Finding dimensions: Analytical approaches towards the integrated assessment of size distribution and composition of nanoparticles

A wide variety of nanoparticles (NPs) is used in everyday applications, ranging from cosmetics and coatings to advanced drug-delivery systems. With the continuous development of new nanoparticle types, such as polymer-based nanoparticles (PNPs) and lipid nanoparticles (LNPs), there is a growing need for analytical methods capable of reliably assessing their properties, including size distribution and composition. Conventional techniques typically provide information on a single property, requiring multiple methods for comprehensive characterization. Multi-dimensional analytical approaches offer the potential to assess multiple properties simultaneously and to establish correlations between them. This thesis focuses on the development and application of two-dimensional liquid chromatography (2D-LC) methods for the analysis of PNPs and LNPs containing functional cargo. As introduced in Chapter 1, the aim was to separate intact nanoparticles based on size in the first dimension, followed by online transformation and analysis of their constituents in a second dimension. Key challenges included selecting suitable size-based separation techniques, enabling online disassembly of nanoparticles, and ensuring compatibility between both dimensions. This work was conducted within the PARADISE (Propelling Analysts by Removing Analytical-, Data-, Instrument-, and Sample-related Encumbrances) project, which aims to develop robust and automated analytical methods for complex samples. Chapter 2 evaluates eleven particle-sizing techniques for determining particle size distributions (PSDs) of PNPs. The results show that no single technique is universally suitable for complex samples; instead, methods should be considered complementary. Ensemble techniques are easy to use but less suitable for complex systems, while separation techniques and flow cytometry provide more detailed insights. Careful interpretation of data is essential, especially when relying on commercial software. Online sample transformation plays a key role in multidimensional analysis. Chapter 3 reviews approaches for converting samples online to enable the characterization of multiple properties, including strategies for nanoparticles, oligonucleotides, and polymers. Such transformations can reduce complexity, improve detectability, and reveal additional sample characteristics. In Chapter 4, solvent-induced disassembly of PNPs is investigated. Using nephelometry, the minimum amount of organic solvent required for complete nanoparticle disruption was determined, showing limited dependence on formulation variables. Chapter 5 presents a 2D-LC method combining hydrodynamic chromatography (HDC) and reversed-phase LC to determine nanoparticle size and encapsulated cargo simultaneously. Chapter 6 introduces a workflow to accurately determine PSDs from HDC data by correcting for system-induced band broadening. For LNPs, Chapter 7 examines the use of in-line mixers in hydrophilic interaction chromatography (HILIC), demonstrating improved compatibility with aqueous samples. Chapter 8 describes a 2D-LC platform combining size exclusion chromatography and HILIC to quantify encapsulated oligonucleotides after online nanoparticle disassembly. Finally, Chapter 9 summarizes the findings and discusses future perspectives, including improved sample transformation strategies and enhanced compatibility in 2D-LC systems. Overall, this work demonstrates the potential of integrated 2D-LC approaches for comprehensive nanoparticle characterization.