Characterization of the Enhancement Effect of Na<sub>2</sub>CO<sub>3</sub> on the Sulfur Capture Capacity of Limestones
Bibliographic record
Abstract
It has been known for a long time that certain additives (e.g., NaCl, CaCl2, Na2CO3, Fe2O3) can increase the sulfur dioxide capture-capacity of limestones. In a recent study we demonstrated that very small amounts of Na2CO3 can be very beneficial for producing sorbents of very high sorption capacities. This paper explores what contributes to these significant increases. Mercury porosimetry measurements of calcined limestone samples reveal a change in the pore-size from 0.04-0.2 microm in untreated samples to 2-10 microm in samples treated with Na2CO3--a pore-size more favorable for penetration of sulfur into the particles. The change in pore-size facilitates reaction with lime grains throughout the whole particle without rapid plugging of pores, avoiding premature change from a fast chemical reaction to a slow solid-state diffusion controlled process, as seen for untreated samples. Calcination in a thermogravimetric reactor showed that Na2CO3 increased the rate of calcination of CaCO3 to CaO, an effect which was slightly larger at 825 degrees C than at 900 degrees C. Peak broadening analysis of powder X-ray diffraction data of the raw, calcined, and sulfated samples revealed an unaffected calcite size (approximately 125-170 nm) but a significant increase in the crystallite size for lime (approximately 60-90 nm to approximately 250-300 nm) and less for anhydrite (approximately 125-150 nm to approximately 225-250 nm). The increase in the crystallite and pore-size of the treated limestones is attributed to an increase in ionic mobility in the crystal lattice due to formation of vacancies in the crystals when Ca is partly replaced by Na.
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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".