Electronic Structure Contributions to Electron-Transfer Reactivity in Iron−Sulfur Active Sites: 2. Reduction Potentials
Bibliographic record
Abstract
This study utilizes photoelectron spectroscopy (PES) combined with theoretical methods to determine the electronic structure contributions to the large reduction potential difference between [FeCl(4)](2)(-)(,1)(-) and [Fe(SR)(4)](2)(-)(,1)(-) (DeltaE(0) approximately 1 V). Valence PES data confirm that this effect results from electronic structure differences because there is a similarly large shift in the onset of valence ionization between the two reduced species (DeltaI(vert) = 1.4 +/- 0.3 eV). Specific electronic contributions to DeltaI(vert) have been investigated and defined. Ligand field effects, which are often considered to be of great importance, contribute very little to DeltaI(vert) (DeltaE(LF) < -0.05 eV). By contrast, electronic relaxation, a factor that is often neglected in the analysis of chemical reactivity, strongly affects the valence ionization energies of both species. The larger electronic relaxation in the tetrathiolate allows it to more effectively stabilize the oxidized state and lowers its I(vert) relative to that of the chloride (DeltaE(rlx) = 0.2 eV). The largest contribution to the difference in redox potentials is the much lower effective charge () of the tetrathiolate in the reduced state, which results in a large difference in the energy of the Fe 3d manifold between the two redox couples (DeltaE(Fe)( )(3d) = 1.2 eV). This difference derives from the significantly higher covalency of the iron-thiolate bond, which decreases and significantly lowers its redox potential.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".