Enhanced Electrocatalytic Hydrogen Peroxide Production via a CuWO<sub>4</sub>/WO<sub>3</sub> Heterojunction with High Selectivity and Stability
Bibliographic record
Abstract
The electrocatalytic conversion of oxygen to hydrogen peroxide offers a promising pathway for sustainable energy production. However, the development of catalysts that are highly active, stable, and cost-effective for hydrogen peroxide synthesis remains a significant challenge. In this study, a novel polyacid–based metal–organic coordination compound (Cu–PW) was synthesized using a hydrothermal approach. Cu–PW served as a precursor to construct a composite electrocatalyst featuring a heterointerface between CuWO 4 and WO 3 (CuWO 4 /WO 3 ) through pyrolysis. The CuWO 4 /WO 3 heterojunction exhibits an impressive H 2 O 2 selectivity of 91.84% at 0.5 V, marking a 19.65% improvement compared to the pristine Cu–PW. Furthermore, the CuWO 4 /WO 3 catalyst demonstrates exceptional stability, maintaining continuous operation for 29 h. At 0.1 V, it delivers a hydrogen peroxide yield of 1537.8 mmol g –1 h –1, with a Faraday efficiency (FE) of 85%. Additionally, this catalyst effectively degrades methyl blue, achieving a 95% removal from an aqueous system within 30 min. Theoretical analysis further corroborates the high electroactivity of CuWO 4 /WO 3 heterojunction structure. The Cu–O–W bridge formed during the reaction facilitates interfacial electron transport and enhances the role of the W–O bond in proton adsorption and transfer kinetics. This strong interfacial coupling in CuWO 4 /WO 3 promotes electron transfer and the formation of *OOH intermediates, thereby favoring hydrogen peroxide generation. Hence, the as-prepared CuWO 4 /WO 3 demonstrates great potential as an efficient electrocatalyst for the green synthesis of hydrogen peroxide, exhibiting high efficiency as a two-electron oxygen reduction reaction catalyst. This work offers a new approach for fabricating CuWO 4 /WO 3 electrocatalyst with high electroactivity and selectivity, paving the way for cost-effective and sustainable hydrogen peroxide production, significantly reducing reliance on the conventional anthraquinone process.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".