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Record W3004019023 · doi:10.3390/molecules25030633

Exploring the Scope of Macrocyclic “Shoe-last” Templates in the Mechanochemical Synthesis of RHO Topology Zeolitic Imidazolate Frameworks (ZIFs)

2020· article· en· W3004019023 on OpenAlexaff
Ivana Brekalo, David E. Deliz, Christopher M. Kane, Tomislav Friščić, K.T. Holman

Bibliographic record

VenueMolecules · 2020
Typearticle
Languageen
FieldChemistry
TopicMetal-Organic Frameworks: Synthesis and Applications
Canadian institutionsMcGill University
FundersNational Science Foundation
KeywordsZeolitic imidazolate frameworkTemplateCavitandTopology (electrical circuits)PorosityImidazolateMaterials scienceScope (computer science)NanotechnologyChemistryChemical engineeringComputer scienceMetal-organic frameworkMoleculeOrganic chemistrySupramolecular chemistryAdsorptionMathematicsComposite materialEngineering

Abstract

fetched live from OpenAlex

The macrocyclic cavitand MeMeCH2 is used as a template for the mechanochemical synthesis of 0.2MeMeCH2@RHO-Zn16(Cl2Im)32 (0.2MeMeCH2@ZIF-71) and RHO-ZnBIm2 (ZIF-11) zeolitic imidazolate frameworks (ZIFs). It is shown that MeMeCH2 significantly accelerates the mechanochemical synthesis, providing high porosity products (BET surface areas of 1140 m2/g and 869 m2/g, respectively). Templation of RHO-topology ZIF frameworks constructed of linkers larger than benzimidazole (HBIm) was unsuccessful. It is also shown that cavitands other than MeMeCH2—namely MeHCH2, MeiBuCH2, HPhCH2, MePhCH2, BrPhCH2, BrC5CH2—can serve as effective templates for the synthesis of x(cavitand)@RHO-ZnIm2 products. The limitations on cavitand size and shape are explored in terms of their effectiveness as templates.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.017
Threshold uncertainty score0.564

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.041
GPT teacher head0.251
Teacher spread0.211 · 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.

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

Citations8
Published2020
Admission routes1
Has abstractyes

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