Ingenieurwissenschaften und zugeordnete Tätigkeiten
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Silica materials are popular in biomedical applications as composites and drug delivery platforms due to their low toxicity and biocompatibility. Mesoporous silica nanoparticles are attractive drug delivery systems based on their porous silica framework with high surface area. In the preparation of mesoporous silica frameworks, most commonly, MCM-41, the efficient removal of the template responsible for introducing porous networks, cetyltrimethyl ammonium bromide (CTAB), is a critical step due to the template’s high toxicity in the environment and human health. In this work, we present a new one-pot approach of introducing challenging antibiotics within a silica framework without the need of toxic templates, but instead using micelle formation by an antibacterial agent. We demonstrate that micelles formed by cetylpyridinium chloride (CPC), a known antibacterial agent, entrap antibiotics such as rifampicin and ciprofloxacin. Extensive NMR studies elucidate the precise localisation of the antibiotic within the CPC micelle. Ciprofloxacin is placed between the outer and palisade region while rifampicin is located further into the hydrophobic CPC micelle core. In both cases, the formation of the silica framework can be built around the CPC-antibiotic loaded micelles. The resulting silica nanoparticles show loading of both CPC and antibiotic agents, porosity and dual antibacterial release upon disruption of the micelle within the silica framework. The design not only provides a strategy of a therapeutic design to form porous frameworks but also highlights the potential of precise antibiotic dose and release in nanoparticle systems.
The roughness as a property of core–shell (CS) microparticles plays a key role in their functionality. Quantitative evaluation of the roughness of CS microparticles is, however, a challenging task with approaches using electron microscopy images being scarce and showing pronounced differences in terms of methodology and results. This work presents a generalized method for the reliable roughness determination of nonplanar specimens such as CS particles from electron microscopic images, the method being robust and reproducible with a high accuracy. It involves a self-written software package (Python) that analyzes the recorded images, extracts corresponding data, and calculates the roughness based on the deviation of the identified contour. Images of single particles are taken by a dual mode scanning electron microscopy (SEM) setup which permits imaging of the same field-of-view of the sample with high resolution and surface sensitive in SE InLens mode as well as in transmission mode (TSEM). Herein, a new type of polystyrene core–iron oxide shell–silica shell particles is developed to serve as a set of lower micrometer-sized study objects with different surface roughness; the analysis of their images by the semiautomatic workflow is demonstrating that the particles’ profile roughness can be quantitatively obtained.