دورية أكاديمية
Comparison of chitosan based nano-adsorbents for dairy industry wastewater treatment through response surface methodology and artificial neural network models
| العنوان: | Comparison of chitosan based nano-adsorbents for dairy industry wastewater treatment through response surface methodology and artificial neural network models |
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| المؤلفون: | B. L. Dinesha, Sharanagouda Hiregoudar, Udaykumar Nidoni, K. T. Ramappa, Anilkumar Dandekar, M. V. Ravi |
| المصدر: | Water Science and Technology, Vol 83, Iss 5, Pp 1250-1264 (2021) |
| بيانات النشر: | IWA Publishing, 2021. |
| سنة النشر: | 2021 |
| المجموعة: | LCC:Environmental technology. Sanitary engineering |
| مصطلحات موضوعية: | dairy industry, optimization, modelling, nano-adsorbents, wastewater treatment, Environmental technology. Sanitary engineering, TD1-1066 |
| الوصف: | The present investigation was focused to compare chitosan based nano-adsorbents (CZnO and CTiO2) for efficient treatment of dairy industry wastewater using Response Surface Methodology (RSM) and Artificial Neural Network (ANN) models. The nano-adsorbents were synthesized using chemical precipitation method and characterized by using scanning electron microscope with elemental detection sensor (SEM-EDS) and atomic force microscope (AFM). Maximum %RBOD (96.71 and 87.56%) and %RCOD (90.48 and 82.10%) for CZnO and CTiO2 nano-adsorbents were obtained at adsorbent dosage of 1.25 mg/L, initial biological oxygen demand (BOD) and chemical oxygen demand (COD) concentration of 100 and 200 mg/L, pH of 7.0 and 2.00, contact time of 100 and 60 min, respectively. The results obtained for both the nano-adsorbents were subject to RSM and ANN models for determination of goodness of fit in terms of sum of square errors (SSE), root mean square error (RMSE), R2 and Adj. R2, respectively. The well trained ANN model was found superior over RSM in prediction of the treatment effect. Hence, the developed CZnO and CTiO2 nano-adsorbents could be effectively used for dairy industry wastewater treatment. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 0273-1223 1996-9732 |
| Relation: | http://wst.iwaponline.com/content/83/5/1250; https://doaj.org/toc/0273-1223; https://doaj.org/toc/1996-9732 |
| DOI: | 10.2166/wst.2021.035 |
| URL الوصول: | https://doaj.org/article/644cd4cf6e044e24aa4cf30f9eb137b3 |
| رقم الأكسشن: | edsdoj.644cd4cf6e044e24aa4cf30f9eb137b3 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 02731223 19969732 |
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| DOI: | 10.2166/wst.2021.035 |