Heterogenous Preparations of Solution-Processable Cobalt Phthalocyanines for Carbon Dioxide Reduction Electrocatalysis
Bibliographic record
Abstract
The development and implementation of technology that can capture and transform carbon dioxide (CO2) is of ongoing interest. To that end, the integration of molecular electrocatalysts into devices is appealing because of the desirable features of molecules, such as the ability to modify active sites. Here, we explore how the identity of the aliphatic group in 1,4,8,11,15,18,22,25-octaalkoxyphthalocyanine cobalt(II) affects the catalytic behavior for heterogeneous CO2 reduction electrocatalysis. The alkyl R-groups correspond to n-butoxy, sec-butoxy, and 2-ethylhexoxy. All of the catalysts are soluble in organic solvents and are readily solution-processed. However, the larger 2-ethylhexoxy group showed solution aggregation behavior at concentrations ≥1 mM, and it was, in general, an inferior catalyst. The other two catalysts show comparable maximum currents, but the octa sec-butoxy-bearing catalyst showed larger CO2 reduction rate constants based on foot-of-the-wave analyses. This behavior is hypothesized to be due to the ability of the sec-butoxy groups to eliminate the ability of the alkoxy oxygen to block Co Sites via ligation. CO2 reduction activity is rationalized based on solid-state structures. Cobalt(II) phthalocyanine and its derivatives are known to be good CO2 reduction catalysts, but the results from this work suggest that straightforward incorporation of bulky groups can improve the processability and per site activity by discouraging aggregation.
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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 | 0.000 |
| 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".