Predicting intraparticle diffusivity as function of stationary phase characteristics in preparative chromatography.
J Chromatogr A
; 1613: 460688, 2020 Feb 22.
Article
in En
| MEDLINE
| ID: mdl-31813564
ABSTRACT
Diffusion inside pores is the rate limiting step in many preparative chromatographic separations and a key parameter for process design in weak interaction aqueous chromatographic separations employed in food and bio processing. This work aims at relating diffusion inside porous networks to properties of stationary phase and of diffusing molecules. Intraparticle diffusivities were determined for eight small molecules in nine different stationary phases made from three different backbone materials. Measured intraparticle diffusivities were compared to the predictive capability of the correlation by Mackie and Meares and the parallel pore model. All stationary phases were analyzed for their porosity, apparent pore size distribution and tortuosity, which are input parameters for the models. The parallel pore model provides understanding of the occurring phenomena, but the input parameters were difficult to determine experimentally. The model predictions of intraparticle diffusion were of limited accuracy. We show that prediction can be improved when combining the model of Mackie and Meares with the fraction of accessible pore volume. The accessible pore volume fraction can be determined from inverse size exclusion chromatographic measurements. Future work should further challenge the improved model, specifically widening the applicability to greater accessible pore fractions (> 0.7) with corresponding higher intraparticle diffusivities (Dp/Dm > 0.2). A database of intraparticle diffusion and stationary phase pore property measurements is supplied, to contribute to general understanding of the relationship between intraparticle diffusion and pore properties.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Chromatography, Gel
Type of study:
Prognostic_studies
/
Risk_factors_studies
Language:
En
Journal:
J Chromatogr A
Year:
2020
Document type:
Article