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Record W4391420482 · doi:10.26434/chemrxiv-2024-ml728

A Thermally Stable, Alkene-Free Palladium Source for Oxidative Addition Complex Formation and High Turnover Catalysis

2024· preprint· en· W4391420482 on OpenAlexafffund
Jingjun Huang, Dang Binh Ho, Gregory Gaube, Holly Celuszak, Joseph Becica, Nathan D. Schley, David C. Leitch

Bibliographic record

VenueChemRxiv · 2024
Typepreprint
Languageen
FieldChemistry
TopicCatalytic Cross-Coupling Reactions
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAlkenePalladiumCatalysisChemistryOxidative additionOxidative phosphorylationReductive eliminationCombinatorial chemistryPhosphineReactivity (psychology)DiimineOrganic chemistry

Abstract

fetched live from OpenAlex

Oxidative addition complexes play a crucial role in Pd-catalyzed transformations. They are not only key catalytic intermediates, but are also powerful and robust precatalysts, and effective reactants for late-stage functionalization of complex molecules. However, accessing a given oxidative addition complex is often challenging due to a lack of effective and stable palladium sources with the correct reactivity. Herein, we report an easily prepared and bench stable Pd(II) dialkyl complex, DMPDAB–Pd–BTSM (BTSM = bis[trimethylsilylmethyl]), that is a versatile precursor for generating Pd(II) oxidative addition complexes, and a highly active Pd source for in situ catalyst formation in cross-coupling reactions. A crucial aspect of this structure is the absence of alkene-based stabilizing ligands common to other Pd precursors. We demonstrate the utility of this precursor in the formation of several Pd(II) complexes, including phosphine and diimine-ligated oxidative addition complexes, and in high turnover number catalysis of C–O, Suzuki, and Heck coupling reactions.

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)
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 score0.029
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.023
GPT teacher head0.261
Teacher spread0.238 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

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