Computer models have been widely used to predict the chromatographic behaviour of liquid chromatography systems. With the introduction of mass spectrometric detection and the use of lower mobile phase flow rates with conventional LC equipment, the influence of the dwell volume on the shape of the gradient curve becomes an issue in predicting the retention times. A new straight forward algorithm is proposed for the modelling of retention times in reversed-phase LC, taking the effect of the dwell volume on the gradient shape into account. The results show that the dwell volume has a large effect at lower flow rates and on the retention times of the analytes eluting at the end of fast gradient curves. The proposed model is able to make reliabl...
This paper describes an approach to rapidly and easily calculate the linear solvent strength paramet...
The work carried out on the linear pH-gradient is critically reviewed in combination with the develo...
For the first time, the performance of a generalised artificial neural network (ANN) approach for th...
Computer models have been widely used to predict the chromatographic behaviour of liquid chromatogra...
New practical algorithm for modelling retention times in gradient reversed-phase high-performance li...
A new numerical emulation algorithm was established to calculate retention parameters in RP-HPLC wit...
Identification of small molecules by liquid chromatography-mass spectrometry (LC-MS) can be greatly ...
Study on the retention equation for protein in RPLC can contribute to optimizing gradient conditions...
Linear gradient programs are very frequently used in reversed phase liquid chromatography to enhance...
The linear solvent strength model was used to predict coverage in online comprehensive two-dimension...
Recent applications of retention modelling in liquid chromatography (2015–2020) are comprehensively ...
Quantitative Structure-Retention Relationships (QSRR) methodology combined with the Hydrophobic Subt...
A great deal of high performance liguid chromatographic (HPLC) fingerprints of complex samples which...
The hydrophobic subtraction model (HSM) combined with quantitative structure-retention relationships...
The validity of a method for characterizing stationary phases for reversed-phase liq. chromatog., ba...
This paper describes an approach to rapidly and easily calculate the linear solvent strength paramet...
The work carried out on the linear pH-gradient is critically reviewed in combination with the develo...
For the first time, the performance of a generalised artificial neural network (ANN) approach for th...
Computer models have been widely used to predict the chromatographic behaviour of liquid chromatogra...
New practical algorithm for modelling retention times in gradient reversed-phase high-performance li...
A new numerical emulation algorithm was established to calculate retention parameters in RP-HPLC wit...
Identification of small molecules by liquid chromatography-mass spectrometry (LC-MS) can be greatly ...
Study on the retention equation for protein in RPLC can contribute to optimizing gradient conditions...
Linear gradient programs are very frequently used in reversed phase liquid chromatography to enhance...
The linear solvent strength model was used to predict coverage in online comprehensive two-dimension...
Recent applications of retention modelling in liquid chromatography (2015–2020) are comprehensively ...
Quantitative Structure-Retention Relationships (QSRR) methodology combined with the Hydrophobic Subt...
A great deal of high performance liguid chromatographic (HPLC) fingerprints of complex samples which...
The hydrophobic subtraction model (HSM) combined with quantitative structure-retention relationships...
The validity of a method for characterizing stationary phases for reversed-phase liq. chromatog., ba...
This paper describes an approach to rapidly and easily calculate the linear solvent strength paramet...
The work carried out on the linear pH-gradient is critically reviewed in combination with the develo...
For the first time, the performance of a generalised artificial neural network (ANN) approach for th...