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Record W2594614655 · doi:10.1002/admi.201601218

Hierarchical Self‐Assembly of Dopamine into Patterned Structures

2017· article· en· W2594614655 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAdvanced Materials Interfaces · 2017
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Surface Interaction Studies
Canadian institutionsUniversity of Alberta
FundersFundamental Research Funds for the Central UniversitiesNational Natural Science Foundation of China
KeywordsDewettingMaterials scienceSelf-assemblyNanotechnologyPolymerizationAqueous solutionChemical engineeringPolymerThin filmOrganic chemistryChemistryComposite material

Abstract

fetched live from OpenAlex

It has been demonstrated that dopamine can undergo oxidation and complicated self‐reaction in aqueous solution to form so‐called polydopamine (PDA). In this paper, for the first time, the hierarchical self‐assembly of dopamine into surface patterned structures is described. PDA nanoaggregates are first prepared assisted by ethylenediamine, based on the covalent self‐polymerization and noncovalent self‐assembly. The surface fractal patterns are further created and modulated by the dynamic self‐assembly of PDA nanoaggregates to develop more macroscopic ordered structure of PDA. Various surface patterns of PDA aggregates are successfully obtained by evaporative dewetting method. The effects of solution pH, type of inorganic salts, and temperature on the morphology of surface pattern are investigated. Mineralization or metal deposition is used to keep the pattern fixed. The surface patterning strategy reported here is applicable to a broad range of materials, which allows the developments of materials with controllable patterned structure.

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.

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 score0.006
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.317
Teacher spread0.301 · 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