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Agro - industrial waste / S. H. Hasan in Industrial & engineering chemistry research, Vol. 49 N° 19 (Octobre 2010) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 49 N° 19 (Octobre 2010) . - pp. 8927–8934 Titre : Agro - industrial waste : A low - cost option for the biosorptive remediation of selenium anions Type de document : texte imprimé Auteurs : S. H. Hasan, Auteur ; D. Ranjan, Auteur Année de publication : 2010 Article en page(s) : pp. 8927–8934 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Biosorbent  Agro  industrial  waste Résumé : For remediation purposes, initially, the screening and selection of potent biosorbent, among three agro-industrial wastes (i.e., wheat bran, maize bran, and rice bran) was done. Wheat bran was found to show maximum uptake in the case of both Se(IV) and Se(VI) ions. Effect of various parameters (pH, temperature, initial metal ion concentration, and biomass dose) was extensively investigated on the uptake of these metal ions by potent biosorbent using batch mode. Langmuir, Freundlich, and Dubinin−Radushkevich (D-R) isotherm models were applied and all three isotherms fitted well to sorption data. The maximum sorption capacity of wheat bran was 89.28 μg/g for Se(VI) and 80.65 μg/g for Se(VI) at 20 °C and pH 2.0. Values of mean sorption energy indicated sorption to be chemisorption. Thermodynamic study revealed that sorption was feasible, spontaneous and exothermic. The sorption reaction was determined to be pseudo-second-order. Fourier transform infrared (FTIR) analysis of raw and metal-loaded biosorbent was done to determine changes on the surface of the sorbent after sorption. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie100622c [article] Agro - industrial waste : A low - cost option for the biosorptive remediation of selenium anions [texte imprimé] / S. H. Hasan, Auteur ; D. Ranjan, Auteur . - 2010 . - pp. 8927–8934. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 49 N° 19 (Octobre 2010) . - pp. 8927–8934 Mots-clés : Biosorbent  Agro  industrial  waste Résumé : For remediation purposes, initially, the screening and selection of potent biosorbent, among three agro-industrial wastes (i.e., wheat bran, maize bran, and rice bran) was done. Wheat bran was found to show maximum uptake in the case of both Se(IV) and Se(VI) ions. Effect of various parameters (pH, temperature, initial metal ion concentration, and biomass dose) was extensively investigated on the uptake of these metal ions by potent biosorbent using batch mode. Langmuir, Freundlich, and Dubinin−Radushkevich (D-R) isotherm models were applied and all three isotherms fitted well to sorption data. The maximum sorption capacity of wheat bran was 89.28 μg/g for Se(VI) and 80.65 μg/g for Se(VI) at 20 °C and pH 2.0. Values of mean sorption energy indicated sorption to be chemisorption. Thermodynamic study revealed that sorption was feasible, spontaneous and exothermic. The sorption reaction was determined to be pseudo-second-order. Fourier transform infrared (FTIR) analysis of raw and metal-loaded biosorbent was done to determine changes on the surface of the sorbent after sorption. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie100622c

Bioadsorption of arsenic / D. Ranjan in Industrial & engineering chemistry research, Vol. 50 N° 17 (Septembre 2011) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 50 N° 17 (Septembre 2011) . - pp. 9852-9863 Titre : Bioadsorption of arsenic : an artificial neural networks and response surface methodological approach Type de document : texte imprimé Auteurs : D. Ranjan, Auteur ; D. Mishra, Auteur ; S. H. Hasan, Auteur Année de publication : 2011 Article en page(s) : pp. 9852-9863 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Neural  network  Biosorption Résumé : The estimation capacities of two optimization methodologies, response surface methodology (RSM) and artificial neural network (ANN) were evaluated for prediction of biosorptive remediation of As(III) and As(V) species in batch as well as column mode. The independent parameters (viz. pH, initial arsenic concentration, temperature, and biomass dose in the case of batch mode and bed height, flow rate, and initial arsenic concentration in the case of column mode) were fed as input to the central composite design (CCD) of RSM and the ANN techniques, and the output was the uptake capacity of the sorbent. The CCD was used to evaluate the simple and combined effects of the independent parameters and to derive a second-order regression equation for predicting optimization of the process. The sets of input-output patterns were also used to train the multilayer feed-forward networks employing the backpropagation algorithm with MATLAB. The application of the RSM and ANN techniques to the available experimental data showed that ANN outperforms RSM indicating the superiority of a properly trained ANN over RSM in capturing the nonlinear behavior of the system and the simultaneous prediction of the output. