| Autor: |
Khan T; Department of Civil Engineering, Faculty of Engineering, Najran University, P.O. Box 1988, King Abdulaziz Road, Najran 61441, Saudi Arabia.; Civil and Environmental Engineering Department, Universiti Teknologi PETRONAS, 32610 Seri Iskandar, Perak Darul Ridzuan, Malaysia., Binti Abd Manan TS; Institute of Tropical Biodiversity and Sustainable Development, Universiti Malaysia Terengganu, 21300 Kuala Terengganu, Malaysia., Isa MH; Civil Engineering Programme, Universiti Teknologi Brunei, Tungku Highway, Gadong BE1410, Brunei Darussalam., Ghanim AAJ; Department of Civil Engineering, Faculty of Engineering, Najran University, P.O. Box 1988, King Abdulaziz Road, Najran 61441, Saudi Arabia., Beddu S; Department of Civil Engineering, Universiti Tenaga Nasional, Jalan Ikram-Uniten, 43000 Kajang, Selangor Darul Ehsan, Malaysia., Jusoh H; Geo TriTech, No. 17, Persiaran Perdana 15A, Pinji Perdana, 31500 Lahat, Perak, Malaysia., Iqbal MS; Department of Space Sciences, Institute of Space Technology, Islamabad 44000, Pakistan., Ayele GT; Australian Rivers Institute and School of Engineering, Griffith University, Nathan, QLD 4111, Australia., Jami MS; Department of Biotechnology Engineering, Faculty of Engineering, International Islamic University Malaysia, P.O. Box 10, Kuala Lumpur 50728, Malaysia. |
| Abstrakt: |
This research optimized the adsorption performance of rice husk char (RHC4) for copper (Cu(II)) from an aqueous solution. Various physicochemical analyses such as Fourier transform infrared spectroscopy (FTIR), field-emission scanning electron microscopy (FESEM), carbon, hydrogen, nitrogen, and sulfur (CHNS) analysis, Brunauer-Emmett-Teller (BET) surface area analysis, bulk density (g/mL), ash content (%), pH, and pH ZPC were performed to determine the characteristics of RHC4. The effects of operating variables such as the influences of aqueous pH, contact time, Cu(II) concentration, and doses of RHC4 on adsorption were studied. The maximum adsorption was achieved at 120 min of contact time, pH 6, and at 8 g/L of RHC4 dose. The prediction of percentage Cu(II) adsorption was investigated via an artificial neural network (ANN). The Fletcher-Reeves conjugate gradient backpropagation (BP) algorithm was the best fit among all of the tested algorithms (mean squared error (MSE) of 3.84 and R 2 of 0.989). The pseudo-second-order kinetic model fitted well with the experimental data, thus indicating chemical adsorption. The intraparticle analysis showed that the adsorption process proceeded by boundary layer adsorption initially and by intraparticle diffusion at the later stage. The Langmuir and Freundlich isotherm models interpreted well the adsorption capacity and intensity. The thermodynamic parameters indicated that the adsorption of Cu(II) by RHC4 was spontaneous. The RHC4 adsorption capacity is comparable to other agricultural material-based adsorbents, making RHC4 competent for Cu(II) removal from wastewater. |
