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Record W4377139897 · doi:10.1002/ange.202303463

Customizable Supraparticles Constructed from Catechol‐Terminated Molecular Building Blocks with Controllable Intermolecular Interactions**

2023· article· en· W4377139897 on OpenAlexaff
Yajing Zhang, Jin Wang, Yunxiang He, Jiezhou Pan, Xin Jin, Jiaojiao Shang, Guidong Gong, Joseph J. Richardson, Ian Manners, Junling Guo

Bibliographic record

VenueAngewandte Chemie · 2023
Typearticle
Languageen
FieldMaterials Science
TopicSupramolecular Self-Assembly in Materials
Canadian institutionsUniversity of British ColumbiaUniversity of Victoria
FundersNational Key Research and Development Program of ChinaNatural Science Foundation of Sichuan ProvinceChina Postdoctoral Science FoundationFundamental Research Funds for the Central UniversitiesDouble First Class University PlanNational Natural Science Foundation of China
KeywordsCatecholNanotechnologyIntermolecular forceMaterials scienceBiomoleculeChemistryMoleculeOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Colloidal supraparticles integrated with multicomponent primary particles come with emerging or synergetic functionalities. However, achieving the functional customization of supraparticles remains a great challenge because of the limited options of building blocks with tailorability and functional extensibility. Herein, we developed a universal approach to construct customizable supraparticles with desired properties from molecular building blocks obtained by the covalent conjugation of catechol groups with a series of orthogonal functional groups. These catechol‐terminated molecular building blocks can assemble into primary particles driven by various intermolecular interactions (i.e. metal‐organic coordination, host–guest, and hydrophobic interactions), and then further assemble into supraparticles governed by catechol‐mediated interfacial interactions. Our strategy enables the formation of supraparticles with diverse functionalities, such as dual‐pH responsiveness, light‐controllable permeability, and non‐invasive fluorescence labeling of living cells. The ease with which these supraparticles can be fabricated, and the ability to tailor their chemical and physical properties through the choice of metals and orthogonal functional groups used, should enable a variety of applications.

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), Insufficient payload (model declined to judge)
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 score0.004
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.011
GPT teacher head0.253
Teacher spread0.242 · 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

Citations6
Published2023
Admission routes1
Has abstractyes

Explore more

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