2013
DOI: 10.1016/j.cej.2013.04.101
|View full text |Cite
|
Sign up to set email alerts
|

Modeling of lead (II) biosorption by residue of allspice in a fixed-bed column

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

4
35
1

Year Published

2015
2015
2021
2021

Publication Types

Select...
8
1

Relationship

0
9

Authors

Journals

citations
Cited by 151 publications
(40 citation statements)
references
References 34 publications
4
35
1
Order By: Relevance
“…The total adsorbed MB quantity (q total ) in mg for a given inlet concentration is equal to the flow rate and the area under the plot of the adsorbed MB dye concentration C ads (C ads = C o -C t ), where C o and C t (mg L -1 ) are the influent and effluent dye concentrations, respectively, versus time (min), and is calculated as follows [31]:…”
Section: Theoretical Backgroundmentioning
confidence: 99%
“…The total adsorbed MB quantity (q total ) in mg for a given inlet concentration is equal to the flow rate and the area under the plot of the adsorbed MB dye concentration C ads (C ads = C o -C t ), where C o and C t (mg L -1 ) are the influent and effluent dye concentrations, respectively, versus time (min), and is calculated as follows [31]:…”
Section: Theoretical Backgroundmentioning
confidence: 99%
“…The steepness of curves determines the column efficiency to reach saturation. The steeper curves have longer mass transfer zone which is necessary for the better column performance (Naja and Volesky 2008;Cruz-Olivares et al 2013). The total volume of the effluent treated and the fractional bed utilization was more at lower concentration because the reason for this is that at lower concentration the feed solution flows inside the column for a longer residence time.…”
Section: Packed-bed Adsorption Experimentsmentioning
confidence: 99%
“…Scalar matrix sy for each output for 500 samples of the Latin hypercube can be composed as: (6) θ i , ε i , d 0 and d j denote probabilistic parameter sampling for i = 500 elements Latin Hypercube, probabilistic regression error for i = 500 elements of the Latin Hypercube, linear regression coefficient and regression coefficients, respectively. The indices i (1-500) and j (1-7) stand for total number of Latin-Hypercube samples and total number of model parameters, respectively.…”
Section: Uncertainty and Sensitivity Analysesmentioning
confidence: 99%
“…Mathematical modeling in process development is used to bring a measure of order to observation and strengthen prediction [4][5][6].…”
Section: Introductionmentioning
confidence: 99%