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=24483627 [article] Bioadsorption of arsenic : an artificial neural networks and response surface methodological approach [texte imprimé] / D. Ranjan, Auteur ; D. Mishra, Auteur ; S. H. Hasan, Auteur . - 2011 . - pp. 9852-9863. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 50 N° 17 (Septembre 2011) . - pp. 9852-9863 Mots-clés : Neural  network  Biosorption Résumé : The estimation capacities of two optimization methodologies, response surface methodology (RSM) and artificial neural network (ANN) were evaluated for prediction of biosorptive remediation of As(III) and As(V) species in batch as well as column mode. The independent parameters (viz. pH, initial arsenic concentration, temperature, and biomass dose in the case of batch mode and bed height, flow rate, and initial arsenic concentration in the case of column mode) were fed as input to the central composite design (CCD) of RSM and the ANN techniques, and the output was the uptake capacity of the sorbent. The CCD was used to evaluate the simple and combined effects of the independent parameters and to derive a second-order regression equation for predicting optimization of the process. The sets of input-output patterns were also used to train the multilayer feed-forward networks employing the backpropagation algorithm with MATLAB. The application of the RSM and ANN techniques to the available experimental data showed that ANN outperforms RSM indicating the superiority of a properly trained ANN over RSM in capturing the nonlinear behavior of the system and the simultaneous prediction of the output. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=24483627

Rice polish / D. Ranjan in Industrial & engineering chemistry research, Vol. 48 N° 23 (Décembre 2009) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 48 N° 23 (Décembre 2009) . - pp. 10180–10185 Titre : Rice polish : an alternative to conventional adsorbents for treating arsenic bearing water by Up-flow column method Type de document : texte imprimé Auteurs : D. Ranjan, Auteur ; M. alat, Auteur ; S. H. Hasan, Auteur Année de publication : 2010 Article en page(s) : pp. 10180–10185 Note générale : Industrial chemistry Langues : Anglais (eng) Mots-clés : Rice  Polish--Alternative--Conventional--Adsorbents--Treating--Arsenic--Bearing--Up-Flow  Column  Method Résumé : “Rice polish”, an agrowaste from rice milling industries, was utilized as potential biosorbent for removal of arsenic from water in a continuous up-flow fixed bed column system. The experiments were conducted to study the effect of important design parameters such as bed height, flow rate, and initial metal ion concentration. At a bed height of 25 cm, flow rate 1.66 mL/min, and initial metal ion concentration 1000 μg/L, the metal uptake capacity of rice polish for As(III) and As(V) was found to be 66.95 and 78.95 μg/g, respectively. The bed depth service time (BDST) model was used to analyze the experimental data. The computed sorption capacity (No) was 28776 and 28248 μg/L for As(III) and As(V), respectively. The rate constant (Ka) was recorded as 0.117 × 10−3 and 0.26 × 10−4 (L/μg)/min for As(III) and As(V), respectively. The column regeneration studies were carried out using 10% NaOH as eluant for three sorption−desorption cycles. The high arsenic removal ability and regeneration efficiency of this biosorbent suggest its applicability in industrial processes and data generated would help in further upscaling of the adsorption process. