| Type: | Package |
| Title: | Suite for Heat-Related Adsorption Knowledge and Thermodynamic Inference |
| Description: | A comprehensive framework for quantifying the fundamental thermodynamic parameters of adsorption reactions—changes in the standard Gibbs free energy (delta G), enthalpy (delta H), and entropy (delta S)—is essential for understanding the spontaneity, heat effects, and molecular ordering associated with sorption processes. By analysing temperature-dependent equilibrium data, thermodynamic interpretation expands adsorption studies beyond conventional isotherm fitting, offering deeper insight into underlying mechanisms and surface–solute interactions. Such an approach typically involves evaluating equilibrium coefficients across multiple temperatures and non-temperature treatments, deriving thermodynamic parameters using established thermodynamic relationships, and determining delta G as a temperature-specific indicator of adsorption favourability. This analytical pathway is widely applicable across environmental science, soil science, chemistry, materials science, and engineering, where reliable assessment of sorption behaviour is critical for examining contaminant retention, nutrient dynamics, and the behaviour of natural and engineered surfaces. By focusing specifically on thermodynamic inference, this framework complements existing adsorption isotherm-fitting packages such as “AdIsMF” https://CRAN.R-project.org/package=AdIsMF <doi:10.32614/CRAN.package.AdIsMF>, and strengthens the scientific basis for interpreting adsorption energetics in both research and applied contexts. Details can be found in Roy et al. (2025) <doi:10.1007/s11270-025-07963-7>. |
| Author: | Arkaprava Roy [aut], Debopam Rakshit [aut, cre], Siba Prasad Datta [aut], Kanchikeri Math Manjaiah [aut], Mandira Barman [aut], Debashis Mandal [aut] |
| Maintainer: | Debopam Rakshit <rakshitdebopam@yahoo.com> |
| Version: | 0.1.0 |
| Encoding: | UTF-8 |
| License: | GPL-3 |
| Imports: | dplyr, stats, magrittr |
| NeedsCompilation: | no |
| RoxygenNote: | 7.3.3 |
| Packaged: | 2025-11-28 06:43:41 UTC; Debopam |
| Repository: | CRAN |
| Date/Publication: | 2025-12-03 20:40:08 UTC |
Dimensionless Distribution Coefficient
Description
This function computes the natural logarithm of dimensionless distribution coefficient (Kd) from adsorption equilibrium data across temperatures, and non-temperature treatments, if any. This function prepares the foundational input required for thermodynamic parameter analysis.
Usage
LnKd(V, m, MW.Ad, M.Ad, Non_T_trt, T_trt, Rep, IGC, Ce)
Arguments
V |
Volumn of water in litre |
m |
Mass of the adsorbent in gram |
MW.Ad |
Molar weight of the adsorbate in gram per mole |
M.Ad |
Molarity of the solvent in mole per litre(55.5 for water) |
Non_T_trt |
Non-temperature treatment |
T_trt |
Temperature treatment |
Rep |
Replication |
IGC |
Initial graded concentrations of the adsorbate in milligram per litre |
Ce |
Equilibrium concentration of the adsorbate in milligram per litre |
Value
qe_i: Absorbed amount in milligram per kg
Kd_i: Distribution coefficient
lnKd_i: Natural logarithm of Kd
Mean_lnkd: Average of lnKd
References
Roy, A., Manjaiah, K. M., Datta, S. P., Rakshit, D., Barman, M., Ray, P., Golui, D., Raza, M. B., Tigga, P., Mondal, S., Vishwanath, Meena, S., & Meena, P. (2025). Effect of Low-Molecular-Weight Organic Acids and Silicon on Arsenic Adsorption and Desorption in a Paddy Soil of Bengal Delta Plain: Insights from Thermodynamics and Equilibrium Modeling. Water, Air, & Soil Pollution, 236(6), 344. https://doi.org/10.1007/s11270-025-07963-7
Examples
V <- 0.02 # in litre
m <- 2 # in gram
MW.Ad <- 75
M.Ad <- 55.5
Non_T_trt <- c(0,0,0,0,0,0,1,1,1,1,1,1)
T_trt <- c(1,1,1,2,2,2,1,1,1,2,2,2)
Rep <- c(1,2,3,1,2,3,1,2,3,1,2,3)
IGC <- c(2,4)
Ce2 <- c(0.030, 0.031, 0.032, 0.033, 0.034, 0.035, 0.030, 0.031, 0.032, 0.033, 0.034, 0.035)
Ce4 <- c(0.030, 0.031, 0.032, 0.033, 0.034, 0.035, 0.030, 0.031, 0.032, 0.033, 0.034, 0.035)
Ce <- data.frame(Ce2, Ce4)
my.LnKd<- LnKd(V, m, MW.Ad, M.Ad, Non_T_trt, T_trt, Rep, IGC, Ce)
Estimation of Slope and Intercept
Description
Generates slope and intercept values from temperature-dependent lnKd data using linear regression, and the corresponding coefficient of determination (R^2) values. These coefficients form the basis for calculating the thermodynamic parameters, providing a simple and transparent bridge between experimental equilibrium measurements and thermodynamic interpretation.
