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Record W2317457062 · doi:10.1021/cg300297p

Rational Synthesis of Metal–Organic Framework Nanocubes and Nanosheets Using Selective Modulators and Their Morphology-Dependent Gas-Sorption Properties

2012· article· en· W2317457062 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCrystal Growth & Design · 2012
Typearticle
Languageen
FieldChemistry
TopicMetal-Organic Frameworks: Synthesis and Applications
Canadian institutionsUniversité LavalCentre in Green Chemistry and Catalysis
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDABCOCrystallinitySorptionOctaneKirkendall effectMetal-organic frameworkAcetic acidNanorodPyridineChemical engineeringMaterials scienceMetalChemistryNanocrystalInorganic chemistryNanotechnologyOrganic chemistryCrystallographyAdsorption

Abstract

fetched live from OpenAlex

Nanocubes and nanosheets of [Cu 2 (ndc) 2 (dabco)] n metal–organic framework (ndc = 1,4-naphthalene dicarboxylate; dabco = 1,4-diazabicyclo[2.2.2]octane) were synthesized by using simultaneously acetic acid and pyridine or only pyridine, respectively, as selective modulators. This approach can tailor crystal growing on different directions for the size- and shape-controlled synthesis of metal–organic framework (MOF) nanocrystals whose structure is composed of two or more types of linkers using selective modulators. These MOF nanocrystals exhibit high crystallinity and higher CO 2 uptakes compared to that of the bulk MOF material or of the [Cu 2 (ndc) 2 (dabco)] n nanorods generated by using only acetic acid as the selective modulator, which may be due to the morphology effect on their gas sorption properties.

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.

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 categoriesMeta-epidemiology (narrow)
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 score0.056
Threshold uncertainty score1.000

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 science0.0000.000
Research integrity0.0000.000
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 head0.027
GPT teacher head0.224
Teacher spread0.197 · 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