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Record W3150837251 · doi:10.1021/acsapm.1c00101

Elastomeric Silicone Sponges for Bleach Delivery

2021· article· en· W3150837251 on OpenAlexafffund
Sijia Zheng, Michael A. Brook

Bibliographic record

VenueACS Applied Polymer Materials · 2021
Typearticle
Languageen
FieldChemistry
TopicAntimicrobial agents and applications
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaChina Scholarship Council
KeywordsBleachSodium hypochloriteSiliconeHypochloriteAqueous solutionElastomerChemistryPeroxideSpongeSilicone oilPulp and paper industryChemical engineeringOrganic chemistry

Abstract

fetched live from OpenAlex

Topical disinfection protocols to inactivate organisms, particularly on high contact surfaces, have become increasingly important. A classical oxidative agent, sodium hypochlorite (bleach), has many benefits, but can be problematic during applications because of its ability to oxidize the organic polymers in which it is contained. We demonstrate that bleach-containing elastomeric sponges are readily created in one step at room temperature from thiopropyl-modified silicone oils; sodium hypochlorite induces disulfide cross-linking and a foam structure due, in part, to the concomitant formation of sulfonates. No surfactants are required. The morphology of the bleach-containing silicone sponge is tunable by the aqueous bleach solution concentration and the water/silicone ratio used. The resulting silicone sponge contains excess bleach that can be released gradually, as shown by its ability to oxidize organic molecules in aqueous solution, either directly or after dehydration/rehydration; the latter process provides a way to store the bleach-containing material in dry form. Such foams exhibit enhanced sustainability as, we show, they can be converted back to thiopropylsilicone oils by reduction using hydrosilicones. The resulting oils can be re-cross-linked, completing the life cycle.

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 categoriesInsufficient payload (model declined to judge)
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 score0.031
Threshold uncertainty score0.996

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)0.0050.000

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 head0.012
GPT teacher head0.229
Teacher spread0.217 · 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

Citations4
Published2021
Admission routes2
Has abstractyes

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