Application of Lever’s Electrochemical E<sub>L</sub> Parameters Scale Toward Fe(II)/Fe(III) Versus Pc(2-)/Pc(1-) Oxidation Process Crossover Point in Axially Coordinated Iron(II) Phthalocyanine Complexes and Its Relation to the MLCT1 Energy Derived from MCD Spectroscopy
Bibliographic record
Abstract
The electronic structures, and, particularly, the nature of the HOMO in a series of the low-spin PcFeL2, PcFeL′L″, and [PcFeX2]2- iron(II) phthalocyanine complexes were probed by electrochemical, spectroelectrochemical and chemical oxidation approaches and complimented by MCD spectroscopy as well as theoretical (DFT and TDDFT) studies. In general, energies of the metal-centered occupied orbitals in the various six-coordinate iron phthalocyanine complexes correlate well with Lever’s electrochemical parameter, EL, and intercross the phthalocyanine-centered a1u orbital in several compounds with moderate-to-strong p-accepting axial ligands. In these cases, an oxidation of the phthalocyanine macrocycle (Pc(2-)/Pc(1-)) rather than the central metal ion (Fe(II)/Fe(III)) was theoretically predicted and experimentally confirmed. The experimentally derived using MCD spectroscopy or theoretically predicted using TDDFT calculations energy of the MLCT1 transition (dπ→Pc(π*)) on iron(II) phthalocyanines also follows the trend expected for the EL properties of the axial ligands.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.002 | 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".