The influence of different zeolitic supports on hydrogen production and waste degradation
Bibliographic record
Abstract
Abstract The photocatalyst composition affects the chemical–physical properties and directly impacts photocatalytic activity, both in the hydrogen production and degradation of organic contaminants. In this work, the influence of zeolitic structures NaA, NaY, and ZSM‐5 combined with a 10% active phase, TiO 2 catalyst doped with 1% copper, and cobalt cocatalysts was tested to mineralize the reactive blue dye (CI250) and to produce hydrogen by photocatalysis under ultraviolet radiation. The band gap energy was affected mainly by the cocatalyst, while the Brunauer‐Emmett‐Teller method (BET) area was affected by the zeolite structure as well as the X‐ray diffraction (XRD). The most active catalyst was the Cu@TiO 2 /NaY, which promoted a hydrogen production rate of 240 μmolH 2 gcat −1 using 10% ethanol (v/v) aqueous solution as a sacrificial agent and mineralization of 53% of the organic dye, followed by the catalysts impregnated on ZSM‐5 zeolites, which had discolouration up to 50% and hydrogen evolution of 92.6 and 109.7 μmolH 2 gcat −1 for the catalyst doped with Cu and Co, respectively.
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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 | 0.001 |
| 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 | 0.001 | 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".