Novel Catalytic Hunsdiecker−Heck (CHH) Strategy toward All-<i>E</i> Stereocontrolled Ferrocene-Capped Conjugated Push−Pull Polyenes
Bibliographic record
Abstract
Halodecarboxylation reaction of ferrocenylacrylic acid 1 and ferrocenyldienoic acid 3d with N -bromo- and N -iodosuccinimide in the presence of catalytic tetrabutylammonium trifluoroacetate at −40 °C and −78 °C affords the corresponding β-halovinylferrocenes 2a, 2b and δ-haloferrocenyldiene 4 in 37−72% yields. Heck reaction of β-iodovinylferrocene 2a with vinyl substrates (CH 2 CH−Z where Z = CO 2 Me, CO 2 Et, COMe, CO 2 H, CONH 2, 4‘-NO 2 C 6 H 4 ) in the presence of tri(4-tolyl)arsine/palladium acetate/lithium chloride/triethylamine in acetonitrile at 35−80 °C affords the corresponding ferrocenyldienes 3a − 3f in 50−81% isolated yields. Similar reaction of δ-iodoferrocenyldiene 4 with vinyl substrates (CH 2 CH−Z where Z = CO 2 Me, CO 2 Et, CO 2 H, 4‘-NO 2 C 6 H 4 ) affords the corresponding ferrocenyltrienes 5a − 5d in 55−87% isolated yields. The ferrocene-capped conjugated dienes and trienes show excellent all- E stereoselectivity (vide NMR). The electronic, redox, and nonlinear optical properties of ferrocenylpolyenes have been evaluated. The data suggest that upon increasing the polyene chain length, (a) the absorption maxima shifts progressively to higher wavelength, (b) the oxidation potential of the Fc/Fc + couple ( E 1/2 ) decreases, and (c) the HRS-derived second-order NLO response (β) increases. From the insights derived from semiempirical calculation (ZINDO/1), a mechanism for the halodecarboxylation reaction has been proposed suggesting the prior formation of tetrabutylammonium salt of ferrocenylacrylic acid I . Attack of the halogenium atom at the π C C in I leads to the formation of intermediate II, and the latter triggers the elimination of carbon dioxide.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".