MétaCan
Menu
Back to cohort
Record W4223419651 · doi:10.3390/nano12071223

Supramolecular Nanostructures Based on Perylene Diimide Bioconjugates: From Self-Assembly to Applications

2022· review· en· W4223419651 on OpenAlexafffund
Nadjib Kihal, Ali Nazemi, Steve Bourgault

Bibliographic record

VenueNanomaterials · 2022
Typereview
Languageen
FieldMaterials Science
TopicSupramolecular Self-Assembly in Materials
Canadian institutionsPROTEORegroupement Québécois sur les Matériaux de PointeUniversité du Québec à Montréal
FundersNatural Sciences and Engineering Research Council of CanadaCourtois Foundation
KeywordsDiimidePeryleneSupramolecular chemistryNanotechnologyMaterials scienceSelf-assemblyNanostructureContext (archaeology)Conjugated systemMoleculeCombinatorial chemistryChemistryPolymerOrganic chemistry

Abstract

fetched live from OpenAlex

Self-assembling π-conjugated systems constitute efficient building blocks for the construction of supramolecular structures with tailored functional properties. In this context, perylene diimide (PDI) has attracted attention owing to its chemical robustness, thermal and photo-stability, and outstanding optical and electronic properties. Recently, the conjugation of PDI derivatives to biological molecules, including oligonucleotides and peptides, has opened new avenues for the design of nanoassemblies with unique structures and functionalities. In the present review, we offer a comprehensive summary of supramolecular bio-assemblies based on PDI. After briefly presenting the physicochemical, structural, and optical properties of PDI derivatives, we discuss the synthesis, self-assembly, and applications of PDI bioconjugates.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.786
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.000
Open science0.0030.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0120.005

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 head0.026
GPT teacher head0.308
Teacher spread0.282 · 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
GenreReview

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

Citations35
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueNanomaterialsSame topicSupramolecular Self-Assembly in MaterialsFrench-language works237,207