Oxygen Vacancies Alter Methanol Oxidation Pathways on NiOOH
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Bibliographic record
Abstract
A thorough comprehension of the mechanism underlying the methanol oxidation reaction (MOR) on Ni-based catalysts is critical for future electrocatalytic design and development. However, the mechanism of MOR on these materials remains a matter of controversy. Herein, we combine in situ surface-enhanced infrared absorption spectroscopy (SEIRAS) and density functional theory (DFT) calculations to identify the active sites and determine the mechanism of MOR on monometallic Ni-based catalysts in alkaline media. The SEIRAS results show that formate and (bi)carbonate are formed after the commencement of the MOR with potential-dependent relative distributions. These spectroscopic results are in good agreement with the DFT-computed reaction profiles over an oxygen vacancy, suggesting that the MOR mainly proceeds through the formate-involving pathway, in which the early consumption of methanol yields formate as the major product, while increasing potential drives further oxidation of formate to (bi)carbonate. We also find a parallel pathway for the generation of (bi)carbonate at high potentials that bypasses the formation of formate. The two main pathways are thermodynamically more feasible than the one predominantly reported in the literature for MOR on NiOOH that involves CHO and/or CO as key intermediates. These DFT results are supported by spectroscopic evidence showing that no band associated with CHO or CO can be detected by SEIRAS, which is attributed to the nature of the oxygen vacancies as the active sites, suppressing deep dehydrogenation of CH 2 O to CHO. This work thus shows the promising role of defect engineering in promoting the electrocatalytic MOR activity and selectivity.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it