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Record W2768184094 · doi:10.3390/polym9120633

Microwave Assisted Preparation of Antimicrobial Chitosan with Guanidine Oligomers and Its Application in Hygiene Paper Products

2017· article· en· W2768184094 on OpenAlexafffund
Junrong Li, Ying Ye, Huining Xiao, Beihai He, Liying Qian

Bibliographic record

VenuePolymers · 2017
Typearticle
Languageen
FieldChemistry
TopicAntimicrobial agents and applications
Canadian institutionsUniversity of New Brunswick
FundersFundamental Research Funds for the Central UniversitiesNatural Sciences and Engineering Research Council of Canada
KeywordsChitosanAntimicrobialCovalent bondNuclear chemistryGuanidineCelluloseMaterials scienceMolar ratioChemistryPolymer chemistryBiomaterialChemical engineeringCombinatorial chemistryOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

Guanidinylated chitosan (GCS) was prepared by grafting guanidine oligomers onto chitosan under microwave irradiation. The structure of GCS characterized by FT-IR and 1H NMR verified the covalent bonding between the guanidine oligomers and chitosan; the effects of molar ratio, reaction temperature, and time were investigated and the degree of substitution of GCS reached a maximum of 25.5% under optimized conditions in this work. The resulting GCS showed significantly enhanced antimicrobial activities. The results obtained from the dynamic UV absorption of Escherichia coli (E. coli) and atomic force microscopy (AFM) revealed that the deactivation of E. coli by GCS was due to the destructing of the cell membrane and the prompt release of cytoplasm from the bacterial cells. The adsorption of GCS onto cellulose fibers and the antimicrobial efficiency of the hygiene papers with GCS were also investigated. Microwave irradiation as a green assisted method was applied to promote this reaction. This facile approach allowed chitosan to be guanidinylated without tedious preparation procedures and thus broadened its application as a biocompatible antimicrobial agent.

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 score0.012
Threshold uncertainty score0.499

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 head0.013
GPT teacher head0.257
Teacher spread0.245 · 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

Citations10
Published2017
Admission routes2
Has abstractyes

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