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Record W2775307124 · doi:10.1021/acs.macromol.7b02163

CO<sub>2</sub>-Switchable Self-Healing Host–Guest Hydrogels

2017· article· en· W2775307124 on OpenAlexafffund
Yong‐Guang Jia, Meng Zhang, X. X. Zhu

Bibliographic record

VenueMacromolecules · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHydrogels: synthesis, properties, applications
Canadian institutionsUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of CanadaFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsCholic acidSelf-healing hydrogelsCyclodextrinEthylene glycolCopolymerSelf-healingAmphiphileChemistryPolymer chemistrySelf-assemblyChemical engineeringMaterials scienceOrganic chemistryPolymerBile acid

Abstract

fetched live from OpenAlex

The use of natural compounds to construct reversible networks is an attractive strategy in biomaterials design. Our design is based on a host–guest pair of natural compounds β-cyclodextrin and cholic acid through the use of a cholic acid dimer tethered with a poly(ethylene glycol) spacer, which subsequently served as a guest cross-linker to afford a hydrogel with copolymers bearing β-cyclodextrin pendants. The hydrogel after incision self-heals rapidly under ambient atmosphere as observed and confirmed by rheological measurements. To endow the hydrogels with reversibility and responsiveness, the addition of a CO 2 -switchable guest of benzimidazole followed by alternating treatments with CO 2 and N 2 leads to a reversible sol–gel transition due to the dynamic complexation between the cholic acid and β-cyclodextrin units. The CO 2 responsiveness and the natural origin of the constituents make these self-healing hydrogels attractive as smart biomaterials.

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 score0.072
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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.250
Teacher spread0.236 · 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

Citations55
Published2017
Admission routes2
Has abstractyes

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