Linear Free Energy Relationships and Transition State Analysis of CO <sub>2</sub> Reduction Catalysts Bearing Second Coordination Spheres with Tunable Acidity
Bibliographic record
Abstract
In molecular catalysts, protic functional groups in the secondary coordination sphere (SCS) work in conjunction with an exogenous acid to relay protons to the active site of electrochemical CO 2 reduction; however, it is not well understood how the acidity of the SCS and exogenous acid together determine the kinetics of catalytic turnover. To evaluate the relative contributions of proton transfer driving forces, we synthesized a series of modular iron tetraphenylporphyrin electrocatalysts bearing SCS amides of tunable p K a (17.6 to 20.0 in dimethyl sulfoxide (DMSO)) and employed phenols of variable acidity (15.3 to 19.1) as exogenous acids. This system allowed us to (1) evaluate contributions from proton transfer driving forces associated with either the SCS or exogenous acid and (2) obtain mechanistic insights into CO 2 reduction as a function of p K a . A series of linear free-energy relationships show that kinetics become increasingly sensitive to variations in SCS p K a when more acidic exogenous acids are used (0.82 ≥ Brønsted α ≥ 0.13), as well as to variations in exogenous acid p K a when SCS acidity is increased (0.62 ≥ Brønsted α ≥ 0.32). An Eyring analysis suggests that the rate-determining transition state becomes more ordered with decreasing SCS acidity, which is consistent with the proposal that SCS acidity modulates charge accumulation and solvation at the rate-limiting transition state. Together, these insights enable the optimization of activation barriers as a function of both SCS and exogenous acid p K a and can further guide the rational design of electrocatalytic systems wherein contributions from all participants in a proton relay are considered.
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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 | 0.001 |
| 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".