4.6 Article

Separation of multicomponent aromatic/aliphatic mixtures by simulated moving bed adsorption: Modeling and experiments

Journal

AICHE JOURNAL
Volume 67, Issue 10, Pages -

Publisher

WILEY
DOI: 10.1002/aic.17375

Keywords

adsorption; aliphatics; aromatics; modeling; simulated moving bed

Funding

  1. ExxonMobil Research and Engineering Company

Ask authors/readers for more resources

The study focuses on the efficient separation of multicomponent feeds using simulated moving bed (SMB) adsorption, with a particular emphasis on aromatics and aliphatics. By progressively adding components and refining parameters, a robust model was developed to predict the influence of key operating parameters on separation results, which was validated through experiments in a mini-plant. The research also established conditions for clear separation of each mixture.
Simulated moving bed (SMB) adsorption has potential for efficient separation of many valuable chemical mixtures, but considerably less attention has been devoted to multicomponent feeds relative to binary mixtures. We take a rigorous experimental and modeling approach to study multicomponent separation of aromatics and aliphatics with a mesoporous silica adsorbent, which is relevant in many petrochemical applications such as separation of reformate and distillate streams. Our approach involves refining multicomponent adsorption, mass transfer, and SMB process parameters based upon detailed experimental inputs, with progressive addition of components. We develop a robust model that quantitatively predicts the influence of key operating parameters such as stream flow rates, desorbent/feed ratio, and switch time on the separation results and concentration profiles. The model is validated as a function of feed complexity by SMB experiments and column concentration profile measurements in a 16-column mini-plant. Furthermore, conditions for clear separation of each mixture are developed.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available