Recent advances of metal suboxide catalysts for carbon‐neutral energy applications
Bibliographic record
Abstract
Abstract Metal suboxides have emerged as a class of promising candidates for many electrocatalytic applications owing to their enhanced electrical conductivity and chemical activities. In this review, we have summarized the recent progress of metal suboxides. We have firstly introduced the discovery of metal suboxides, and their categories according to element tables. Then various metal suboxides synthetic methods have been systematically illustrated involving solid‐state synthesis, high‐temperature synthesis, low‐temperature synthesis and plasma‐driven synthetic methods, etc. In addition, their applications have been demonstrated in the field of water, carbon and nitrogen cycle‐based energy catalysis technologies involving electrochemical hydrogen evolution reaction, oxygen evolution reaction, oxygen reduction reaction, carbon dioxide reduction, urea oxidation reaction, methanol oxidation reaction, nitrogen reduction reaction and nitrate reduction reaction, etc. Finally, we make a brief conclusion about the developments of metal suboxides, giving an outlook for future research challenges. These insights are expected to hold promise for developing metal suboxide catalysts toward practical applications.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".