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Record W2409013724 · doi:10.1021/acsami.5b02486

Preparation of Hollow <i>N-</i>Chloramine-Functionalized Hemispherical Silica Particles with Enhanced Efficacy against Bacteria in the Presence of Organic Load: Synthesis, Characterization, and Antibacterial Activity

2015· article· en· W2409013724 on OpenAlexafffund
Hakim Rahma, Sogol Asghari, Sarvesh Logsetty, Xiaochen Gu, Song Liu

Bibliographic record

VenueACS Applied Materials & Interfaces · 2015
Typearticle
Languageen
FieldChemistry
TopicAntimicrobial agents and applications
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsMaterials scienceAntimicrobialBacteriaChloramineMoleculeChemical engineeringParticle sizeDisinfectantParticle (ecology)NanotechnologyNanoparticleAmine gas treatingOrganic chemistryChemistryChlorine

Abstract

fetched live from OpenAlex

The fabrication of highly effective antimicrobial materials is an important strategy for coping with the growing concern of bacterial resistance. In this study, N-chloramine-functionalized hollow hemispherical structures were designed and prepared to examine possible enhancement of antimicrobial performance. Antimicrobial testing was carried out on Gram-negative (Escherichia coli) and Gram-positive (Baccilus Cereus) bacteria in the presence and absence of biological medium. The efficacy of the hollow hemispherical particles functionalized with various N-chloramines in killing bacteria was compared among themselves with that of small organic molecules and spherical particles to investigate the effect of the surface charge, chemical structure, and shape of the particles. Results demonstrated that quaternary ammonium salt or amine functions in the chemical structure enhanced the antimicrobial activity of the particles and made the particles more effective than the small molecules in the presence of biological medium. The importance of particle shape in the killing tests was also confirmed.

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 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 score0.002
Threshold uncertainty score0.568

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 head0.014
GPT teacher head0.248
Teacher spread0.235 · 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.

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

Citations23
Published2015
Admission routes2
Has abstractyes

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