Adsorption Of Acid Violet 7 Dye Using RHA/CFA Sorbent : Modelling, Process Analysis And Optimization
The factors affecting the performance of acid violet 7 (AV 7) adsorption were analyzed, which includes the rice husk ash (RHA)/coal fly ash (CFA) ash ratio, type of additives used, and concentration of additives. The experiment was run based on the 3-level factorial design in response surface meth...
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| Format: | Monograph |
| Language: | English |
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Universiti Sains Malaysia
2018
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| Online Access: | http://eprints.usm.my/53629/1/Adsorption%20Of%20Acid%20Violet%207%20Dye%20Using%20RHA%20CFA%20Sorbent%20%20Modelling%2C%20Process%20Analysis%20And%20Optimization_Ng%20Wei%20Ling_K4_2018.pdf |
| _version_ | 1825906921856565248 |
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| author | Ng, Wei Ling |
| author_facet | Ng, Wei Ling |
| author_sort | Ng, Wei Ling |
| collection | USM |
| description | The factors affecting the performance of acid violet 7 (AV 7) adsorption were analyzed, which includes the rice husk ash (RHA)/coal fly ash (CFA) ash ratio, type of additives
used, and concentration of additives. The experiment was run based on the 3-level factorial design in response surface methodology (RSM). The experimental results were used to analyze the effect of input factors on dye adsorption and to build a model to predict the performance of the system. Response surface plot suggested that higher dye adsorption efficiency can be achieved at higher ash ratio and higher additive concentration. Mathematical model was built using RSM and the performance of the model was analyzed through analysis of variance (ANOVA). Another neural network model were also built by using neural network toolbox in Matlab, and net operation and predictor function in Mathematica. The mathematical and neural network model were used to predict the performance of AV 7 adsorption. Due to the limited
experimental data available for neural network training, mathematical model generated in RSM had better accuracy in predicting the output response. , with R2 of 0.9336 and RMSE of 3.3515. Numerical optimization for AV 7 adsorption was done
by RSM to obtain the optimum operating condition for adsorption to achieve maximum dye removal efficiency. It was found out that the maximum adsorption efficiency (45.14%) would be achieved at RHA/CFA ash ratio of 3.00 and 1 M of NaOH. |
| first_indexed | 2024-03-06T15:56:42Z |
| format | Monograph |
| id | usm.eprints-53629 |
| institution | Universiti Sains Malaysia |
| language | English |
| last_indexed | 2024-03-06T15:56:42Z |
| publishDate | 2018 |
| publisher | Universiti Sains Malaysia |
| record_format | dspace |
| spelling | usm.eprints-536292022-07-27T07:01:30Z http://eprints.usm.my/53629/ Adsorption Of Acid Violet 7 Dye Using RHA/CFA Sorbent : Modelling, Process Analysis And Optimization Ng, Wei Ling T Technology TP Chemical Technology The factors affecting the performance of acid violet 7 (AV 7) adsorption were analyzed, which includes the rice husk ash (RHA)/coal fly ash (CFA) ash ratio, type of additives used, and concentration of additives. The experiment was run based on the 3-level factorial design in response surface methodology (RSM). The experimental results were used to analyze the effect of input factors on dye adsorption and to build a model to predict the performance of the system. Response surface plot suggested that higher dye adsorption efficiency can be achieved at higher ash ratio and higher additive concentration. Mathematical model was built using RSM and the performance of the model was analyzed through analysis of variance (ANOVA). Another neural network model were also built by using neural network toolbox in Matlab, and net operation and predictor function in Mathematica. The mathematical and neural network model were used to predict the performance of AV 7 adsorption. Due to the limited experimental data available for neural network training, mathematical model generated in RSM had better accuracy in predicting the output response. , with R2 of 0.9336 and RMSE of 3.3515. Numerical optimization for AV 7 adsorption was done by RSM to obtain the optimum operating condition for adsorption to achieve maximum dye removal efficiency. It was found out that the maximum adsorption efficiency (45.14%) would be achieved at RHA/CFA ash ratio of 3.00 and 1 M of NaOH. Universiti Sains Malaysia 2018-06-01 Monograph NonPeerReviewed application/pdf en http://eprints.usm.my/53629/1/Adsorption%20Of%20Acid%20Violet%207%20Dye%20Using%20RHA%20CFA%20Sorbent%20%20Modelling%2C%20Process%20Analysis%20And%20Optimization_Ng%20Wei%20Ling_K4_2018.pdf Ng, Wei Ling (2018) Adsorption Of Acid Violet 7 Dye Using RHA/CFA Sorbent : Modelling, Process Analysis And Optimization. Project Report. Universiti Sains Malaysia, Pusat Pengajian Kejuruteraan Kimia. (Submitted) |
| spellingShingle | T Technology TP Chemical Technology Ng, Wei Ling Adsorption Of Acid Violet 7 Dye Using RHA/CFA Sorbent : Modelling, Process Analysis And Optimization |
| title | Adsorption Of Acid Violet 7 Dye Using RHA/CFA Sorbent : Modelling, Process Analysis And Optimization |
| title_full | Adsorption Of Acid Violet 7 Dye Using RHA/CFA Sorbent : Modelling, Process Analysis And Optimization |
| title_fullStr | Adsorption Of Acid Violet 7 Dye Using RHA/CFA Sorbent : Modelling, Process Analysis And Optimization |
| title_full_unstemmed | Adsorption Of Acid Violet 7 Dye Using RHA/CFA Sorbent : Modelling, Process Analysis And Optimization |
| title_short | Adsorption Of Acid Violet 7 Dye Using RHA/CFA Sorbent : Modelling, Process Analysis And Optimization |
| title_sort | adsorption of acid violet 7 dye using rha cfa sorbent modelling process analysis and optimization |
| topic | T Technology TP Chemical Technology |
| url | http://eprints.usm.my/53629/1/Adsorption%20Of%20Acid%20Violet%207%20Dye%20Using%20RHA%20CFA%20Sorbent%20%20Modelling%2C%20Process%20Analysis%20And%20Optimization_Ng%20Wei%20Ling_K4_2018.pdf |
| work_keys_str_mv | AT ngweiling adsorptionofacidviolet7dyeusingrhacfasorbentmodellingprocessanalysisandoptimization |