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Record W7021315214

Novel Infusion Procedure for Antimicrobial Fabric Generation

2023· dissertation· en· W7021315214 on OpenAlexaffabout

Bibliographic record

VenueUWSpace (University of Waterloo) · 2023
Typedissertation
Languageen
FieldChemistry
TopicAntimicrobial agents and applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsAntimicrobialWoven fabricCopperTextile
DOInot available

Abstract

fetched live from OpenAlex

Antimicrobial fabrics are fabrics that can kill or slow down the growth of microorganisms that contact the fabric. It is a massive field that is developing due to the sheer variety of fabrics that are possible. Antimicrobial fabrics contain active (antimicrobial compounds) such as organic molecules, metals, or antimicrobial peptides. The variety in antimicrobial fabrics comes from the ability to combine and use the antimicrobial compounds to create a fabric finish with unique properties. Therefore, various properties can be explored to determine the best usage case for the fabric.
\nI created a novel antimicrobial infusion fabric nicknamed “Beryl” together with its production process. In collaboration with engineers Microbonds Inc., Markham, Canada. This fabric is based on a standard woven cotton subject to a pre-infusion (pretreatment) of a solution containing an organic acid, a polymer, and a surfactant. This fabric is then subject to a main infusion with various ppm levels of cupric (Cu2+) ions. These successive infusions impart antimicrobial properties to the fabric.
\nDescribed in this thesis are the physical and antimicrobial properties of this new fabric. The fabric is compared to a previous proprietary fabric from Microbonds Inc, named AC5, as well as a control fabric treated with copper sulfate. Characterization begins with the fabric feel and odor, which remained unchanged. Color change was measured using a PICO paint matcher device, which showed that the Beryl fabric maintains the original color of the fabric better than the AC5 fabric. The copper content of the fabric was tested, showing that the Beryl had typically between 0.357 and 6.43 mg of copper per gram of fabric. Fabric morphology was determined using a scanning electron microscope, which showed the Beryl fabric contained a thin coating of copper on the surface of the cotton fibers, with only a few small copper deposits at some exposed locations on the fabric fibers. In contrast, the AC5 fabric showed a discontinuous, seemingly brittle but thick layer of copper, with larger deposits at multiple locations on the surface of the fabric. The thin layer of copper for the Beryl was confirmed using energy dispersive x-ray spectroscopy, despite it not being visible in the backscatter electron detector image. Antimicrobial efficiency tests were done before and after multiple wash cycles to show laundering resistance of the antimicrobial coatings. It was found that the fabric was perfectly efficient at 0 washes, while after 30 washes, the fabric’s efficiency dropped to 96 % for the 1000 ppm copper infused Beryl fabric. The antimicrobial properties of the pre-infusion were also tested showing the fabric was effective at 0 washes. Plates incubated for longer suggest Beryl is bacteriostatic at 30 washes rather than bactericidal. Contact time efficiency tests showed that the fabric reduced bacterial load within 45 seconds, with 100 % efficiency reached after 5 minutes of contact time with the fabric.
\nAfter laundering, the efficiency for the Beryl decreased below that of the AC5 fabric. However, by increasing the copper ion content of the cupric ion infusion bath, the wash resistance of the fabric can be expected to increase to maintain 100 % efficiency, so it retains effectiveness after larger numbers of washes. Furthermore, usage of the Beryl process is safer, making it more sustainable than the AC5 due to no hazardous gaseous products being created in the Beryl process.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.931
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.018
GPT teacher head0.219
Teacher spread0.202 · 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 teacher head, not a consensus.

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
Published2023
Admission routes2
Has abstractyes

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