Chemical model to explain asphalt binder and asphalt–aggregate interface behaviors
Bibliographic record
Abstract
The behavior of asphalt mixtures is very complicated due to structural configuration and interfacial friction of aggregates as well as chemical and rheological reactions of the asphalt binder itself or with the aggregates. Furthermore, this complex response is more complicated under various loads, temperatures, and other environmental factors. To control the complex responses and reduce the complex factors, a DSR moisture damage test using small rock disks was developed. This paper focuses on the more fundamental concepts to explain asphalt and asphalt–aggregate bond behavior exhibited under the newly-developed DSR moisture damage test. The traditional model of asphalt structure is based on the theory of colloid and surface chemistry. Although this traditional model can explain many physical phenomena of asphalt structure, it cannot explain all the asphalt behaviors, such as steric hardening. Therefore, more general, but fundamental concepts may be required to attain insight of the material. As one of the possible concepts, a self-assembly concept in supramolecular chemistry is proposed and phenomena and results of the DSR moisture damage test are explained by the concept.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".