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Record W6982460338

Improving Sustainability of Silicone Materials Using Natural Products via Imine Chemistry

2024· dissertation· en· W6982460338 on OpenAlexfundno aff

Bibliographic record

VenueMacSphere (McMaster University) · 2024
Typedissertation
Languageen
FieldChemistry
TopicPlant-Derived Bioactive Compounds
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSiliconeElastomerThermosetting polymerThermal stabilityBiocompatibilityDegradation (telecommunications)Silicone ElastomersPolymer
DOInot available

Abstract

fetched live from OpenAlex

Silicones are commonly used to make materials that play an important role in our everyday lives. Their broad uses are attributed to the vast array of unique properties that these materials boast, including thermal stability, biocompatibility and gas permeability, to name a few, attributed to the unique structure and stability of the dimethylsiloxane bonds. Materials made with silicones are not without their faults, particularly as it pertains to their environmental impact. There are negative environmental implications of synthesizing and disposing of silicone elastomers; synthesis requires very high heat and results in the release of greenhouse gases, in addition to the use of expensive and/or toxic metal catalysts, such as platinum or tin. This is made worse by the fact that the resulting elastomers resist degradation in the environment, unlike linear silicone oil, due to the formation of permanent bonds resulting in robust, thermosetting materials. As such, the need to improve the end-of-life of silicone elastomers and develop methods to recycle the silicone oil to reduce environmental impact is critical for the future of silicone materials. The use of dynamic bonds has been a recent area of interest for promoting better circularity of materials. Dynamic bonds, both covalent and non-covalent, could allow for the formation of materials with stable but reversible crosslinks, allowing for facile reprocessing and degradation at end-of-life. Silicone-hydrogels are unique materials that have important applications in the medical field, including wound dressings and contact lenses. As the rates of degradation of silicones in crosslinked matrices are unclear, it was reasoned that, if incorporated into a protein hydrogel, degradable materials which exhibit silicone-like properties could be obtained. Classic methods used to crosslink proteins exploit amine reactions with aldehydes; for this reason, formaldehyde was chosen as the crosslinking agent in this system. Aqueous protein solutions of gelatin were combined with telechelic and pendent aminopropyl silicones in different concentrations, to yield gelatin-silicone hydrogels. Using this method, hydrogels composed of >90% hydrophilic material could be prepared while still retaining silicone-like properties. The mechanical properties of the gels were tuned by altering the crosslinker concentration and the ratio of gelatin:silicone to yield robust materials that, after dehydration, formed tough elastomers that resisted rehydration and exhibited low surface energies. Enzymatic degradation of the hydrated gelatin-silicone hydrogels was facile using bromelain, a protease derived from pineapple stems. The use of gelatin allowed the target silicone materials to be enzymatically degraded, yielding silicone oil bound to amino acids or peptides. The ability to make silicone materials that could be reprocessed to reform the original silicone oil for reuse was of interest. The potential to use vanillin, a phenolic aldehyde, to make vanillin-silicone elastomers via Schiff-base chemistry was investigated. Vanillin-silicone oils were first synthesized by a green, catalyst-free process to form oils that were stable under inert conditions. The resulting oils were used to produce a library of vanillin-silicone elastomers that varied in hardness, rate of cure and heat and chemical reprocessability. These variables were shown to be highly tunable depending on the composition of the vanillin-silicone oil ([NH2], % vanillin functionalization, and molecular weight of the silicone) and curing conditions (including humidity and heat). Although stable in neutral aqueous solutions, hydrolysis under acidic conditions was possible, however very slow. Transimination with butylamine was shown to be significantly faster and successful in degrading all elastomers, resulting in the ability to recover the starting silicone oil.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.009
GPT teacher head0.210
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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