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Record W2877265633 · doi:10.1039/c8sm01239c

Reversible fabrication and self-assembly of a gemini supra-amphiphile driven by dynamic covalent bonds

2018· article· en· W2877265633 on OpenAlexafffund
Lijuan Shi, Fenglin Liu, Tingting Liu, Jingsi Chen, Xu Shaobo, Hongbo Zeng

Bibliographic record

VenueSoft Matter · 2018
Typearticle
Languageen
FieldMaterials Science
TopicSupramolecular Self-Assembly in Materials
Canadian institutionsAlberta Hospital EdmontonUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of ChinaCanada Research Chairs
KeywordsCovalent bondAmphiphileFabricationSelf-assemblyDynamic covalent chemistryNanotechnologyChemistryMaterials scienceChemical physicsChemical engineeringOrganic chemistrySupramolecular chemistryMoleculePolymerEngineeringCopolymer

Abstract

fetched live from OpenAlex

A smart gemini supra-amphiphile behaving with pH/CO2 dual-sensitive hierarchical self-assembly was fabricated under the effect of dynamic covalent bonds. In the presence of an amino-functionalized cation, water-insoluble terephthalaldehyde, and an amphiphilic anion, the benzoic imine bond can initiate the transformation from a single-tailed supra-amphiphile to a gemini supra-amphiphile with increasing pH, followed by the subsequent evolution from micelles to vesicles. Reversible self-assembly and disassembly of the gemini supra-amphiphile can be realized via CO2/N2 treatment, thus inducing the fission and reversion of vesicles. Interestingly, the flexible nature of supra-amphiphiles allows for the hierarchical assembly of vesicles, leading to the formation of aqueous two-phase systems. Multiple responsive supra-amphiphiles have useful applications in the fabrication of smart supra-molecular materials, including self-healing materials, nanocarriers and chemosensors.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.027
Threshold uncertainty score0.999

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)0.0010.002

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 head0.006
GPT teacher head0.243
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; both teacher heads agree on what is shown here.

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

Citations7
Published2018
Admission routes2
Has abstractyes

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