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Record W2122219260 · doi:10.1039/c5dt02889b

Mechanistic features of the copper-free Sonogashira reaction from ESI-MS

2015· article· en· W2122219260 on OpenAlexafffund
Zohrab Ahmadi, Lars P. E. Yunker, Allen G. Oliver, J. Scott McIndoe

Bibliographic record

VenueDalton Transactions · 2015
Typearticle
Languageen
FieldChemistry
TopicCatalytic Cross-Coupling Reactions
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationBritish Columbia Knowledge Development FundUniversity of Victoria
KeywordsSonogashira couplingCopperChemistryCombinatorial chemistryComputational chemistryPalladiumOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

The mechanism of the Sonogashira reaction in methanol was studied in detail using pressurized sample infusion electrospray ionization mass spectrometry (PSI-ESI-MS). Several key intermediates were identified and their structures were assigned by MS/MS studies. Cationic and anionic charged-tagged substrates were employed to look into the mechanism of this reaction from variety of angles. A reverse kinetic isotope effect was observed in which the reaction rate is accelerated in deuterated solvents (kH/kD = 0.6). The reaction was found to be zero order with respect to the aryl iodide and first order with respect to the phenylacetylene. A Hammett parameter of ρ = 1.4 indicates that the reaction is more favorable for aryl iodides with para EWGs. No evidence of product inhibition, dimerization of palladium catalyst, or agglomeration were observed. However, catalyst decomposition was inferred from a non-zero intercept in the plot of catalyst loading versus reaction rate. Monitoring the reaction by PSI-ESI-(-)MS on neutral and negatively charged substrates at variety of concentrations and conditions did not reveal any detectable anionic palladium complexes. Likewise no evidence of carbopalladation and relevant intermediates in the absence of a base was observed.

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)0.000
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 score0.028
Threshold uncertainty score0.699

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.021
GPT teacher head0.255
Teacher spread0.234 · 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

Citations26
Published2015
Admission routes2
Has abstractyes

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