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A commercial software was used to build up retention models.
This mismatch is more serious in retention models at low methanol fractions.
Accurate retention time predictions (<0.5%) were achievable using non-linear retention models (3 × 3).
The two concepts of micelle formation (pseudo-phase and mass-action) could be the basis of retention models in micellar liquid chromatography (MLC).
The suitability of three different retention models to predict the retention times of poly ethylene glycol)s (PEGs) in gradient and isocratic chromatography was investigated.
Significant differences (p < 0.05) between most of the coefficients in the retention models were observed when comparing models from set and actual conditions.
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MATLAB Neural Networks ToolBox was not adequate for application to retention modelling in this particular case.
The polarization relaxation characteristics were investigated in details based on Lou's polarization retention model.
Therefore the authors adopted it for retention modelling by programming in MATLAB metalanguage.
Secondly, a generally applicable retention model was established, based on chromatographic retention data (log k) acquired for 76 model compounds.
The retention time prediction model was constructed by modification from past respectable knowledge of retention modeling against ternary solvent strength changes.
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