Mixed Redox-Couple-Involved Bornite Phase Cu<sub>5</sub>FeS<sub>4</sub> as Efficient and Robust Cocatalysts for Greatly Enhanced Visible-Light Photocatalytic Activities
Bibliographic record
Abstract
Design and conception of a competent photocatalyst for water splitting and photodegradation are critical for energy transformation and environmental remediation. Herein, for the first time, we demonstrated that mixed redox-couple-involved bornite phase Cu 5 FeS 4 could act as an efficient and robust cocatalyst for graphitic C 3 N 4 (g-C 3 N 4 ), which enables the achievement of considerably boosted visible-light photocatalytic activities in both H 2 evolution and pollutant degradation reactions. Under visible-light irradiation, the optimized g-C 3 N 4 /Cu 5 FeS 4 heterojunction presented a remarkably increased H 2 production rate of 27.92 μmol g –1 h –1 (without involving any noble metals) and methyl orange (MO) photodegradation rate of 2.18 min –1 g –1 compared with those of g-C 3 N 4 and Cu 5 FeS 4 . To be more specific, these rates are ∼15 and 3 times higher than those of pure g-C 3 N 4 in these two reactions, where the pure Cu 5 FeS 4 did not show any activities. The enhanced photocatalytic performance was identified to be due to the presence of a “mixed redox-couple” of Cu(I)–S–Fe(III), which enhanced charge separation efficiency between g-C 3 N 4 and Cu 5 FeS 4, consequently facilitating the overall reaction kinetics. Overall, our work not only demonstrates the immense potential of using mixed redox-couple-involved bornite phase Cu 5 FeS 4 as the cocatalyst in photocatalysis but also expedites the designing and discovering of novel photocatalytic systems based on the proposed concept of the mixed redox-couple.
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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) | 0.000 | 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) | 0.000 | 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 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".