Enhancement of the Sulfur Capture Capacity of Limestones by the Addition of Na<sub>2</sub>CO<sub>3</sub> and NaCl
Bibliographic record
Abstract
The ability of Na2CO3 and NaCl to enhance the sulfur capture capacity of three limestones was evaluated via fixed-bed calcination and sulfation experiments. The tested limestones represent three different sulfation morphologies: unreacted-core, network, and uniformly sulfated. Treatment with aqueous or powdered Na2CO3 significantly increased the Ca-utilization for two stones which normally sulfate in an unreacted-core pattern (20% to 45%) and network pattern (33% to 49%). The increase was lower for the uniformly sulfated stone (44% to 48%). Na2CO3 treatment increased the number of macropores leading to uniform sulfation of all particles, nearly eliminating the normal strong dependence of utilization on limestone type and particle size. The effect of Na2CO3 is believed to be associated with formation of a eutectic melt which enhances ionic diffusion and accelerates molecular rearrangement of the CaO. Treatment with aqueous NaCl solution caused a decrease in utilization, probably due to formation of large grains and plugging of pores caused by formation of a large amount of eutectic melt. The effect of Na2CO3 is less sensitive than that of NaCl to the amount added and the combustion environment (temperature and gas composition). In addition, Na2CO3 neither promotes corrosion nor forms chlorinated byproducts, which are main concerns associated with NaCl. Thus, Na2CO3 appears to have significant advantages over NaCl for enhancement of limestone sulfur capture capacity in fluidized-bed combustors.
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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".