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Record W2729349265 · doi:10.1107/s2052252517008326

Structure-directing effects of ionic liquids in the ionothermal synthesis of metal–organic frameworks

2017· review· en· W2729349265 on OpenAlexafffund
Thomas P. Vaid, Steven P. Kelley, Robin D. Rogers

Bibliographic record

VenueIUCrJ · 2017
Typereview
Languageen
FieldChemistry
TopicMetal-Organic Frameworks: Synthesis and Applications
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Excellence Research Chairs, Government of Canada
KeywordsIonic liquidChemistryMetal-organic frameworkLinkerSolventIonCombinatorial chemistrySolvothermal synthesisIonic bondingMetalOrganic synthesisInorganic chemistryOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

Traditional synthesis of metal-organic frameworks (MOFs) involves the reaction of a metal-containing precursor with an organic linker in an organic solvent at an elevated temperature, in what is termed a 'solvothermal' reaction. More recently, many examples have been reported of MOF synthesis in ionic liquids (ILs), rather than an organic solvent, in 'ionothermal' reactions. The high concentration of both cations and anions in an ionic liquid allows for the formation of new MOF structures in which the IL cation or anion or both are incorporated into the MOF. Most commonly, the IL cation is included in the open cavities of the MOF, countering the anionic charge of the MOF framework itself and acting as a template around which the MOF structure forms. Ionic liquids can also serve other structure-directing roles, for example, when an IL containing a single enantiomer of a chiral anion leads to a homochiral MOF, even though the IL anion is not itself incorporated into the MOF. A comprehensive review of ionothermal syntheses of MOFs, and the structure-directing effects of the ILs, is given.

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)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.027
GPT teacher head0.310
Teacher spread0.283 · 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

Citations77
Published2017
Admission routes2
Has abstractyes

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Same venueIUCrJSame topicMetal-Organic Frameworks: Synthesis and ApplicationsFrench-language works237,207