Kinetic Modeling and Quantum Yields: Hydrogen Production via Pd-TiO2 Photocatalytic Water Splitting under Near-UV and Visible Light
Bibliographic record
Abstract
A palladium (Pd) doped mesoporous titanium dioxide (TiO2) photocatalyst was used to produce hydrogen (H2) via water splitting under both near-UV and visible light. Experiments were carried out in the Photo-CREC Water-II Reactor (PCW-II) using a 0.25 wt% Pd-TiO2 photocatalyst, initial pH = 4 and 2.0 v/v% ethanol, as an organic scavenger. After 6 h of near-UV irradiation, this photocatalyst yielded 113 cm3 STP of hydrogen (H2). Furthermore, after 1 h of near-UV photoreduction followed by 5 h of visible light, the 0.25 wt% Pd-TiO2 photocatalyst yielded 5.25 cm3 STP of H2. The same photocatalyst, photoreduced for 24 h under near-UV and subsequently exposed to 5 h of visible light, yielded 29 cm3 STP of H2. It was observed that the promoted redox reactions led to the production of hydrogen and by-products such as methane, ethane, ethylene, acetaldehyde, carbon monoxide, carbon dioxide and hydrogen peroxide. These redox reactions could be modeled using an “in series-parallel” reaction network and Langmuir Hinshelwood based kinetics. The proposed rate equations were validated using statistical analysis for the experimental data and calculated kinetic parameters. Furthermore, Quantum yields (QYH•%) based on the H• produced were also established at promising levels: (a) 34.8% under near-UV light and 1.00 g L−1 photocatalyst concentration; (b) 8.8% under visible light and 0.15 g L−1. photocatalyst concentration following 24 h of near-UV.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".