Design and analysis of a thermolysis reactor for scaled-up copper-chlorine hydrogen production cycle
Bibliographic record
Abstract
Alternative hydrogen production methods are being explored with the goal of finding efficient and economical process. The copper-chlorine (Cu-Cl) cycle for hydrogen production has been the focus of the Clean Energy Research Laboratory (CERL) at the University of Ontario Institute of Technology (UOIT). The Cu-Cl cycle has lower thermal energy requirements compared to other methods and utilizes waste heat from power plants and/or some industrial processes. The cycle includes the electrolysis, hydrolysis and thermolysis reaction steps. Decomposition of copper oxychloride (CuOCuCl2) occurs in the thermolysis reactor between 480°C and 530°C. A thermolysis reactor design is presented here with the purpose of scaling it up for a pilot plant of the Cu-Cl process. Transient thermal simulations were conducted with 2.0kg of cuprous chloride (CuCl), single and dual heating sources, and 1, 2 and 4 Wm-2K-1 internal surface convection rates. The dual heater configuration provided the required temperature distribution to allow decomposition to occur. Experimental data with dual heat sources showed that surface temperatures reached 531°C ± 14.0°C. Faster heating was observed with granular CuCl in comparison to solidified CuCl, because the material was allowed to mix in the reactor while it was melted. Simulations with 10.35kg CuCl confirmed adequate surface temperatures for decomposition at low convection rates. Fouling in the phase separation section was observed: XRD analysis showed that the bottom was crystalized CuCl while the upper section was a mixture of predominately CuCl2 dihydrate and CuCl. The vapor production was due to temperatures exceeding 530°C at the CuCl-crucible interface.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".