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Record W1982517153 · doi:10.1021/jo502710a

Why Are Organotin Hydride Reductions of Organic Halides So Frequently Retarded? Kinetic Studies, Analyses, and a Few Remedies

2014· article· en· W1982517153 on OpenAlexaff
K. U. Ingold, Vincent W. Bowry

Bibliographic record

VenueThe Journal of Organic Chemistry · 2014
Typearticle
Languageen
FieldChemistry
TopicOrganometallic Compounds Synthesis and Characterization
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsChemistryHalideHydrideKinetic energyOrganic chemistryMedicinal chemistryHydrogen

Abstract

fetched live from OpenAlex

Kinetic data for reduction of organic halides (RX) by tri-n-butylstannane (SnH) reveal a serious flaw in the current view of the kinetic radical chain: the tacit but unproven assumption that the speed of reaction is determined by the slowest propagation step. Our results show this is rarely true for reductive chains and that the observed rate is in fact controlled by unseen side-reactions of propagating R(•) and Sn(•) radicals with the solvent (notably, benzene!) or solvent impurities (e.g., trace benzophenone dryness indicator in THF) or, crucially, with allylic-CH and conjugated unsaturated groups in substrates and products. Most R(•) and/or Sn(•) radicals are therefore converted into relatively inert delocalized species A(•) and/or B(•) that inhibit the chain. Retardation in the degraded chain is given by a simple sum of terms, each being the ratio of the chain-transfer rate divided by the rate of chain-return. The model kinetic equation is linear and easy to ratify, interpret, and apply: to calculate retarding rate constants, optimize reaction conditions, and identify additives or "remedies" that repair the chain and accelerate reaction. The present work is thus expected to have a helpful impact on the practice and design of SnH radical chain based (and related) syntheses.

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)0.002
metaresearch head score (Gemma)0.003
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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.001
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 head0.030
GPT teacher head0.263
Teacher spread0.233 · 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

Citations21
Published2014
Admission routes1
Has abstractyes

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