New Photoelectrochemical Reactor for Hydrogen Generation: Experimental Investigation
Bibliographic record
Abstract
In the scope of this study, a new photoelectrochemical (PEC) reactor, comprising a novel geometry for effective absorption of sunlight, is developed conceptually, and tested and assessed experimentally. The conic mesh structure of the photoelectrode offers maximizing the performance via passive tracking of solar light during daylight. In sequence, electrodeposition and sol–gel dip coating techniques are practiced, fabricating a copper oxide semiconductor as a working electrode and a titanium dioxide-coated electrode as the counter electrode. The new reactor concept is experimentally assessed for various conditions through electrochemical tests including open circuit potential, linear sweep voltammetry, cyclic voltammetry, and PWR potentiostatic tests. Energy and exergy efficiencies and hydrogen production rates are evaluated for various experimental conditions implying with and without light. The highest hydrogen production rate corresponding to 4.48 μg H 2 /s at near-atmospheric conditions (25 °C temperature and 101.3 kPa pressure) is obtained with the applied external bias of 2.25 V, where the reactor operates under artificial solar light with an intensity of 1000 W/m 2 . The produced photocurrent density is determined to be 1.81 mA/cm 2, corresponding to a photo-conversion efficiency of 1.84%. For these operational conditions, the energetic and exergetic efficiencies of the reactor are evaluated as 0.866 and 0.878%, respectively. Without light case, the PEC reactor acting as an electrolyzer operates with energetic and exergetic electrolysis efficiencies of 56.51 and 54.38%, 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".