Evaluating Fly Ash‐Based Geopolymers as a Modifier for Asphalt Binders
Bibliographic record
Abstract
Severe Canadian winter conditions and growing traffic volumes are vital factors resulting in a reduction of the service life of flexible pavements. Researchers and engineers strived to develop several additives to develop balanced asphalt mixers capable of resisting distresses that caused deterioration of flexible pavements in Canada. In this study, a critical literature review regarding the use of geopolymers and their application in construction materials is provided. Moreover, an experimental matrix of laboratory testing was conducted to study the rheological and microstructural properties of the PG 58‐28 asphalt binder, with different percentages (0%, 3%, 6%, and 9%) of geopolymer. The effect of geopolymer‐curing time on rheological properties was investigated. Rotational viscometer, dynamic shear rheometer (DSR), and environmental scanning electron microscopy (ESEM) imaging devices were used to compare the performance of control binder with a binder with different percentages of geopolymers. Results indicated that the increase in the geopolymer content and the curing time affect the rheological behavior of the asphalt binder by increasing its viscosity, complex shear modulus, and failure temperature. Samples with higher geopolymer percentage exhibited better performance in terms of rutting resistance. Moreover, an increase in the failure temperature of modified asphalt binder with 9% geopolymer is recorded as 8.58%, 14.2%, and 15.2% for curing times of 2, 7, and 14 days, respectively, compared with virgin asphalt. Furthermore, the nanoparticles appear to be well dispersed in the binder, and increasing the percentage of the geopolymer does not seem to affect the microstructure of the binder. Overall research conclusion is that geopolymer application resulted in a potential enhancement of some of the properties of the asphalt 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".