Author ORCID Identifier:

https://orcid.org/0009-0003-4959-3134

Date of Graduation

5-2026

Document Type

Thesis

Degree Name

Master of Science in Chemical Engineering (MSChE)

Degree Level

Graduate

Department

Chemical Engineering

Advisor/Mentor

Monroe, Jacob

Committee Member

Hestekin, Christa

Second Committee Member

Nelson, Christopher

Third Committee Member

Nayani, Kartik

Fourth Committee Member

Wang, Xiaoyu

Keywords

Adeno Associated Virus(AAV) purification; Crystallization; Gene therapy; Gibbs-Duhem Integration; Monte Carlo Simulation; phase diagram

Abstract

Gene therapy using adeno-associated viruses (AAVs) holds promise for treating genetic diseases, but high manufacturing costs limit its widespread use. A major challenge is separating functional (full) AAV capsids from non-functional (empty) ones, which are produced in similar amounts and have nearly identical structures. Conventional purification methods, such as density gradient ultracentrifugation and chromatography, face drawbacks like low yield, poor scalability, and high cost, often requiring multi-step processes. Recently, selective crystallization has emerged as a promising alternative, offering improved efficiency, scalability, and product quality. However, optimizing this method requires a deep understanding of thermodynamic phase behavior in multicomponent systems. In this thesis, we utilize Gibbs-Duhem integration (GDI) and Monte Carlo simulations in the FEASST framework to study the solid-liquid phase behavior of binary Lennard-Jones (LJ) mixtures, which serves as a model for AAV purification through selective crystallization. Using the VODE for numerical integration, we trace solid-liquid coexistence curves across a range of interaction parameters, including diameter ratios σ11/σ22 and well-depth ratios ϵ11/ϵ22. We further examine the effects of varying pressures on phase stability, coexistence compositions, and tieline characteristics. The resulting phase diagrams reveal that solid-liquid phase stability is highly sensitive to interaction asymmetry, interaction strength, and pressure. In particular, the length, slope, and composition contrast along the tie-lines, which are critical indicators of separation efficiency, vary significantly with these parameters. These findings enhance our understanding of how small differences in particle interactions and operating pressure can enhance selective crystallization. Moreover, this work establishes an efficient computational workflow for mapping phase behavior in complex systems, laying the groundwork for thermodynamic-guided design of scalable, high-yield AAV purification processes.

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