Amorphous BiSn <sub>x</sub> O <sub>y</sub> for Efficient CO <sub>2</sub> Electroreduction to Formate via In Situ Doping
Bibliographic record
Abstract
ABSTRACT The practical implementation of electrochemical CO 2 reduction to formate has been limited by persistent issues concerning product selectivity, operational current density, and long‐term stability. To address these challenges, we developed an amorphous BiSn x O y precatalyst capable of overcoming conventional activity‐stability compromises, enabling efficient and durable formate production at industrially relevant current densities. The amorphous structure exhibits significantly reduced oxygen vacancy formation energy compared to its crystalline counterpart, facilitating rapid structural transformation under electrocatalytic conditions. Remarkably, this catalyst demonstrates exceptional performance, achieving a Faradaic efficiency (FE Formate ) of 95.6% at 800 mA cm −2 in a flow cell, maintaining stable operation at 500 mA cm −2 in a membrane electrode assembly (MEA) electrolyzers, and delivering an FE of 92.3% for over 160 h at 200 mA cm −2 . We further validated the practical applicability by integrating the catalyst into a solar‐powered MEA system for sustainable formate generation. Through comprehensive in situ spectroscopic characterization and density functional theory (DFT) calculations incorporating crystal orbital Hamilton population (COHP) analysis, we elucidate that Sn incorporation tailors the electronic configuration of Bi sites, optimizing the binding of the crucial *OCHO intermediate for selective formate formation. This work establishes a dynamic catalyst paradigm that transcends classical activity‐stability tradeoffs, charting an atom‐efficient pathway for industrial CO 2 valorization using renewable energy.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".