The stochastic model of chromatography describes the separation process at the molecular level in probabilistic terms. Unfortunately, terms such as "stochastic" or "random" frighten chromatographers away from the use of this model. Nevertheless, this microscopic model is rather straightforward to comprehend, and it can furnish direct answers when one tries to understand the development of chromatographic peaks. In this study, we summarize briefly the basic concepts of the stochastic model and with an application to a simple reversed-phase high performance liquid chromatography (HPLC) separation, we show that it can be used easily to estimate the fundamental characteristics of the separation process.
|Number of pages||6|
|Journal||LC-GC North America|
|Publication status||Published - Jul 1 2004|
ASJC Scopus subject areas
- Analytical Chemistry