Date of Award

January 2025

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Chemical Engineering

First Advisor

Ali Alshami

Abstract

Membrane technologies have emerged as a cornerstone of sustainable process operations, providing efficient alternatives to conventional separation methods. With increasing emphasis on sustainability and environmental concerns, the projected membrane market growth is largely driven by their application in novel fields, replacing traditional processes. However, the widespread adoption of next-generation membranes hinges on overcoming critical fabrication challenges, such as membrane fouling, filler-matrix compatibility, and the inherent permeability-selectivity trade-off. This work explores innovative solutions to these challenges across multiple separation processes, including reverse osmosis (RO), pervaporation, and gas separation. Membrane fouling is a critical issue towards Reverse Osmosis (RO) based sustainable water purification. An eight-month long pilot study was conducted using three antiscalants to evaluate RO performance and fouling patterns. The study revealed an antiscalant dependent fouling deposition with critical manganese scaling with environmentally friendly terpolymer antiscalants. Operational modifications along with surface-modified membranes were proposed to mitigate membrane fouling. Pervaporation, a pharmaceutically attractive liquid-liquid membrane separation process, was studied with mixed matrix membranes. In particular, the filler-matrix interactions were closely studied to propose state-of-the-art permeation modeling based on filler hydrophilicity. Additionally, to address the limitations of conventional membrane materials, the study further includes the fabrication of 2D nanomaterial-based membranes, incorporating magnetic stimuli to create tunable membranes for critical gas separations. These membranes demonstrate magnetic control over selectivity and permeability, offering a solution to the traditional permeability-selectivity trade-off. Finally, the study integrates machine learning assisted material discovery into membrane science by directing pathways to streamline membrane material optimization and accelerate innovation. Collectively, the proposed innovations in membrane fabrication pave the way for next-generation applications, providing efficient and sustainable separation solutions across diverse industries.

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