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Record W2725336466 · doi:10.1021/acs.organomet.7b00292

Study of Monomeric Copper Complexes Supported by <i>N</i>-Heterocyclic and Acyclic Diamino Carbenes

2017· article· en· W2725336466 on OpenAlexafffund
Jason P. Coyle, Eric R. Sirianni, Ilia Korobkov, Glenn P. A. Yap, Gangotri Dey, Seán T. Barry

Bibliographic record

VenueOrganometallics · 2017
Typearticle
Languageen
FieldChemistry
TopicN-Heterocyclic Carbenes in Organic and Inorganic Chemistry
Canadian institutionsUniversity of OttawaCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistrySteric effectsCopperAlkylMelting pointMonomerThermal stabilityCarbeneVaporizationCrystallographyIsothermal processVapor pressurePhysical chemistryPolymer chemistryStereochemistryOrganic chemistryThermodynamicsPolymer

Abstract

fetched live from OpenAlex

The thermal properties of a series of monomeric copper(I) hexamethyldisilazide complexes supported by N -heterocyclic and acyclic diamino carbenes were evaluated to study the impact of N -alkyl substituents and backbone character on volatility and thermal stability of copper amides. The series of complexes were either liquids or solids with melting points in the broad range of 45–184 °C. Vaporization rates were measured by stepped-isothermal TGA experiments and found to be between 110–170 °C. Enthalpies of vaporization were determined to be 63–90 kJ/mol. Temperatures for 1 Torr vapor pressure were estimated to be 143–172 °C, showing a general dependence on molecular weight. The imidazolylidene complexes were thermally unstable with convincing evidence indicating the unsaturated backbone as a point of weakness. The imidazolinylidene complexes showed excellent thermal stability with comparable results for the formamidinylidenes complexes. The steric parameter of the carbene, % V Bur, was calculated for all complexes characterized by single crystal X-ray diffraction.

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 score0.002

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 head0.018
GPT teacher head0.258
Teacher spread0.241 · 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

Citations32
Published2017
Admission routes2
Has abstractyes

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