Density Functional Theory Calculations Support the Additive Nature of Ligand Contributions to the p<i>K</i><sub>a</sub> of Iron Hydride Phosphine Carbonyl Complexes
Bibliographic record
Abstract
The acid dissociation constant K a of a transition-metal hydride complex is a key thermodynamic quantity for evaluating reactivity and stability of the complexes and their conjugate bases in stoichiometric and catalytic reactions. It can be estimated using a simple ligand acidity constant (LAC) empirical equation for a wide range of complexes. Here, we provide the first density functional theory (DFT) study that supports the additive nature of ligand contributions to the p K a of metal hydride complexes. Specifically, the p K a values of iron hydride complexes [FeH(CO) x (PR 3 ) (5– x ) ] + in either tetrahydrofuran or dichloromethane solutions are estimated using the LAC method and DFT calculations. There is a linear correlation between these two methods, and both predict a surprisingly linear increase in p K a over a wide range from approximately −15 for x = 5 to approximately 40 for x = 0. The LAC equation predicts that p K a THF or p K a DCM increases by 9 units with the replacement of each CO ligand with a trialkylphosphine ligand in a stepwise fashion, whereas the DFT calculations predict the step size will be approximately 11. The two methods agree with p K DCM data available for x = 3 and qualitative data for x = 1 and 0, but further quantitative measurements over a wider range are needed to firmly establish the trend. The free energy of protonation and the energy of the highest occupied molecular orbital of Fe(CO) x (PR 3 ) (5– x ) (mainly nonbonding d electrons) increase linearly with phosphine substitution, and this increases the p K a value as observed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".