Comprehensive study on efficient diclofenac sodium removal using walnut and pistachio shell activated carbon: ANN, kinetics, isotherms, thermodynamics and DFT calculations

Seymen S. T., Atalay Eroğlu H., Kadioglu E. N., Umar M., Hamid A., Khan H., ...Daha Fazla

BIOMASS & BIOENERGY, cilt.202, 2025 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 202
  • Basım Tarihi: 2025
  • Doi Numarası: 10.1016/j.biombioe.2025.108216
  • Dergi Adı: BIOMASS & BIOENERGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, BIOSIS, Biotechnology Research Abstracts, CAB Abstracts, Compendex, Environment Index, Geobase, INSPEC, Pollution Abstracts, Veterinary Science Database, DIALNET, Civil Engineering Abstracts
  • Ondokuz Mayıs Üniversitesi Adresli: Evet

Özet

This study investigates diclofenac (DCF) adsorption using walnut shell activated carbon (WSAC) and pistachio shell activated carbon (PSAC), evaluating the effects of pH, contact time, adsorbent dosage, and initial DCF concentration. Maximum removal was achieved at pH 7, with WSAC and PSAC reaching 96.12 % and 95.93 %, respectively. Equilibrium occurred within 30 min. WSAC showed a maximum capacity of 48.408 mg/g, while PSAC reached 42.262 mg/g. Kinetic modelling revealed that WSAC followed a pseudo-first-order model, whereas PSAC fitted a pseudo-second-order model, indicating different adsorption mechanisms. Increasing adsorbent dosage improved removal efficiency but decreased adsorption capacity per unit mass. Higher initial DCF concentrations reduced removal performance. Isotherm analysis showed that the Toth model best described WSAC data, while the Radke-Prausnitz model fit PSAC. Thermodynamic evaluations confirmed both adsorption processes were spontaneous and exothermic. FTIR and SEM analyses revealed distinct surface properties for both adsorbents. WSAC exhibited more pronounced hydroxyl and carbonyl groups, contributing to stronger hydrogen bonding and electrostatic interactions, while SEM images showed a more porous and irregular surface morphology compared to PSAC. Density functional theory (DFT) analysis revealed strong interactions involving hydrogen bonding, electrostatic forces, and it-it stacking, supporting the spontaneous nature of adsorption. WSAC proved more effective overall. Artificial neural network (ANN) model predicted DCF removal with high accuracy (R2 = 0.983, RMSE = 0.7119), demonstrating strong agreement with experimental data. This study provides a cost-effective, efficient method for pollutant removal and offers valuable insights into optimizing wastewater treatment strategies. This study highlights the significant practical potential of low-cost biomass-based adsorbents in enhancing existing wastewater treatment technologies, as well as providing a cost-effective and efficient method for the removal of pharmaceutical contaminants.