Investigation of self-healing properties of nanoclay-modified asphalt binder using two-piece healing test
Bibliographic record
Abstract
Asphalt's self-healing properties demonstrate the capability to partially or even fully restore the damage caused by external loads, which could be improved using innovative modifying materials. In this study, the impact of nanoclays on asphalt performance grading (PG), complex shear modulus, and self-healing properties are investigated on a laboratory scale. The intrinsic healing phenomenon of the analyzed binders is measured using a two-piece healing test. Prepared by high shear mixing, the modified binders containing different dosages of two types of organo-modified montmorillonites were evaluated in this paper. In addition to the Superpave PG, the dispersion method's effectiveness was analyzed using a scanning electron microscope. This study indicates that nanoclays improve the high-temperature performance grade of the binder, while they do not hinder the low-temperature performance. Finally, nanoclay-modified binders showed higher shear strength and improved self-healing properties compared to the unmodified binder.
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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".