کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5765858 1627008 2017 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Predicting the capability of carboxymethyl cellulose-stabilized iron nanoparticles for the remediation of arsenite from water using the response surface methodology (RSM) model: Modeling and optimization
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات فرآیندهای سطح زمین
پیش نمایش صفحه اول مقاله
Predicting the capability of carboxymethyl cellulose-stabilized iron nanoparticles for the remediation of arsenite from water using the response surface methodology (RSM) model: Modeling and optimization
چکیده انگلیسی


- Synthesis of carboxymethyl cellulose-stabilized iron nanoparticles for the removal of arsenite was done
- The investigation is focused on the carboxymethyl cellulose-stabilized iron nanoparticles ability to removal arsenite.
- Operational parameters involved in arsenite in the removal of arsenite by carboxymethyl cellulose-stabilized iron nanoparticles are discussed.

This study aimed to investigate the feasibility of carboxymethyl cellulose-stabilized iron nanoparticles (C-nZVI) for the removal of arsenite ions from aqueous solutions. Iron nanoparticles and carboxymethyl cellulose-stabilized iron nanoparticles were freshly synthesized. The synthesized nanomaterials had a size of 10 nm approximately. The transmission electron microscope (TEM) images depicted bulkier dendrite flocs of non-stabilized iron nanoparticles. It described nanoscale particles as not discrete resulting from the aggregation of particles. The scanning electron microscopy (SEM) image showed that C-nZVI is approximately discrete, well-dispersed and an almost spherical shape. The energy dispersive x-ray spectroscopy (EDAX) and X-ray diffraction (XRD) spectrum confirmed the presence of Fe0 in the C-nZVI composite. The central composite design under the Response Surface Methodology (RSM) was employed in order to investigate the effect of independent variables on arsenite removal and to determine the optimum condition. The reduced full second-order model indicated a well-fitted model since the experimental values were in good agreement with it. Therefore, this model is used for the prediction and optimization of arsenite removal from water. The maximum removal efficiency was estimated to be 100% when all parameters are considered simultaneously. The predicted optimal conditions for the maximum removal efficiency were achieved with initial arsenite concentration, 0.68 mg L− 1; C-nZVI, 0.3 (g L− 1); time, 31.25 (min) and pH, 5.2.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Contaminant Hydrology - Volume 203, August 2017, Pages 85-92
نویسندگان
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