Development and simulation of new electrode designs for improved hydrogen production in alkaline electrolyzers
Bibliographic record
Abstract
This study develops multiple modified electrode surface geometries which aims at enhancing the hydrogen production rates of alkaline water electrolyzers (AWEs). Subsequently, the study investigates how the developed simulation model to determine is utilized to evaluate the flow characteristics and identify the optimal electrode surface modification. The model incorporates dimpled electrode surfaces with circular, triangular, and rectangular shapes. Furthermore, we study each dimple shape in its inward, outward, and alternating configurations. The simulations show that these surface modifications can introduce localized turbulence to the flow inside the gas evolution chamber. This, in turn, improves the gas bubbles’ separation from the electrode surface. The results demonstrate a correlation between the induced turbulence from electrode surface changes and an increase in the volume fraction of evolved gases. Notably, inward-facing rectangular dimples lead to an increment in hydrogen volume fraction of up to 9.7%. This study highlights the critical role of electrode geometry in improving AWE performance and provides insights for advancing green hydrogen production technologies.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".