2004
DOI: 10.2116/analsci.20.1403
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Characterization of the Microscopic Surface Structure of the Octadecylsilica Stationary Phase Using a Molecular-Dynamics Simulation

Abstract: Liquid chromatography (LC) is one of the most powerful techniques for the separation of various nonvolatile organic compounds. Nevertheless, the separation mechanism in LC has not yet been completely clarified. It is well known that the retention in LC is generated by a dispersion of the analyte between the mobile phase and the stationary phase. Especially, the intermolecular interaction of the analyte and the stationary phase ligand molecule plays a very important role during the retention process in LC. Ther… Show more

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Cited by 24 publications
(21 citation statements)
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“…The retention and separation mechanism of aromatic compounds including a variety of polycyclic aromatic hydrocarbons (PAHs) and pyrazines have been studied. [4][5][6][7][8][9][10][11][12][13][14][15][16][17] On the basis of actual retention measurements for pyrazines in several experimental conditions, a theoretical interpretation and the subsequent retention prediction were also studied in our previous work, 17 where the retention prediction models for pyrazine and alkylpyrazines were developed using multiple linear regression (MLR) and artificial neural networks (ANNs). During the study, the retention of these compounds was carefully determined in various conditions, including a variety of mobile phase conditions and column temperatures.…”
Section: Introductionmentioning
confidence: 99%
“…The retention and separation mechanism of aromatic compounds including a variety of polycyclic aromatic hydrocarbons (PAHs) and pyrazines have been studied. [4][5][6][7][8][9][10][11][12][13][14][15][16][17] On the basis of actual retention measurements for pyrazines in several experimental conditions, a theoretical interpretation and the subsequent retention prediction were also studied in our previous work, 17 where the retention prediction models for pyrazine and alkylpyrazines were developed using multiple linear regression (MLR) and artificial neural networks (ANNs). During the study, the retention of these compounds was carefully determined in various conditions, including a variety of mobile phase conditions and column temperatures.…”
Section: Introductionmentioning
confidence: 99%
“…Previous simulations of the more hydrophobic C 18 chains in neat water found the core bonded-phase region to be solvent-depleted, 14,15,18 probably because the highly disordered and partially backfolded C 18 chains form a hydrocarbon layer at the interface that is largely impenetrable to water. In a previous simulation of a C 8 -bonded phase, penetration of water molecules up to 0.6 nm into the bonded-phase in neat water and water/acetonitrile 70/30 (v/v) was observed, but this model did not include an explicit silica surface.…”
Section: Solvent and Ion Distributionmentioning
confidence: 99%
“…Numerous numbers of reports on the separation mechanism have been published on the basis of the retention analysis, however, there is still a long way to get the complete explanations of the whole separation mechanism. This is because many parameters are controlling the retention generated by a molecular recognition process in typical LC separations [5][6][7][8].…”
Section: Simentioning
confidence: 99%
“…Development of novel fibrous extraction/separation media having different chemical structures and then different functionalities on the surface could be realized in the near future based on the concept of molecular shape recognition [3][4][5][6][7][8] and the systematic retention mechanism analysis with a help of various modern computational data calculations in LC [106][107][108][109][110][111][112][113][114][115][116][117][118]. Miniaturization of packed columns in GC [119][120][121][122][123] is also possible for high speed analysis with a unique selectivity but without a loss of sample loading capacity.…”
Section: Future Prospectivementioning
confidence: 99%