Experimental and Theoretical Investigation of Solar Molten Media Methane Cracking for Hydrogen Production
Bibliographic record
Abstract
Canada is the largest H2 consumer per capita in the world, giving a strong market demand for H2. H2 is commercially produced using steam CH4 reforming, which is energy and CO2 intensive. Solar molten metal CH4 cracking is an alternative zero emissions technology. Solar radiation is focused with large curved mirrors onto the molten metal. The molten media provides improved heat transfer, a thermal storage medium against transient solar flux, and a unique method of separating H2 and C. Blank and molten metal alumina tube reactors are studied from 1023 K to 1323 K. Plug flow, perfectly mixed, and combined perfectly mixed with a bypass (CPMR) reactor models were numerically implemented to simulate the blank reactor and determine the kinetic parameters. The CPMR model incorporated a third parameter that dictates how much how travels through the bypass. Results for the CPMR model showed k0 = 5.43e15 1/s, Ea = 420.7 kJ/mol and β = 0.426. The CPMR model was shown to have 8.3% ± 6.8% average error against data found in literature. Sn was selected as the bath material for the molten metal reactor (MMR), and the reaction gas was bubbled through the bath using an injector. 18.9% conversion was obtained at 1273 K, and near zero conversion for lower temperatures. A numerical model of the MMR was implemented using a spherical bubble model coupled with the CPMR model for the blank space above the molten metal. The MMR model showed that the majority of CH4 conversion occurred in the blank space above the bath. Decreasing bubble size and increasing bath height improved bubble conversion.
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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 | 0.000 | 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".