Optimizing Chloride and Calcium Ion Extraction from Municipal Solid Waste Incineration Fly Ash from Zhoushan, China: Effects of Leaching Conditions and Industrial Applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Municipal solid waste incineration (MSWI) fly ash, containing substantial amounts of calcium (Ca), chloride (Cl), and other valuable elements, offers promising potential as a raw material for carbon capture, utilization (CCU), and alkali production. Despite numerous approaches being explored to enhance calcium ion leaching from fly ash, the combined effects of salt and leaching conditions on ion extraction have not been thoroughly investigated. This study provides a comprehensive examination of various leaching conditions, including primary leaching—optimal for efficiency—secondary leaching, which achieved the highest leaching rate, and reverse secondary leaching, focusing on their impact on calcium extraction efficiency. Considering optimal leaching efficiency and resource utilization, this study identifies the most favorable industrial conditions as a 15 min leaching time, a stirring speed of 200 rpm, a temperature of 25 °C, and a 1:10 liquid-to-solid ratio (L/S ratio). The application of a 6% NaCl solution in salt-assisted leaching elevated the calcium ion concentration from 4101.5 mg/L to 4662.6 mg/L, indicating a substantial improvement in leaching performance. Additionally, in carbonate-assisted and ultrasound-assisted leaching, the introduction of CO2 further increased calcium extraction amounts, but it did not enhance efficiency, while ultrasonic intervention had minimal impact. This research investigates enhanced efficiencies through multiple optimized and assisted leaching conditions, advancing MSWI fly ash utilization in carbon capture applications while paving new pathways for sustainable industrial practices that could revolutionize waste management and support global environmental objectives.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it