Literature DB >> 21211802

Probabilistic model for immiscible separations and extractions (ProMISE).

Joost de Folter1, Ian A Sutherland.   

Abstract

Chromatography models, liquid-liquid models and specifically Counter-Current Chromatography (CCC) models are usually either iterative, or provide a final solution for peak elution. This paper describes providing a better model by finding a more elemental solution. A completely new model has been developed based on simulating probabilistic units. This model has been labelled ProMISE (probabilistic model for immiscible phase separations and extractions), and has been realised in the form of a computer application, interactively visualising the behaviour of the units in the CCC process. It does not use compartments or cells like in the Craig based models, nor is it based on diffusion theory. With this new model, all the CCC flow modes can be accurately predicted. The main advantage over the previously developed model, is that it does not require a somewhat arbitrary number of steps or theoretical plates, and instead uses an efficiency factor. Furthermore, since this model is not based on compartments or cells like the Craig model, and is therefore not limited to a compartment or cell nature, it allows for an even greater flexibility.
Copyright © 2010 Elsevier B.V. All rights reserved.

Mesh:

Year:  2010        PMID: 21211802     DOI: 10.1016/j.chroma.2010.12.079

Source DB:  PubMed          Journal:  J Chromatogr A        ISSN: 0021-9673            Impact factor:   4.759


  3 in total

1.  Recent progress on countercurrent chromatography modeling.

Authors:  Fengkang Wang; Yoichiro Ito; Yun Wei
Journal:  J Liq Chromatogr Relat Technol       Date:  2015       Impact factor: 1.312

Review 2.  Countercurrent Separation of Natural Products: An Update.

Authors:  J Brent Friesen; James B McAlpine; Shao-Nong Chen; Guido F Pauli
Journal:  J Nat Prod       Date:  2015-07-15       Impact factor: 4.050

3.  Countercurrent chromatographic fractionation followed by gas chromatography/mass spectrometry identification of alkylresorcinols in rye.

Authors:  Tim Hammerschick; Tim Wagner; Walter Vetter
Journal:  Anal Bioanal Chem       Date:  2020-10-10       Impact factor: 4.142

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.