Electrocatalytic conversion of methane: Recent progress and future prospects
Bibliographic record
Abstract
Methane has gained significant attention due to its abundant reserves and notable greenhouse effect. Electrocatalytic conversion of methane is an efficient and green pathway proceeding under mild conditions. However, the low solubility of methane in aqueous electrolytes imposes mass transfer limitations, leading to low current densities in electrocatalytic reactions and hindering large-scale production. This paper discusses the recent progress in quite a few aspects of electrocatalytic conversion of methane. Firstly, the reaction mechanisms involved in methane electrocatalysis are summarized, including dehydrogenation and C–H bond cleavage mediated by the active species. Next, we discuss how to promote electrochemical methane conversion regarding both the reaction process and mass transfer from the perspective of chemical engineering. Considerable efforts have been done to enhance the reaction process, including developing efficient electrocatalyst and devices. Meanwhile, the enhancement of transport processes via, e.g. improving the solubility of methane and modification on the transport area and distance, also facilitates more efficient methane conversion. Finally, an outlook on future development challenges is provided.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".