Easy preparation of magnetic nanoparticles-rGO-chitosan composite beads: Optimization study on cefixime removal based on RSM and ANN by using Genetic Algorithm Approach

CİĞEROĞLU Z., KÜÇÜKYILDIZ G., Erim B., ALP E.

Journal of Molecular Structure, cilt.1224, 2021 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 1224
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1016/j.molstruc.2020.129182
  • Dergi Adı: Journal of Molecular Structure
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Chemical Abstracts Core, INSPEC
  • Anahtar Kelimeler: Adsorption, Artificial Neural Network, Cefixime, Magnetic nanoparticles-rGO-chitosan composite beads
  • Uşak Üniversitesi Adresli: Evet

Özet

Today, antibiotic resistance is emerging as a global health problem. Antibiotic-resistant bacteria are formed by misuse of antibiotics, throwing some of them into the sewers and also throwing them into the environment. For this purpose, an easy preparation methodology was used to synthesize a cost-effective magnetic nanoparticles-rGO-chitosan composite bead. TEM, FESEM-EDX, FTIR, XRD, and VSM were applied to enlighten the structure of adsorbent. Cefixime (CFX) removal was chosen as the application area of adsorbent. Response surface methodology (RSM) and Artificial neural network (ANN) using by Genetic Algorithm (GA) approach were utilized to determine not only the optimal conditions but also optimal adsorption uptake. The optimal operation conditions of RSM were found as pH 8, initial concentration of CFX =42.81 mgL−1 and adsorbent dose was 5 mg. The adsorption uptake corresponding to these optimal values was found to be 30.63 mgg−1. When the models were compared, it was found that GA+RF was compatible with the experimental data. Furthermore, RF has emerged as the highest determination coefficient (R2=0.9939). Finally, the adsorbent can be implemented on pilot scale systems for antibiotic treatment owing to its promising results.