Hartree–Fock and density functional theory study of remote substituent effects on heterolytic Fe―C bond energies of <i>p</i>‐G‐C<sub>6</sub>H<sub>4</sub>CH<sub>2</sub>Fe(CO)<sub>2</sub>(η<sup>5</sup>‐C<sub>5</sub>H<sub>5</sub>) and <i>p</i>‐G‐C<sub>6</sub>H<sub>4</sub>(H)(CN)CFe(CO)<sub>2</sub>(η<sup>5</sup>‐C<sub>5</sub>H<sub>5</sub>)
Bibliographic record
Abstract
Knowledge of the strength of the metal–ligand bond breaking and formation is fundamental for an understanding of the thermodynamics underlying many important stoichiometric and catalytic organometallic reactions. Quantum chemical calculations at different levels of theory have been used to investigate heterolytic Fe―C bond energies of para‐substituted benzyldicarbonyl(η5‐cyclopentadienyl)iron, p‐G‐C6H4CH2Fp [1, G = NO2, CN, COMe, CO2Me, CF3, Br, Cl, F, H, Me, MeO, NMe2; Fp = (η5‐C5H5)(CO)2Fe], and para‐substituted α‐cyanobenzyldicarbonyl(η5‐cyclopentadienyl)iron, p‐G‐PANFp [2, PAN = C6H4CH(CN)]. The results show that BP86 and TPSSTPSS can provide the best price/performance ratio and more accurate predictions in the study of ΔHhet(Fe―C)'s. The good linear correlations [r = 0.98 (g, 1a), 0.99 (g, 2b)] between the substituent effects of heterolytic Fe―C bond energies [ΔΔHhet(Fe―C)'s] of series 1 and 2 and the differences of acidic dissociation constants (ΔpKa) of C―H bonds of p‐G‐C6H4CH3 and p‐G‐C6H4CH2CN imply that the governing structural factors for these bond scissions are similar. And the excellent linear correlations [r = −1.00 (g, 1c), −0.99 (g, 2d)] between ΔΔHhet(Fe―C)'s and the substituent σp− constants show that these correlations are in accordance with Hammett linear free energy relationships. The polar effects of these substituents and the basis set effects influence the accuracy of ΔHhet(Fe―C)'s. ΔΔHhet(Fe―C)'s(1, 2) follow the Capto‐dative Principle. The detailed knowledge of the factors that determine the Fp―C bond strengths would greatly aid in understanding reactivity patterns in many processes. Copyright © 2011 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".