2022
DOI: 10.3390/met12101664
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Optimization of As(V) Removal by Dried Bacterial Biomass: Nonlinear and Linear Regression Analysis for Isotherm and Kinetic Modelling

Abstract: Arsenic occurrence and toxicity records in various industrial effluents have prompted researchers to find cost-effective, quick, and efficient methods for removing arsenic from the environment. Adsorption of As(V) onto dried bacterial biomass is proposed in the current work, which continues a line of previous research. Dried bacterial biomass of WS3 (DBB) has been examined for its potential to remove As(V) ions from aqueous solutions under various conditions. Under optimal conditions, an initial concentration … Show more

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Cited by 7 publications
(4 citation statements)
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“…The method of synthesis of carbon and its activation plays a role in the crystallinity. The orthorhombic crystalline peaks that appeared at 2θ 26.61º, 43.45º, 46.32º, 54.81º and 56.68º are relevant to (111), (100), ( 110), ( 222) and (211) planes, respectively [5,6,[12][13][14][15][16].…”
Section: Resultsmentioning
confidence: 99%
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“…The method of synthesis of carbon and its activation plays a role in the crystallinity. The orthorhombic crystalline peaks that appeared at 2θ 26.61º, 43.45º, 46.32º, 54.81º and 56.68º are relevant to (111), (100), ( 110), ( 222) and (211) planes, respectively [5,6,[12][13][14][15][16].…”
Section: Resultsmentioning
confidence: 99%
“…More than 100 million people in the world are consuming arseniccontaminated water that contains more than the threshold limit of arsenic. The toxicity of As(III) is 30-70 times more than As(V) as As(III) interacts with thiol (-SH) groups of enzymes and inhibits enzyme action, ATP synthesis with replacement of the phosphate group, gastrointestinal problems, anaemia, skin cancer/skin diseases and neurological defects [6].…”
Section: Introductionmentioning
confidence: 99%
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“…The best-fit model is selected based on the size of the coefficient of determination. The best match is often considered to be the model with the greatest coefficient of determination value (R 2 ) [39]. Additionally, the fit for the removal data is improved by reducing the numerical value of the error functions for a particular model.…”
Section: Analytical Error Analysismentioning
confidence: 99%