Modeling of Swelling Behaviors of Acrylamide-Based Polymeric Hydrogels by Intelligent System

BOZTEPE C., Solener M., Yuceer M., KÜNKÜL A., Kabasakal O. S.

JOURNAL OF DISPERSION SCIENCE AND TECHNOLOGY, cilt.36, sa.11, ss.1647-1656, 2015 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 36 Sayı: 11
  • Basım Tarihi: 2015
  • Doi Numarası: 10.1080/01932691.2014.996892
  • Dergi Adı: JOURNAL OF DISPERSION SCIENCE AND TECHNOLOGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.1647-1656
  • Anahtar Kelimeler: ANN, hydrogel, MLSR, modeling, swelling behavior, ARTIFICIAL NEURAL-NETWORK, PH, PREDICTION, KINETICS, ACID
  • İnönü Üniversitesi Adresli: Evet

Özet

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.