Templating Bicarbonate in the Second Coordination Sphere Enhances Electrochemical CO <sub>2</sub> Reduction Catalyzed by Iron Porphyrins
Bibliographic record
Abstract
Bicarbonate-based electrolytes are ubiquitous in aqueous electrochemical CO 2 reduction, particularly in heterogenous catalysis, where they demonstrate improved catalytic performance relative to other buffers. In contrast, the presence of bicarbonate in organic electrolytes and its roles in homogeneous electrocatalysis remain underexplored. Here, we investigate the influence of bicarbonate on iron porphyrin-catalyzed electrochemical CO 2 reduction. We show that bicarbonate is a viable proton donor in organic electrolyte (p K a = 20.8 in dimethyl sulfoxide) and that urea pendants in the second coordination sphere can be used to template bicarbonate in the vicinity of a molecular iron porphyrin catalyst. The templated binding of bicarbonate increases its acidity, resulting in a 1500-fold enhancement in catalytic rates relative to unmodified parent iron porphyrin. This work emphasizes the importance of bicarbonate speciation in wet organic electrolytes and establishes second-sphere bicarbonate templating as a design strategy to harness this adventitious acid and enhance CO 2 reduction catalysis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.001 | 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".