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Record W2515388800 · doi:10.1002/chem.201602890

Computational Study of the Palladium‐Catalyzed Carbonylative Synthesis of Aromatic Acid Chlorides: The Synergistic Effect of P<i>t</i>Bu<sub>3</sub> and CO on Reductive Elimination

2016· article· en· W2515388800 on OpenAlexaff
Jeffrey S. Quesnel, Salvador Moncho, Kai E. O. Ylijoki, Gerardo M. Torres, Edward N. Brothers, Ashfaq A. Bengali, Bruce A. Arndtsen

Bibliographic record

VenueChemistry - A European Journal · 2016
Typearticle
Languageen
FieldChemistry
TopicAsymmetric Hydrogenation and Catalysis
Canadian institutionsSaint Mary's UniversityMcGill University
FundersQatar National Research Fund
KeywordsReductive eliminationCarbonylationChemistryPalladiumPhosphineSteric effectsCarbon monoxideArylCatalysisMedicinal chemistryLigand (biochemistry)Combinatorial chemistryOrganic chemistryPhotochemistryAlkylReceptor

Abstract

fetched live from OpenAlex

Abstract We describe herein computational studies on the unusual ability of Pd(P t Bu 3 ) 2 to catalyze formation of highly reactive acid chlorides from aryl halides and carbon monoxide. These show a synergistic role of carbon monoxide in concert with the large cone angle P t Bu 3 that dramatically lowers the barrier to reductive elimination. The tertiary structure of the phosphine is found to be critical in allowing CO association and the generation of a high energy, four coordinate (CO)(PR 3 )Pd(COAr)Cl intermediate. The stability of this complex, and the barrier to elimination, is highly dependent upon phosphine structure, with the tertiary steric bulk of P t Bu 3 favoring product formation over other ligands. These data suggest that even difficult reductive eliminations can be rapid with CO association and ligand manipulation. This study also represents the first detailed exploration of all the steps involved in palladium‐catalyzed carbonylation reactions with simple phosphine ligands, including the key rate‐determining steps and palladium(0) catalyst resting state in carbonylations.

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)0.002
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 score0.009
Threshold uncertainty score0.464

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.007
GPT teacher head0.217
Teacher spread0.209 · 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

Citations31
Published2016
Admission routes1
Has abstractyes

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Same venueChemistry - A European JournalSame topicAsymmetric Hydrogenation and CatalysisFrench-language works237,207