A review of the mechanical and leaching performance of stabilized/solidified contaminated soils
Bibliographic record
Abstract
Stabilization/solidification (S/S) technology, which basically involves chemical fixation and immobilization of contaminants (primarily metals) in the matrix of cementitious binders, is widely used for treatment of contaminated soils. This paper presents a critical review of the performance of commonly used blended binder systems in S/S technology. The binders considered are Portland cement and blends of cement–fly ash, cement–slag, lime–slag, and lime–fly ash. This work compares and evaluates the performance of contaminated soils treated by the binders in terms of commonly used mechanical and leaching properties, including unconfined compressive strength (UCS), bulk density, hydraulic conductivity, and leachability. The long-term performance of S/S-treated soils is also reviewed. It was observed that the inclusion of slag in a binder blend gave superior performance compared to fly ash. Generally, the leachability of common contaminants in soil can be reduced to acceptable levels with approximately 20%–35% dosage of the different binders. The UCS was observed to be optimum around the optimum water content for compaction. The hydraulic conductivity was approximately 10 −9 m/s over time. Long-term performance of treated soils showed consistent effectiveness over a period of 5–14 years with fluctuations in mechanical and leaching behaviour caused by the complex nature and variability of S/S-treated soils.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".