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Record W2889151438 · doi:10.13005/ojc/340404

Novel Green Hydrogel Material using Bacterial Cellulose

2018· article· en· W2889151438 on OpenAlexafffund
Amorn Chaiyasat, Sirinard Jearanai, Somporn Moonmangmee, Duangtip Moonmangmee, Lew P. Christopher, Md Nur Alam, Preeyaporn Chaiyasat

Bibliographic record

VenueOriental Journal Of Chemistry · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHydrogels: synthesis, properties, applications
Canadian institutionsLakehead University
FundersRajamangala University of Technology ThanyaburiLakehead University
KeywordsBacterial celluloseSelf-healing hydrogelsChemistryAcetic acidSwellingCellulosePolymer chemistryGreen chemistryMacromoleculeCrystallizationNuclear chemistryChemical engineeringSupramolecular chemistryOrganic chemistryBiochemistryCrystal structure

Abstract

fetched live from OpenAlex

The green bacterial cellulose (BC)-based hydrogel materials have successfully prepared by modification and crosslink BC. BC was derived from acetic acid bacteria isolated and selected from ripe fruits. The production of BC was performed by fermentation in various media. It was found that using liquid potato medium represented the highest thickness of BC film (0.80 cm) with 2 wt% solid content covered the media. To reduce the crystallization of BC, carboxyl group was introduced onto BC chains using a carboxymethylation reaction giving carboxymethyl BC (CMBC) and subsequently crosslinked with divinyl sulfone (DVS). The extent of crosslinking influenced on the swelling properties of the hydrogels. Using large DVS amounts (>30 wt%-of CMBC), dense macromolecular network with less capacity spaces in the hydrogel was formed. The maximum water retention value of green hydrogels containing ~3.0 mmol carboxyl groups/g CMBC reached 27 (g/g).

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 score0.021
Threshold uncertainty score0.678

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 head0.238
Teacher spread0.223 · 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

Citations17
Published2018
Admission routes2
Has abstractyes

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