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Record W3010095503 · doi:10.1039/c9cs00456d

Surface-confined single-layer covalent organic frameworks: design, synthesis and application

2020· review· en· W3010095503 on OpenAlexafffund
Daling Cui, Dmitrii F. Perepichka, Jennifer MacLeod, Federico Rosei

Bibliographic record

VenueChemical Society Reviews · 2020
Typereview
Languageen
FieldMaterials Science
TopicCovalent Organic Framework Applications
Canadian institutionsMcGill UniversityInstitut National de la Recherche Scientifique
FundersAustralian Research CouncilCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsCovalent bondLayer (electronics)NanotechnologySurface (topology)ChemistrySurface modificationReticular connective tissueMaterials scienceOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

Two-dimensional (2D) nanomaterials, such as graphene and single layer covalent organic frameworks (sCOFs) are being widely studied due to their unusual structure/property relationships. sCOFs typically feature atomic thickness, intrinsic nanoscale porosity and a crystalline lattice. Compared to other organic 2D materials, sCOFs exhibit major advantages including topological designation and constitutional tunability. This review describes the state of the art of surface-confined sCOFs, emphasizing reticular design, synthesis approaches, and key challenges related to improving quality and exploring 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.075
GPT teacher head0.314
Teacher spread0.239 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations110
Published2020
Admission routes2
Has abstractyes

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