Simultaneous removal of Cu²⁺, Ni²⁺ and Zn²⁺ ions using leftover Azadirachta indica twig ash

Abstract

A novel adsorbent namely, Azadirachta indica twig ash, was identified and evaluated for adsorption of Cu²⁺, Ni²⁺ and Zn²⁺ ions. The properties of novel adsorbent were studied by various characterization techniques such as Scanning Electron Microscopy, Fourier Transformation Infrared analysis, X-ray diffraction, proximate and ultimate analysis. Furthermore, an optimization study was conducted to determine the optimal value of process parameters. Various dimensionless numbers have been derived and used to elucidate the adsorption dynamics in the present study. Application of Artificial Neural Network in data modeling together with comparative analysis of novel adsorbents with other adsorbents has been done. Elemental analysis revealed 38.47% Carbon, 1.89% Hydrogen, 49.21% Oxygen and 10.43% Nitrogen in the A. indica twig ash. Outcome of X-ray diffraction showed amorphous characteristic (58.4%) of an adsorbent. BET surface area and bulk density was found to be 71.35 m²/g and 0.47 g/cm³ for A. indica twig ash. Furthermore, the correlation plot showed a deviation of 0.16% for Cu²⁺, 0.09% for Ni²⁺ and 0.08% for Zn²⁺ between experimental and Artificial Neural Network predicted values which implied that the chosen algorithm and methodology were appropriate for prediction. The obtained values of film and pore diffusivity were 2.13 × 10⁻¹², 5.17 × 10⁻¹², 3.43 × 10⁻¹¹ cm² sec⁻¹ and 3.70 × 10⁻¹³, 4.44 × 10⁻¹³, 5.55 × 10⁻¹³ cm² sec⁻¹ for Cu²⁺, Ni²⁺ and Zn²⁺ ions, respectively. These values revealed that the adsorption mechanism depends on the pore diffusion. The values of dimensionless numbers $(\phi ,$ N_k and $\lambda )\mathrm{}$ indicated that the adsorption of Cu²⁺, Ni²⁺ and Zn²⁺ ions on A. indica twig ash surface was predominantly controlled by diffusion. Moreover, isotherm and kinetic modeling demonstrated superior values of the regression coefficient for the Langmuir isotherm and pseudo-second order kinetic model. This reflected that the adsorption occurred in monolayer fashion. Simultaneous removal of metal ions followed an order based on electronegativity: Cu²⁺ > Ni²⁺ > Zn²⁺. Positive ΔH (126,579.20 kJ/mole, 96,527.95 kJ/mole and 73,076.65 kJ/mole) and ΔS (437.65 J/mol K, 331.15, J/mol K and 248.71 J/mol K) for Cu²⁺, Ni²⁺ and Zn²⁺ ions, respectively showed that binding of metal ions on the surface of A. indica twig ash was endothermic with increased turbulence at the solid-aqueous interface.

Keywords:

• Adsorption
• artificial neural network
• Azadirachta indica twig ash
• copper
• nickel
• zinc

Acknowledgments

The authors are thankful to the School of Biochemical Engineering, IIT (BHU) Varanasi, Varanasi, for financial and technical support of the present research work.

Conflicts of interest

The authors have no conflicts of interest.