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie900877p [article] Rice polish : an alternative to conventional adsorbents for treating arsenic bearing water by Up-flow column method [texte imprimé] / D. Ranjan, Auteur ; M. alat, Auteur ; S. H. Hasan, Auteur . - 2010 . - pp. 10180–10185. Industrial chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 48 N° 23 (Décembre 2009) . - pp. 10180–10185 Mots-clés : Rice  Polish--Alternative--Conventional--Adsorbents--Treating--Arsenic--Bearing--Up-Flow  Column  Method Résumé : “Rice polish”, an agrowaste from rice milling industries, was utilized as potential biosorbent for removal of arsenic from water in a continuous up-flow fixed bed column system. The experiments were conducted to study the effect of important design parameters such as bed height, flow rate, and initial metal ion concentration. At a bed height of 25 cm, flow rate 1.66 mL/min, and initial metal ion concentration 1000 μg/L, the metal uptake capacity of rice polish for As(III) and As(V) was found to be 66.95 and 78.95 μg/g, respectively. The bed depth service time (BDST) model was used to analyze the experimental data. The computed sorption capacity (No) was 28776 and 28248 μg/L for As(III) and As(V), respectively. The rate constant (Ka) was recorded as 0.117 × 10−3 and 0.26 × 10−4 (L/μg)/min for As(III) and As(V), respectively. The column regeneration studies were carried out using 10% NaOH as eluant for three sorption−desorption cycles. The high arsenic removal ability and regeneration efficiency of this biosorbent suggest its applicability in industrial processes and data generated would help in further upscaling of the adsorption process. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie900877p

“Rice polish” for the removal of arsenic from aqueous solution / S. H. Hasan in Industrial & engineering chemistry research, Vol. 48 N° 9 (Mai 2009) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 48 N° 9 (Mai 2009) . - pp. 4194–4201 Titre : “Rice polish” for the removal of arsenic from aqueous solution : optimization of process variables Type de document : texte imprimé Auteurs : S. H. Hasan, Auteur ; D. Ranjan, Auteur ; M. Talat, Auteur Année de publication : 2009 Article en page(s) : pp. 4194–4201 Note générale : Chemical engineering Langues : Anglais (eng) Mots-clés : Rice  polish  Aqueous  solution  Box−Behnken  Design  Polynomial  regression  model Résumé : Rice polish, a waste from the rice milling industry, was utilized as a potential biosorbent for removal of arsenic from aqueous solution. Optimization of process variables (pH, initial metal concentration, and temperature) and their cumulative effect were investigated using Box−Behnken Design (BBD) with only 15 sets of experimental runs. A second-order polynomial regression model was used, and results predicted showed high value of regression coefficients (R2, i.e., 95.69% for As(III) and 98.42% for As(V)) indicating good agreement with experimental data. The main effect plot showed uptake of arsenic having a curved relationship with pH, initial metal ion concentration having a positive effect, and temperature having a negative effect. The maximum removal of As(III) (41.18 μg/g) and As(V) (49 μg/g) predicted by contour and optimization plot was achieved at pH 6.84 and 4.29, respectively, at an initial metal ion concentration of 1000 μg/L, temperature 20 °C, and biomass dose of 1 g/50 mL. Scanning electron microscopy (SEM) analysis was carried out to find out the changes on the biosorbent surface during the sorption process. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie801822d [article] “Rice polish” for the removal of arsenic from aqueous solution : optimization of process variables [texte imprimé] / S. H. Hasan, Auteur ; D. Ranjan, Auteur ; M. Talat, Auteur . - 2009 . - pp. 4194–4201. Chemical engineering Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 48 N° 9 (Mai 2009) . - pp. 4194–4201 Mots-clés : Rice  polish  Aqueous  solution  Box−Behnken  Design  Polynomial  regression  model Résumé : Rice polish, a waste from the rice milling industry, was utilized as a potential biosorbent for removal of arsenic from aqueous solution. Optimization of process variables (pH, initial metal concentration, and temperature) and their cumulative effect were investigated using Box−Behnken Design (BBD) with only 15 sets of experimental runs. A second-order polynomial regression model was used, and results predicted showed high value of regression coefficients (R2, i.e., 95.69% for As(III) and 98.42% for As(V)) indicating good agreement with experimental data. The main effect plot showed uptake of arsenic having a curved relationship with pH, initial metal ion concentration having a positive effect, and temperature having a negative effect. The maximum removal of As(III) (41.18 μg/g) and As(V) (49 μg/g) predicted by contour and optimization plot was achieved at pH 6.84 and 4.29, respectively, at an initial metal ion concentration of 1000 μg/L, temperature 20 °C, and biomass dose of 1 g/50 mL. Scanning electron microscopy (SEM) analysis was carried out to find out the changes on the biosorbent surface during the sorption process. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie801822d