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Record W2199395922 · doi:10.1021/acssuschemeng.5b01400

Comparison of Hydrogels Prepared with Ionic-Liquid-Isolated vs Commercial Chitin and Cellulose

2015· article· en· W2199395922 on OpenAlexaff
Xiaoping Shen, Julia L. Shamshina, Paula Bertón, Jenny Bandomir, Hui Wang, Gabriela Gurău, Robin D. Rogers

Bibliographic record

VenueACS Sustainable Chemistry & Engineering · 2015
Typearticle
Languageen
FieldMaterials Science
TopicNanocomposite Films for Food Packaging
Canadian institutionsMcGill University
FundersSmall Business Innovation ResearchChina Scholarship CouncilU.S. Department of Energy
KeywordsSelf-healing hydrogelsCelluloseIonic liquidMicrocrystalline celluloseChitinEpichlorohydrinNanocelluloseBiopolymerChemical engineeringChemistryPolymer chemistryMaterials scienceAqueous solutionChitosanOrganic chemistryPolymer

Abstract

fetched live from OpenAlex

Physical and/or covalently linked (chemical) hydrogels were prepared from chitin and cellulose extracted with ionic liquid from shrimp shells and wood biomass, respectively, and compared with hydrogels prepared from commercially available biopolymers, practical grade chitin, and microcrystalline cellulose. The highly porous aerogels were formed by initial dissolution of the biopolymers in NaOH/urea aqueous systems using freeze/thaw cycles, followed by thermal treatment (with or without epichlorohydrin as a cross-linker) and supercritical CO 2 drying. The ionic-liquid-extracted cellulose pulp and chitin, as well as practical grade chitin could form both stable physical and chemical hydrogels, whereas biopolymers of lower apparent molecular weight such as microcrystalline cellulose required a covalent cross-linker for hydrogel formation and commercially available pure chitin was not suitable for the preparation of hydrogels of either type. Hydrogels prepared from the ionic-liquid-extracted biopolymers exhibited properties substantially different from those made from the commercially available biopolymers. Loading of an active ingredient into the hydrogel and its subsequent release was demonstrated using indigo carmine and revealed that the release rate was controlled mainly by the biopolymer concentration of the gel network.

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: Empirical
Teacher disagreement score0.013
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 head0.009
GPT teacher head0.238
Teacher spread0.229 · 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

Citations112
Published2015
Admission routes1
Has abstractyes

Explore more

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