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Record W2614941360 · doi:10.1021/jacs.7b03144

Experimental and Theoretical Evaluation of the Stability of True MOF Polymorphs Explains Their Mechanochemical Interconversions

2017· article· en· W2614941360 on OpenAlexafffund
Zamirbek Akimbekov, Athanassios D. Katsenis, G. P. Nagabhushana, Ghada Ayoub, Mihails Arhangelskis, Andrew J. Morris, Tomislav Friščić, Alexandra Navrotsky

Bibliographic record

VenueJournal of the American Chemical Society · 2017
Typearticle
Languageen
FieldChemistry
TopicMetal-Organic Frameworks: Synthesis and Applications
Canadian institutionsMcGill University
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaEngineering and Physical Sciences Research CouncilU.S. Department of Energy
KeywordsChemistryZeolitic imidazolate frameworkChemical stabilityMetal-organic frameworkCalorimetrySubstituentLigand (biochemistry)ThermodynamicsDensity functional theoryStability (learning theory)ImidazolateComputational chemistryCrystallographyTopology (electrical circuits)Physical chemistryStereochemistryInorganic chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

We provide the first combined experimental and theoretical evaluation of how differences in ligand structure and framework topology affect the relative stabilities of isocompositional (i.e., true polymorph) metal-organic frameworks (MOFs). We used solution calorimetry and periodic DFT calculations to analyze the thermodynamics of two families of topologically distinct polymorphs of zinc zeolitic imidazolate frameworks (ZIFs) based on 2-methyl- and 2-ethylimidazolate linkers, demonstrating a correlation between measured thermodynamic stability and density, and a pronounced effect of the ligand substituent on their stability. The results show that mechanochemical syntheses and transformations of ZIFs are consistent with Ostwald's rule of stages and proceed toward thermodynamically increasingly stable, more dense phases.

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)0.001
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 score0.005
Threshold uncertainty score0.950

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.024
GPT teacher head0.285
Teacher spread0.261 · 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

Citations115
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the American Chemical SocietySame topicMetal-Organic Frameworks: Synthesis and ApplicationsFrench-language works237,207