Experimental investigation and performance assessment of magnesium-based hydrogen generation
Bibliographic record
Abstract
• Mg based hydrogen production is uniquely studied using Mg powder and scraps. • The effects of various effects and parameters on hydrogen production are assessed. • It appears to be an effective option for waste Mg for hydrogen production. • Mg powder gives better hydrogen production results. This paper investigates a uniquely designed experimental hydrogen production system with a distillation unit through magnesium hydrolysis. Two types of magnesium sources were tested: 100-µm powder particles and magnesium scrap, with their microstructures analyzed by scanning electron microscopy. Hydrolysis reactions were conducted at room temperature (19 °C-22 °C) to study the effect of environmentally friendly solutions on reaction kinetics and hydrogen production. Various solutions were evaluated, including NaCl and NaOH as additives. Among the samples, the highest hydrogen capacity was achieved using 7 wt% NaCl with magnesium powder, reaching 1.38 mL H 2 /g Mg in 15 min. In comparison, simulated seawater (3.5 wt% NaCl) produced 1.18 mL H 2 /g Mg over the same period. Hydrogen production was monitored by measuring the instantaneous hydrogen generation rate (mL/min) and calculating cumulative hydrogen capacity throughout the reaction.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".