Flow-based crystallization-driven self-assembly: advancements in reproducibility, scalability, and functional design

Xiao, Laihui ORCID: 0000-0002-3412-0954 (2025). Flow-based crystallization-driven self-assembly: advancements in reproducibility, scalability, and functional design. University of Birmingham. Ph.D.

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Abstract

Crystallization-Driven Self-Assembly (CDSA) is a powerful technique for synthesizing anisotropic nanoparticles. However, CDSA often requires long aging times and low concentrations to maintain precise control over nanoparticle dimensions, leading to low throughput and limiting its potential for commercial applications. Furthermore, CDSA faces challenges in increasing structural complexity. This project aims to address these limitations by increasing the throughput of nanoparticle preparation through the transition from batch to flow reactors, and subsequently enhancing the structural complexity of the resulting nanoparticles. The entire process was divided into three key stages, demonstrated through the preparation of platelet nanostructures. First, living CDSA was conducted using pre-formed seed particles to investigate flow conditions, highlighting the potential for enhanced scalability and reproducibility of platelet preparation using flow. In the next stage, a flash-freezing method was employed to improve seed formation efficiency significantly. Subsequently, an integral flow system was developed, combining seed formation and living growth stages, enabling the high-throughput synthesis of platelets directly from the polymer in just three minutes. Finally, a temperature-responsive CDSA strategy was implemented to fabricate delicate platelets with controllable 3D surface patterns, leveraging the precise temperature regulation offered by flow reactors. Overall, this work presents a novel approach to nanoparticle preparation that combines enhanced throughput with increased structural complexity, paving the way for innovations in nanotechnology and advancing the development of functional nanoparticles.

Type of Work:

Thesis (Doctorates > Ph.D.)

Award Type:

Doctorates > Ph.D.

Supervisor(s):