The two retention models, the linear solvent strength model (LSS) and the quadratic relationship, in addition to artificial neural network (ANN) approach, were compared in their ability to predict the retention behaviour of common cations (Li, Na, NH4, K, Mg and Ca) in isocratic ion chromatography using the methanesulfonic acid (MSA) eluent. Over wide variations in the MSA concentration, the quadratic model shows a quite good prediction power. LSS can be used only for monovalent cations and in the proximity of the experimental design point. ANN fails to predict the retention for the data not included in the training set. To find the optimal conditions in the experimental design, the normalized resolution product as a chromatographic objecti...
Three ion chromatography (IC) retention models, namely the linear solvent strength model (LSSM), emp...
A new software package, Virtual Column 2, is described for the simulation and optimization of the se...
The separation by ion-interaction chromatography (IIC) of metal complexes having single and double c...
The two retention models, the linear solvent strength model (LSS) and the quadratic relationship, in...
The aim of this work was to develop an empirical model for retention of inorganic anions (fluoride, ...
This work deals with the optimisation of the eluent composition for the separation of anions using ...
Abstract: The aim of this work is comparison of the prediction power of multiple linear regression a...
The feasibility of using an artificial neural network (ANN) to predict the retention times of anions...
An Artificial Neural Network (ANN) was investigated as a method to model retention times of anions i...
Interpretive retention modeling was utilized to optimize the isocratic ion chromatographic (IC) sepa...
Quantitative Structure-Retention Relationships (QSRRs) represent a popular technique to predict the ...
A series of mathematical models describing analyte retention behaviour in non-suppressed ion chromat...
Seven theoretical retention models, namely the linear solvent strength model (using the dominant equ...
Three ion chromatography (IC) retention models, namely the linear solvent strength model (LSSM), emp...
A new software package, Virtual Column 2, is described for the simulation and optimization of the se...
The separation by ion-interaction chromatography (IIC) of metal complexes having single and double c...
The two retention models, the linear solvent strength model (LSS) and the quadratic relationship, in...
The aim of this work was to develop an empirical model for retention of inorganic anions (fluoride, ...
This work deals with the optimisation of the eluent composition for the separation of anions using ...
Abstract: The aim of this work is comparison of the prediction power of multiple linear regression a...
The feasibility of using an artificial neural network (ANN) to predict the retention times of anions...
An Artificial Neural Network (ANN) was investigated as a method to model retention times of anions i...
Interpretive retention modeling was utilized to optimize the isocratic ion chromatographic (IC) sepa...
Quantitative Structure-Retention Relationships (QSRRs) represent a popular technique to predict the ...
A series of mathematical models describing analyte retention behaviour in non-suppressed ion chromat...
Seven theoretical retention models, namely the linear solvent strength model (using the dominant equ...
Three ion chromatography (IC) retention models, namely the linear solvent strength model (LSSM), emp...
A new software package, Virtual Column 2, is described for the simulation and optimization of the se...
The separation by ion-interaction chromatography (IIC) of metal complexes having single and double c...