2015
DOI: 10.1016/j.molliq.2015.02.029
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Adsorption of copper (II) using modified activated carbon prepared from Pomegranate wood: Optimization by bee algorithm and response surface methodology

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Cited by 108 publications
(39 citation statements)
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“…ANOVA, as shown in Table S2, was utilized to determine the adequacy of the predicted model. The second‐order polynomial model, considering the Fisher's test ( p < 0.05), suggested that most of the single, interaction, and quadratic factors had a significant impact at the significance level (≤0.05) . Lack‐of‐fit p ‐value of 0.1595 for MG and that of 0.2958 for MO validated the effectiveness of the model from statistical point.…”
Section: Resultsmentioning
confidence: 81%
“…ANOVA, as shown in Table S2, was utilized to determine the adequacy of the predicted model. The second‐order polynomial model, considering the Fisher's test ( p < 0.05), suggested that most of the single, interaction, and quadratic factors had a significant impact at the significance level (≤0.05) . Lack‐of‐fit p ‐value of 0.1595 for MG and that of 0.2958 for MO validated the effectiveness of the model from statistical point.…”
Section: Resultsmentioning
confidence: 81%
“…The production of activated carbon from agricultural by-products has received much attention from the scientific community as they are renewable, low-cost and environmentally friendly materials (Okman et al 2014). A large number of agricultural by-products, such as date stone (Danish et al 2014b), Acacia mangium wood (Danish et al 2011), cocoa shell (Ahmad et al 2012), waste tea (Auta and Hameed 2011), coffee husks (Oliveira et al 2009), pomegranate wood (Ghaedi et al 2015), mahogany sawdust (Malik 2003), rice husk (Malik 2003), corn cob (Sych et al 2012), and other materials have been successfully used for the production of low-cost activated carbon.…”
Section: Page 2 Of 11mentioning
confidence: 99%
“…Statistical experimental designs such as PBD and CCD have been successfully applied to optimize many bioprocesses (Rahimdokht et al, 2016;Sadhukhan et al, 2016), Response Surface Methodology (RSM) is a collection of mathematical and statistical techniques that is applied for the modeling and analysis of various processes in which the response of interest is influenced by several factors and the response is optimized (Ghaedi et al, 2015;Witek-Krowiak et al, 2014). The objective for the present work was to Screening the variables using statistical techniques, a Plackett-Burman design was used to study the effects of factors on the preparation of the active coal has the basis of oil shale in order to extract the most important ones.…”
Section: Elaboration Of Novel Adsorbent From Moroccan Oil Shale Usingmentioning
confidence: 99%