Green and efficient biosorptive removal of methylene blue by Abelmoschus esculentus seed: Process optimization and multi-variate modeling.
The present work explores, for the first time, the adsorptive removal of methylene blue (MB) dye from aqueous solution using different parts of abundantly available agricultural product, Abelmoschus esculentus (lady's finger), and the processed seed powder (designated as LFSP) was found as the best....
| Publicado en: | Journal of Environmental Management Vol. 200; pp. 145 - 160 |
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| Autores principales: | , |
| Formato: | Artículo |
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Academic Press Inc.
Sep2017
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=123882139&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 123882139 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 03014797 EMJ jtl: Journal of Environmental Management issn: 03014797 maglogo: N pubinfo: dt: Sep2017 vid: 200 pid: 735 pub: Academic Press Inc. artinfo: ui: 123882139 10.1016/j.jenvman.2017.05.045 ppf: 145 ppct: 15 formats: tig: atl: Green and efficient biosorptive removal of methylene blue by Abelmoschus esculentus seed: Process optimization and multi-variate modeling. aug: au: Nayak, Ashish Kumar Pal, Anjali affil: Civil Engineering Department, Indian Institute of Technology, Kharagpur 721302, West Bengal, India su: Methylene blue Okra Multivariate analysis Scanning electron microscopy Field emission sug: subj: Other Vegetable (except Potato) and Melon Farming Methylene blue Okra Multivariate analysis Scanning electron microscopy Field emission keyword: Artificial neural network (ANN) Biosorption Lady's finger ( Abelmoschus esculentus ) Response surface methodology (RSM) Artificial neural network (ANN) Biosorption Lady's finger ( Abelmoschus esculentus ) Response surface methodology (RSM) ab: The present work explores, for the first time, the adsorptive removal of methylene blue (MB) dye from aqueous solution using different parts of abundantly available agricultural product, Abelmoschus esculentus (lady's finger), and the processed seed powder (designated as LFSP) was found as the best. The aforesaid biosorbent was characterized using field emission scanning electron microscopy (FESEM), Fourier transform infrared spectroscopy (FTIR) and pH ZPC analyses. The biosorption performance was evaluated using batch studies at 303 K, at varying operating conditions such as solution pH, biosorbent dosage, initial dye concentration and contact time. The pseudo-second order kinetic model was followed during the adsorption, and it was also found that intra-particle diffusion played a prominent role in the rate-controlling step. Langmuir and Temkin isotherms were followed the best, as was evident from the lower % non-linear error values and higher degree of determination coefficients. Thermodynamic investigations revealed that the biosorption processes were spontaneous and endothermic. Using the response surface methodology (RSM), a central composite design was developed, and subsequently applied as an input for the artificial neural network (ANN) approach in order to further analyze the interactive term effects between the significant process parameters, on the maximum biosorption capacity for MB dye removal by LFSP. The non-linear error functions and linear regression coefficients on the RSM model showed its dominance behaviour over ANN model for both data fitting and estimation capabilities. Using the statistical optimization, the maximum uptake capacity was found to be 205.656 mg/g. Experiments were conducted to regenerate the adsorbent and to recover the adsorbed dye using the eluent 0.5 M HCl. Cost analysis showed that, LFSP was 7 times cheaper than commercially available activated carbons. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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