Usage
Slope_Intercept(lnKd, Temp)
Arguments
lnKd |
Natural logarithm of distribution coefficient |
Temp |
Temperature in Kelvin |
Value
Intercept: Intercept of the fitted line
Slope: Slope of the fitted line
R_square: Coefficient of determination of the fitted line
References
Gouaich, I., Bestani, B., Bouberka, Z., Srenscek-Nazza, J., Michalkiewicz, B., Benzekri-Benallou, M., Boucherdoud, A., and Benderdouche, N. (2023). Characterization of a low-cost Eucalyptus camaldulensis leaves based activated carbon for pharmaceutical residues removal from aqueous solutions. Desalination and Water Treatment, 296, 19–31. https://doi.org/10.5004/dwt.2023.29602
Examples
lnKd <- c(5.01, 5.02)
Temp <- c (298, 303)
my.SI<- Slope_Intercept(lnKd, Temp)
Estimation of Thermodynamic Parameters
Description
Calculates delta H, delta S, and delta G across temperature and non-temperature treatments using regression-derived slope and intercept values, integrating van’t Hoff and Gibbs-based relationships. This function assesses spontaneity, energetic favourability, and system randomness, providing a comprehensive thermodynamic profile for interpreting adsorption energetics.
Usage
Thermo_parameters(lnKd, Temp, Slope, Intercept)
Arguments
lnKd |
Natural logarithm of distribution coefficient corresponding to each initial graded concentrations |
Temp |
Temperature in Kelvin |
Slope |
Estimated slope of the fitted line |
Intercept |
Estimated intercept of the fitted line |
Value
Delta_H: Change in the standard enthalpy
Delta_S: Change in the standard entropy
Delta_G: Change in the standard Gibbs free energy
Descriptive: Mean and standard error of the thermodynamic parameters
References
Roy, A., Manjaiah, K. M., Datta, S. P., Rakshit, D., Barman, M., Ray, P., Golui, D., Raza, M. B., Tigga, P., Mondal, S., Vishwanath, Meena, S., & Meena, P. (2025). Effect of Low-Molecular-Weight Organic Acids and Silicon on Arsenic Adsorption and Desorption in a Paddy Soil of Bengal Delta Plain: Insights from Thermodynamics and Equilibrium Modeling. Water, Air, & Soil Pollution, 236(6), 344. https://doi.org/10.1007/s11270-025-07963-7
Yi, Z., Yao, J., Zhu, M., Chen, H., Wang, F., & Liu, X. (2016). Kinetics, equilibrium, and thermodynamics investigation on the adsorption of lead (II) by coal-based activated carbon. SpringerPlus, 5(1), 1160. https://doi.org/10.1186/s40064-016-2839-4
Examples
lnKd <- c(7,8)
Temp <- 298
Slope <- c(-180, -200)
Intercept <- c(5, 6)
my.tp <- Thermo_parameters(lnKd, Temp, Slope, Intercept)