High-Purity Hydrogen via the Sorption-Enhanced Steam Methane Reforming Reaction over a Synthetic CaO-Based Sorbent and a Ni Catalyst
Bibliographic record
Abstract
Sorbent-enhanced steam methane reforming (SE-SMR) is an emerging technology for the production of high-purity hydrogen from hydrocarbons with in situ CO2 capture. Here, SE-SMR was studied using a mixture containing a Ni-hydrotalcite-derived catalyst and a synthetic, Ca-based, calcium aluminate supported CO2 sorbent. The fresh and cycled materials were characterized using N2 physisorption, X-ray diffraction, and scanning and transmission electron microscopy. The combination of a Ni-hydrotalcite catalyst and the synthetic CO2 sorbent produced a stream of high-purity hydrogen, that is, 99 vol % (H2O- and N2-free basis). The CaO conversion of the synthetic CO2 sorbent was 0.58 mol CO2/mol CaO after 10 cycles, which was more than double the value achieved by limestone. The favorable CO2 capture characteristics of the synthetic CO2 sorbent were attributed to the uniform dispersion of CaO on a stable nanosized mayenite framework, thus retarding thermal sintering of the material. On the other hand, the cycled limestone lost its nanostructured morphology completely over 10 SE-SMR cycles due to its intrinsic lack of a support component.
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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) | 0.000 | 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) | 0.001 | 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".