The Polymerization and Application of Silicone Microemulsions in the Development of Nanostructured Materials
Bibliographic record
Abstract
Microemulsions are nanostructured dispersions that have unique properties, which make them attractive for applications such as biomaterials, drug delivery, and nanoparticle synthesis. The behaviour of hydrocarbon microemulsions and their applications have been extensively studied, however, there have been very few studies in the preparation or the polymerization of silicone microemulsions. Silicone microemulsions offer a unique template by which to create novel nanoporous silicone elastomers and/or hydrogels. The prevalent use of silicones in biomaterials, coatings, and personal care (to name a few) make the development of silicone-based microemulsions of particular interest. The aim of thesis research was to polymerize silicone microemulsions and to understand the factors that contribute to retaining initial template morphology in the polymeric product. Chapter Two of this thesis focuses on the preparation of silicone microemulsions containing a non-polymerizable and polymerizable trisiloxane surfactant, respectively. Formulations were prepared and characterized by electrical conductivity to determine the microemulsion structure type. Formulations located in the bicontinuous region of the phase diagram were polymerized, producing transparent silicone elastomers. The focus of Chapter Three was to determine the tolerance of silicone microemulsions to selected chemistry that is relevant to silicone polymers. Previous work done in the field of polymerizing silicone microemulsions has been based on radical polymerization processes. There are no reports that examine the polymerization of a silicone microemulsion by room temperature vulcanization (RTV), a common process for creating silicone elastomers. We aimed to better understand the effects of RTV cure on morphology retention from the liquid to polymeric product to determine if this type of chemistry could be used in the formation of nanoporous silicone elastomers either on its own or in conjunction with a radical polymerization process. In order to understand the effects of an RTV process on polymer structure, we examined the effect of the variable components (necessary for the RTV cure) on the silicone microemulsion template. Small angle X-ray scattering (SAXS) and transmission electron microscopy (TEM) were used as tools to characterize materials prior to and after cure. Silicone microemulsions that were cured using the RTV process produced nanoporous polymeric elastomers, however, the initial bicontinuous microemulsion template was not retained. RTV cured microemulsions retained the bicontinuous structure if the RTV cure was preceded by a photopolymerization reaction to “lock-in” surfactant monomers at the oil/water interface. Chapter Four explores the use of silicone microemulsions as a reaction vehicle in the formation of nano-TiO2 particles. The focus of this chapter was the exploitation of microemulsion droplets and bicontinuous structures that were designed to retard TiO2 particle formation in situ. Titanium isopropoxide (TTIP) was incorporated into silicone microemulsions containing varying amounts of water. Interactions between TTIP and the trisiloxane polyether surfactant result in the formation of a compound containing a Ti4+, coordinated to silicone surfactant molecules via a polyether linkage. Titania forms in situ as water is titrated into the surfactant/oil mixture, resulting in the formation of a microemulsion. The formation of TiO2 was monitored by UV-Vis spectroscopy and the TiO2 particles were characterized using transmission electron microscopy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".