Predicting complex mixture permeation in polymer membranes
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Lee, Youngjoo
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Abstract
The fractionation or separation of complex mixtures by polymer membranes is attractive when hybridized with existing separation modalities (e.g., distillation, evaporation) especially for hydrocarbon separations, and has the potential to be applied to biobased complex mixtures (e.g., biocrude, crude tall oils) that are often incompatible with high temperature operations. In this work, it is demonstrated that membrane-distillation hybrid systems can significantly reduce thermal energy used for energy intensive separation processes in a crude oil refinery.
However, a critical gap for this class of membrane separations is the difficulty associated with estimating membrane performance when challenged with a complex mixture. Thus, there is the potential for the field of membrane-based complex mixture separations to develop in an entirely ad-hoc manner, by not utilizing rational design approaches (that have shown value in many chemical engineering applications) to systematically handle the enormous complexity of the separations problem.
Inspired by this gap, the primary goal of this work is to construct an experimentally grounded and generalizable prediction framework based on a Maxwell-Stefan model that rapidly estimates any organic solvent separations through any linear polymer membrane. In the development of this prediction framework, the first aim of this dissertation is to develop predictors for transport parameters (e.g., diffusivities, solubilities) using machine learning algorithms, informed with empirically observed diffusion physics. In the second aim of this dissertation, a study on diffusion behaviors of organic molecules in polymer membranes is conducted to understand the effect of chemical interactions between the membrane and the feed mixture on the multi-component diffusion. Lastly, the prediction framework – developed in the first two aims – is utilized to facilitate new membrane materials development by screening out potential candidate materials and applied to generate synthetic ‘landscape’ plots for various organic solvent separations, which does not yet exist for organic solvent reverse osmosis separation.
Membranes are being deployed in ever more challenging liquid phase separations. The work here has potential to accelerate research, development, and deployment of membrane materials and separation processes for a wide variety of important complex mixture separations.
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Date
2024-07-26
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Dissertation