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Maryam Dolatabadi

Bio: Maryam Dolatabadi is an academic researcher from Shahid Sadoughi University of Medical Sciences and Health Services. The author has contributed to research in topics: Adsorption & Response surface methodology. The author has an hindex of 17, co-authored 37 publications receiving 756 citations. Previous affiliations of Maryam Dolatabadi include Mashhad University of Medical Sciences & Kerman Medical University.

Papers published on a yearly basis

Papers
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Journal ArticleDOI
TL;DR: In this article, the authors used Response Surface Methodology (RSM) to evaluate the main effects of parameters, their simultaneous interactions and quadratic effect to achieve the optimum condition for EC process with removal efficiency of 88.57% under optimal operating condition of pH 7.78.

156 citations

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TL;DR: In this paper, the authors focused on the removal of ciprofloxacin from hospital wastewater using electrocoagulation (EC) process by iron electrode and the kinetic and isotherms of adsorption were investigated.

130 citations

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TL;DR: In this paper, a feed-forward artificial neural network (ANN) and an adaptive neuro-fuzzy inference system (ANFIS) have been utilized to the prediction of adsorption potential of sawdust in simultaneous removal of a cationic dye and heavy metal ion from aqueous solution.

106 citations

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TL;DR: In this paper, a quadratic polynomial model was developed via response surface methodology (RSM), and the analysis of variance (ANOVA) was performed for evaluating the significance of the proposed assumptions.

78 citations


Cited by
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TL;DR: This review encompasses recent advancements, trends and challenges for natural biopolymers assembled from renewable resources for exploitation in the production of starch, cellulose, pectin, gum, alginate, chitin and chitosan-derived (nano)materials.

326 citations

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TL;DR: In this article, the authors focused on the removal of arsenic from water using iron-based materials, such as iron nanoparticles, layered double hydroxides (LDHs), zero-valent iron (ZVI), iron-doped activated carbon, iron-depleted polymer/biomass materials, and iron-containing combined metal oxides.
Abstract: Intensive research efforts have been pursued to remove arsenic (As) contamination from water with an intention to provide potable water to millions of people living in different countries. Recent studies have revealed that iron-based adsorbents, which are non-toxic, low cost, and easily accessible in large quantities, offer promising results for arsenic removal from water. This review is focused on the removal of arsenic from water using iron-based materials such as iron-based nanoparticles, iron-based layered double hydroxides (LDHs), zero-valent iron (ZVI), iron-doped activated carbon, iron-doped polymer/biomass materials, iron-doped inorganic minerals, and iron-containing combined metal oxides. This review also discusses readily available low-cost adsorbents such as natural cellulose materials, bio-wastes, and soils enriched with iron. Details on mathematical models dealing with adsorption, including thermodynamics, kinetics, and mass transfer process, are also discussed. For elucidating the adsorption mechanisms of specific adsorption of arsenic on the iron-based adsorbent, X-ray photoelectron spectroscopy (XPS) and X-ray absorption spectroscopy (XAS) are frequently used. Overall, iron-based adsorbents offer significant potential towards developing adsorbents for arsenic removal from water.

275 citations

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TL;DR: A review of the state-of-the-art of magnetic nanomaterials and biosorbents for the removal of contaminants from wastewater streams can be found in this paper.

190 citations

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TL;DR: In this article, a hollow Co3S4 was synthesized by using ZIF-67 as template and thioacetamide as sulfide reagent through a simple solvothermal method, and characterized by SEM, TEM, HRTEM, XRD, FT-IR, zeta potential measurement, TG, N2 adsorption-desorption and XPS analysis.

171 citations

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TL;DR: In this article, the authors reviewed the literature on CIP adsorption and identified key empirical findings on specific investigation domains, establish knowledge gaps and grey areas that could serve as a foundation for other investigations by researchers and predict future perspectives in the research area.

163 citations