Conductive Zeolite Supported Indium–Tin Alloy Nanoclusters for Selective and Scalable Formic Acid Electrosynthesis
Bibliographic record
Abstract
Abstract Upgrading excess CO 2 toward the electrosynthesis of formic acid is of significant research and commercial interest. However, simultaneously achieving high selectivity and industrially relevant current densities of CO 2 ‐to‐formate conversion remains a grand challenge for practical implementations. Here, an electrically conductive zeolite support is strategically designed by implanting Sn ions into the skeleton structure of a zeolite Y, which impregnates ultrasmall In 0.2 Sn 0.8 alloy nanoclusters into the supercages of the tailored 12‐ring framework. The prominent electronic and geometric interactions between In 0.2 Sn 0.8 nanoalloy and zeolite support lead to the delocalization of electron density that enhances orbital hybridizations between In active site and *OCHO intermediate. Thus, the energy barrier for the rate‐limiting *OCHO formation step is reduced, facilitating the electrocatalytic hydrogenation of CO 2 to formic acid. Accordingly, the developed zeolite electrocatalyst achieves an industrial‐level partial current density of 322 mA cm −2 and remarkable Faradaic efficiency of 98.2% for formate production and stably maintains Faradaic efficiency above 93% at an industrially relevant current density for over 102 h. This work opens up new opportunities of conductive zeolite‐based electrocatalysts for industrial‐level formic acid electrosynthesis from CO 2 electrolysis and toward practically accessible electrocatalysis and energy conversion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".