Determination of adsorption isotherms in supercritical fluid chromatography

Enmark, Martin; Forssén, Patrik; Samuelsson, Jörgen; Fornstedt, Torgny

doi:10.1016/j.chroma.2013.09.007

Cited by 32 publications

(23 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The injection profiles were experimentally determined by directly connecting the outlet of the injector to the detector. To simplify this study, the Langmuir adsorption isotherm model was applied instead of the bi-Langmuir models that were used in the previous study [2]. The adsorption parameters for the first component were a 1 = 4.9,…”

Section: Methodsmentioning

confidence: 99%

“…The calculations were conducted using input parameters from experiments described in another study [2]. In short, the adsorption isotherms and van Deemter curves were determined from the separation of omeprazole enantiomers using pure methanol as eluent on an AmyCoat column (250 × 4.6 mm, 5 lm nominal particle diameter) from Eka Chemicals (Bohus, Sweden).…”

Section: Methodsmentioning

confidence: 99%

“…For this purpose, adsorption isotherm parameters were chosen, determined using the inverse method and the Rouchon algorithm for the model system described in [2]. Because of high column efficiency on the used 10 lm/25 cm column, the accuracy of this determination is high.…”

Section: Data Setmentioning

confidence: 99%

“…Here, it is assumed that the separation problem is to obtain a pure component from a purely racemic crude extract, and that this can be achieved in a single chromatographic unit operation. This model system is based on several published works regarding the chiral separation of omeprazole [1,2].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Highlighting Important Parameters Often Neglected in Numerical Optimization of Preparative Chromatography

et al. 2011

View full text Add to dashboard Cite

When a chromatographic separation process is numerically optimized, a number of input parameters to the column model need to be accurately determined, and the accuracy will affect the reliability of the predicted optimal operational conditions. Furthermore, the numerical accuracy of the solution to the column model will have similar impact. The input parameters holdup volume, injection profiles, and the selection of an algorithm for solving the column model were investigated. Errors in parameters or a numerical error in the solution of the column model were found to lead to a prediction of a product fraction where the set purity and/ or yield requirements are not met.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Data Setmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Highlighting Important Parameters Often Neglected in Numerical Optimization of Preparative Chromatography

et al. 2011

View full text Add to dashboard Cite

show abstract

“…The outcome of a chromatographic separation is strongly dependent on the adsorption isotherms of the solutes, since they dictate the separation factors and saturation capacities, i.e., how much solute can be adsorbed. Therefore, estimation of adsorption isotherms is crucial and also gives deeper understanding of the separation processes [3,4,9,12,14,31].…”

Section: Introductionmentioning

confidence: 99%

A modified coupled complex boundary method for an inverse chromatography problem

Cheng

Lin

Zhang

et al. 2017

Journal of Inverse and Ill-Posed Problems

View full text Add to dashboard Cite

Adsorption isotherms are the most important parameters in rigorous models of chromatographic processes. In this paper, in order to recover adsorption isotherms, we consider a coupled complex boundary method (CCBM), which was previously proposed for solving an inverse source problem [2]. With CCBM, the original boundary fitting problem is transferred to a domain fitting problem. Thus, this method has advantages regarding robustness and computation in reconstruction. In contrast to the traditional CCBM, for the sake of the reduction of computational complexity and computational cost, the recovered adsorption isotherm only corresponds to the real part of the solution of a forward complex initial boundary value problem. Furthermore, we take into account the position of the profiles and apply the momentum criterion to improve the optimization progress. Using Tikhonov regularization, the well-posedness, convergence properties and regularization parameter selection methods are studied. Based on an adjoint technique, we derive the exact Jacobian of the objective function and give an algorithm to reconstruct the adsorption isotherm. Finally, numerical simulations are given to show the feasibility and efficiency of the proposed regularization method.

show abstract

Solvation processes on phenyl‐bonded stationary phases—The influence of polar functional groups

Bocian

Skoczylas

Gorynska

et al. 2016

J of Separation Science

View full text Add to dashboard Cite

A series of phenyl-bonded stationary phases with incorporated polar functional groups was subjected to an adsorption investigation. Measurement of acetonitrile and methanol adsorption was obtained using the minor disturbance method. It was observed that adsorption of organic solvent strongly depends on the presence of polar functional groups in the bonded phases that influence the hydrophobicity and polarity of the stationary phase surface. Additionally, relative adsorption of acetonitrile and methanol confirms earlier observations, that the presence of amine and amide groups in the stationary phase changes the relative elution strength of organic solvents. The heterogeneous surface of the stationary phase makes it possible to observe the competitiveness of the water and organic solvent adsorption.

show abstract

Determination of adsorption isotherms in supercritical fluid chromatography

Cited by 32 publications

References 42 publications

Highlighting Important Parameters Often Neglected in Numerical Optimization of Preparative Chromatography

Highlighting Important Parameters Often Neglected in Numerical Optimization of Preparative Chromatography

A modified coupled complex boundary method for an inverse chromatography problem

Solvation processes on phenyl‐bonded stationary phases—The influence of polar functional groups

Contact Info

Product

Resources

About