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Record W4401384127 · doi:10.1021/acscatal.4c02407

Halide Salts Alleviate TMSOK Inhibition in Suzuki–Miyaura Cross-Couplings

2024· article· en· W4401384127 on OpenAlexafffund
Yao Shi, Joshua S. Derasp, Sara M. Guzman, Brian O. Patrick, Jason E. Hein

Bibliographic record

VenueACS Catalysis · 2024
Typearticle
Languageen
FieldChemistry
TopicCatalytic Cross-Coupling Reactions
Canadian institutionsUniversity of TorontoUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaAdvanced Research Projects AgencyDefense Advanced Research Projects AgencyUniversity of British ColumbiaCanada Foundation for Innovation
KeywordsChemistryHalideReactivity (psychology)Combinatorial chemistryCatalysisSalt (chemistry)HomogeneousPotassiumBase (topology)Organic chemistry

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide The Suzuki–Miyaura cross-coupling (SMC) remains one of the most widely used transformations available to chemists. Recently, robust new conditions achieving rapid reactivity under homogeneous aprotic conditions enabled by the use of potassium trimethylsilanolate (TMSOK) as a base were reported. However, the strong inhibitory effect of TMSOK restricts the generality of such conditions. Moreover, the basic nature of TMSOK impedes the use of protic heterocycles as substrates, as these latter anionic species are even more potent catalyst inhibitors. Herein, we report a thorough mechanistic study of these novel SMC conditions. Halide salt additives were found to provide a dramatic rate acceleration and mitigate the inhibitory effect of TMSOK. NMR experiments revealed that this is largely achieved by impacting the unexpected formation of inactive [LnPd(Ar)(μ–OH)] 2, favoring the formation of active LnPd(Ar)(X) instead. These findings enabled an impressive substrate scope even at low catalyst loadings (0.1 mol %). Finally, halide additives were observed to enable the use of protic heterocyclic substrates, which could otherwise completely inhibit reactivity.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.007
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.297
Teacher spread0.285 · 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.

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

Citations6
Published2024
Admission routes2
Has abstractyes

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