Photoelectrochemical CO<sub>2</sub> Reduction into Syngas with the Metal/Oxide Interface
Bibliographic record
Abstract
Photoelectrochemical (PEC) reduction of CO2 with H2O not only provides an opportunity for reducing net CO2 emissions but also produces value-added chemical feedstocks and fuels. Syngas, a mixture of CO and H2, is a key feedstock for the production of methanol and other commodity hydrocarbons in industry. However, it is challenging to achieve efficient and stable PEC CO2 reduction into syngas with controlled composition owing to the difficulties associated with the chemical inertness of CO2 and complex reaction network of CO2 conversion. Herein, by employing a metal/oxide interface to spontaneously activate CO2 molecule and stabilize the key reaction intermediates, we report a benchmarking solar-to-syngas efficiency of 0.87% and a high turnover number of 24 800, as well as a desirable high stability of 10 h. Moreover, the CO/H2 ratios in the composition can be tuned in a wide range between 4:1 and 1:6 with a total unity Faradaic efficiency. On the basis of experimental measurements and theoretical calculations, we present that the metal/oxide interface provides multifunctional catalytic sites with complementary chemical properties for CO2 activation and conversion, leading to a unique pathway that is inaccessible with the individual components. The present approach opens new opportunities to rationally develop high-performance PEC systems for selective CO2 reduction into valuable carbon-based chemicals and fuels.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".