Valorization of Coal Fly Ash as a Stabilizer for the Development of Ni/CaO-Based Bifunctional Material
Bibliographic record
Abstract
Sorption-enhanced glycerol steam reforming (SEGSR) is considered as one of the promising processes for H 2 production by combining glycerol steam reforming with simultaneous CO 2 capture in a single-unit operation. The key challenge for a successful SEGSR process is the selection of suitable high-temperature CO 2 sorbents with high resistance to sintering. In the present work, an attempt was made to modify a CaO-based sorbent by adding different types of coal fly ash (FA1–FA12) to develop highly effective and economical CaO-based sorbents suitable for CO 2 removal at high temperatures. Among the synthesized sorbents, the 90%CaO–FA5 sorbent offered the most stable CO 2 capture activity over 20 cycles, with a CO 2 capture capacity of 0.58 g CO 2 /g sorbent at the 1st cycle and 0.45 g CO 2 /g sorbent at the 20th cycle. This can be attributed to the relatively high amounts of SiO 2 and mullite (inert materials) in FA5 compared with those of the other FA-containing samples. The presence of these inert materials helps enhancing the sorbent stability by hindering their aggregation and sintering. This sorbent was then selected to synthesize a bifunctional catalyst–sorbent material for H 2 production via SEGSR. The 15%Ni–CaO–FA5 bifunctional material exhibited a stable H 2 purity of ∼97% and a H 2 yield of ∼90% for 30 min (prebreakthrough) of the SEGSR reaction. These results highlight the high potential of FA5 as a low-cost stabilizer for improving the stability of CaO-based sorbents.
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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".