Experimental evaluation of photocatalytic and photoelectrochemical hydrogen fuel production with metal-based catalysts, electrodes and coatings in a novel manner
Bibliographic record
Abstract
In this work, transition-metal based photoelectrodes are developed and tested across three permutations, including pristine copper oxide mesh, titania coated, and nickel-zinc-iron oxide (NiZnFeO)/titania coated copper oxide mesh. Additionally, NiZnFeO photocatalyst’s performance for photocatalytic hydrogen production is assessed. Subsequently, an integrated cell combining both photocatalytic and photoelectrochemical effects is considered. The novelty of this work is assessing the combination of NiZnFeO photocatalyst with titania in photoelectrochemical settings as well as developing an integrated hybrid system combining both photoelectrochemical and photocatalytic effects. For the photoelectrochemical system, the highest current density is attributed to the titania-coated copper oxide mesh photoelectrode, with values of −1.17 mA/cm 2 and −2.92 mA/cm 2 , for dark and light conditions, respectively, at −0.6 V vs Ag/AgCl, and with an onset potential of −0.18 V vs Ag/AgCl. Additionally, the integrated cell shows a current density of −1.71 mA/cm 2 at −0.6 V vs Ag/AgCl. The optimization study on a NiZnFeO photocatalyst is conducted with the objective function of maximizing hydrogen concentration to fine-tune factors such as catalyst loading, sacrificial agent molarity, and temperature. The highest obtained hydrogen concentration after 30 min and under simulated solar light is 26 ppm, at an energy efficiency of 1.83 %, with optimum conditions of 15 mg/100 ml catalyst loading, 1 M of triethanolamine sacrificial agent, and 35 °C temperature.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".