temperature. The pH- and temperature-dependent mechanical property of IPN hydrogel was investigated. It was found that the compressive strength of the IPN hydrogels was changed inversely proportional to the swelling capacity. To develop the model for deswelling behaviors of IPN hydrogel, artificial neural network (ANN) model and least squares support vector machine model techniques were used. The predictions from the ANN model showed very good correlation with observed data. The results indicated that the ANN model could accurately predict complex deswelling behavior of pH- and temperature-responsive IPN hydrogels.