Type: Package
Title: Adsorption Isotherm Model Fitting
Version: 0.1.0
Author: Debopam Rakshit [aut, cre], Arkaprava Roy [aut], K. M. Manjaiah [aut], Siba Prasad Datta [aut], Ritwika Das [aut]
Maintainer: Debopam Rakshit <rakshitdebopam@yahoo.com>
Description: The Langmuir and Freundlich adsorption isotherms are pivotal in characterizing adsorption processes, essential across various scientific disciplines. Proper interpretation of adsorption isotherms involves robust fitting of data to the models, accurate estimation of parameters, and efficiency evaluation of the models, both in linear and non-linear forms. For researchers and practitioners in the fields of chemistry, environmental science, soil science, and engineering, a comprehensive package that satisfies all these requirements would be ideal for accurate and efficient analysis of adsorption data, precise model selection and validation for rigorous scientific inquiry and real-world applications. Details can be found in Langmuir (1918) <doi:10.1021/ja02242a004> and Giles (1973) <doi:10.1111/j.1478-4408.1973.tb03158.x>.
Encoding: UTF-8
License: GPL-3
Imports: AICcmodavg, ggplot2, nls2, stats
NeedsCompilation: no
RoxygenNote: 7.3.1
Packaged: 2024-07-22 10:51:29 UTC; Debopam
Repository: CRAN
Date/Publication: 2024-07-26 20:00:06 UTC

Freundlich Linear Model

Description

This model will fit the adsorption data to the linear form of the Freundlich equation and will give the estimates of the Freundlich parameters, namely "kf" and "1/n" while evaluating the performance efficiency of the linear model of Freundlich through several error functions.

Usage

FLM (ce, qe)

Arguments

ce

Equilibrium concentration of the adsorbate in the solution

qe

Amount adsorbed

Value

References

Examples

ce <- c(0.025, 0.04, 0.055, 0.099, 0.139, 0.402, 1.999, 11.336)
qe <- c(17.21, 35.42, 51.238, 72.659, 89.268, 182.21, 345.29, 634.231)
m.fit <- FLM (ce, qe)

Freundlich Nonlinear Model

Description

This model will fit the adsorption data to the nonlinear form of the Freundlich equation and will give the estimates of the Freundlich parameters, namely "kf" and "1/n" while evaluating the performance efficiency of the nonlinear model of Freundlich through several error functions.

Usage

FNLM (ce, qe)

Arguments

ce

Equilibrium concentration of the adsorbate in the solution

qe

Amount adsorbed

Value

References

Examples

ce <- c(0.025, 0.04, 0.055, 0.099, 0.139, 0.402, 1.999, 11.336)
qe <- c(17.21, 35.42, 51.238, 72.659, 89.268, 182.21, 345.29, 634.231)
m.fit <- FNLM (ce, qe)

Langmuir Linear Model

Description

This model will fit the adsorption data to the linear form of the Langmuir equation and will give the estimates of the Langmuir parameters, namely "b" and "k" while evaluating the performance efficiency of the linear model of Langmuir through several error functions.

Usage

LLM(ce, qe)

Arguments

ce

Equilibrium concentration of the adsorbate in the solution

qe

Amount adsorbed

Value

References

Examples

ce <- c(0.025, 0.04, 0.055, 0.099, 0.139, 0.402, 1.999, 11.336)
qe <- c(17.21, 35.42, 51.238, 72.659, 89.268, 182.21, 345.29, 634.231)
m.fit <- LLM (ce, qe)

Langmuir Nonlinear Model

Description

This model will fit the adsorption data to the nonlinear form of the Langmuir equation and will give the estimates of the Langmuir parameters, namely "b" and "k" while evaluating the performance efficiency of the nonlinear model of Langmuir through several error functions.

Usage

LNLM (ce, qe)

Arguments

ce

Equilibrium concentration of the adsorbate in the solution

qe

Amount adsorbed

Value

References

Examples

ce <- c(0.025, 0.04, 0.055, 0.099, 0.139, 0.402, 1.999, 11.336)
qe <- c(17.21, 35.42, 51.238, 72.659, 89.268, 182.21, 345.29, 634.231)
m.fit <- LNLM (ce, qe)