Optimizing coal gasification slag utilization: Predictive modeling and hydration mechanism of blast furnace slag replacement in solid waste cementitious materials
Bibliographic record
Abstract
Coal gasification slag (CGS), a by-product of the coal gasification process, is produced in large quantities but remains underutilized, posing environmental challenges. This study investigates the feasibility of partially substituting blast furnace slag (BFS) with CGS in the preparation of solid waste cementitious materials (SWCM), aiming to enhance resource utilization and reduce costs. A constrained mixing test design was employed to optimize the proportions of CGS, BFS, steel slag (SS), and desulphurization gypsum (DG), and a regression model was developed to predict compressive strength at 3, 7, and 28 days. The optimal mix (20 % CGS, 23 % BFS, 37 % SS, 20 % DG) achieved a 28-day compressive strength of 57.1 MPa, with the model demonstrating high predictive accuracy (Adj-R 2 up to 95.27 %). Microscopic analyzes (XRD, SEM-EDS, XPS, TG-DTG/DSC) revealed that CGS contributes abundant aluminosilicate glass, promoting the formation of C-(A)S-H gels and AFt, which enhance strength and densify the microstructure. The study confirms that CGS can effectively replace BFS in SWCM, providing a theoretical basis for large-scale, sustainable utilization of CGS in construction materials.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".