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Record W4247249316 · doi:10.26434/chemrxiv.11886651

Transformation Between 2D and 3D Covalent Organic Frameworks via Reversible [2+2] Cycloaddition

2020· preprint· en· W4247249316 on OpenAlexaff
Thaksen Jadhav, Yuan Fang, Chenghao Liu, Afshin Dadvand, Ehsan Hamzehpoor, William Patterson, Antranik Jonderian, Robin S. Stein, Dmitrii F. Perepichka

Bibliographic record

VenueChemRxiv · 2020
Typepreprint
Languageen
FieldMaterials Science
TopicCovalent Organic Framework Applications
Canadian institutionsMcGill University
Fundersnot available
KeywordsCovalent bondCrystallinityCycloadditionCrystallographyAbsorption (acoustics)Exfoliation jointConductivityMaterials scienceAbsorption edgeDopingLuminescenceChemistryNanotechnologyPhysical chemistryBand gapOrganic chemistryGraphene

Abstract

fetched live from OpenAlex

We report the first transformation between crystalline vinylene-linked two-dimensional (2D) polymers and crystalline cyclobutane-linked three-dimensional (3D) polymers. Specifically, absorption-edge irradiation of the 2D poly(arylenevinylene) covalent organic frameworks (COFs) results in topological [2+2] cycloaddition cross-linking the π-stacked layers in 3D COFs. The reaction is reversible and heating to 200°C leads to a cycloreversion while retaining the COF crystallinity. The resulting difference in connectivity is manifested in the change of mechanical and electronic properties, including exfoliation, blue-shifted UV-Vis absorption, altered luminescence, modified band structure and different acid-doping behavior. The Li-impregnated 2D and 3D COFs show a significant ion conductivity of 1.8×10<sup>−4</sup> S/cm and 3.5×10<sup>−5</sup> S/cm, respectively. Even higher room temperature proton conductivity of 1.7×10<sup>-2</sup> S/cm and 2.2×10<sup>-3</sup> S/cm was found for H<sub>2</sub>SO<sub>4</sub>-treated 2D and 3D COFs, respectively.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.021
GPT teacher head0.255
Teacher spread0.234 · 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 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

Citations2
Published2020
Admission routes1
Has abstractyes

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