Predicting Iron Adsorption Capacity and Thermodynamics onto Calcareous Soil from Aqueous Solution by Linear Regression and Neural Network Modeling
Journal Title: Universal Journal of Environmental Research and Technology - Year 2011, Vol 1, Issue 4
Abstract
Calcareous soil with various physical parameters along with morphological characteristics Fourier Transform Infrared (FTIR), X-Ray Diffraction (XRD) and Scanning Electron microscopy (SEM) was used for removal of Fe+2 from aqueous solution through batch process. During batch study various parameters effects on the adsorption capacity of Fe+2. This adsorption was followed by pseudo-second-order kinetic and Langmuir isotherm model. The activation energy was determined at 9.47 kJ/mol indicating physical adsorption. According to D-R model, Es also supports this. Gibb’s free energy (∆G0), explains the spontaneous nature of adsorption and negative value of ∆H0 implies exothermic nature. A six layered feed forward neural network with back propagation training algorithm was developed using twenty one experimental data sets obtained from laboratory batch study. The ANN predicted results were compared with the experimental results of the laboratory test. It was concluded that calcareous soil is an effective adsorbent for removal of Fe+2 from aqueous solution.
Authors and Affiliations
Bhaumik R. , Mondal N. K. , Das B. , Roy P. and Pal K. C.
Keywords
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