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Record W3087117600 · doi:10.1021/acs.accounts.0c00479

Coupling without Coupling Reactions: En Route to Developing Phenols as Sustainable Coupling Partners via Dearomatization–Rearomatization Processes

2020· article· en· W3087117600 on OpenAlexafffund
Zihang Qiu, Huiying Zeng, Chao‐Jun Li

Bibliographic record

VenueAccounts of Chemical Research · 2020
Typearticle
Languageen
FieldChemistry
TopicChemical synthesis and alkaloids
Canadian institutionsMcGill UniversityCentre in Green Chemistry and Catalysis
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsMinistry of Education of the People's Republic of ChinaCanada Foundation for InnovationNational Natural Science Foundation of ChinaFonds Québécois de la Recherche sur la Nature et les TechnologiesMcGill University
KeywordsCoupling (piping)PhenolsChemistryCoupling reactionComputational chemistryChemical physicsMaterials scienceOrganic chemistryCatalysisMetallurgy

Abstract

fetched live from OpenAlex

Transition-metal-catalyzed cross-coupling reactions represent one of the most straightforward and efficient protocols to assemble two different molecular motifs for the construction of carbon-carbon or carbon-heteroatom bonds. Because of their importance and wide applications in pharmaceuticals, agrochemicals, materials, etc., cross-coupling reactions have been well recognized in the 2010 Nobel Prize in chemistry. However, in the classical transition-metal-catalyzed cross-coupling reactions (e.g., the Suzuki-Miyaura, the Buchwald-Hartwig, and the Ullmann cross-coupling reactions), organohalides, which mainly stem from the nonrenewable fossil resources, are often utilized as coupling partners with halide wastes being generated after the reactions. To make cross-coupling reactions more sustainable, we initiated a general research program by employing phenols and cyclohexa(e)nones (the reduced forms of phenols) as pivotal feedstocks (coupling partners), instead of the commonly used fossil-derived organohalides, for cross-coupling reactions to build C-O, C-N, and C-C bonds. Phenols (cyclohexa(e)nones) are widely available and can be obtained from lignin biomass, highlighting their renewable and sustainable features. Moreover, water is expected to be the only stoichiometric byproduct, thus avoiding halide wastes.Notably, the cross-coupling reactions utilizing phenols/cyclohexa(e)nones are not based on the traditional transition-metal-catalyzed "oxidative-addition and reductive-elimination" mechanism, but via a novel "phenol-cyclohexanone" redox couple. This new working mechanism opens up new horizons of designing cross-coupling reactions via simple nucleophilic addition of cyclohexanones along with aromatization processes, thereby simplifying the design and avoiding laborious optimization of transition-metal precursors (e.g., Pd, Ni, Cu, etc.), as well as ligands in classical transition-metal-catalyzed cross-coupling reactions. Specifically, in this Account, we will summarize and discuss our related research work in the following three categories: "formal oxidative couplings of cyclohexa(e)nones", "formal reductive couplings of phenols", and "formal redox-neutral couplings of phenols". The successes of these research projects clearly demonstrated our initial inspirations and rational designs to develop cross-coupling reactions without the "conventional cross-coupling conditions" by pushing the reaction frontiers from initial cyclohexanones, ultimately, to the sustainable phenol targets.

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)0.001
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.058
GPT teacher head0.372
Teacher spread0.315 · 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

Citations95
Published2020
Admission routes2
Has abstractyes

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