Microstructural engineering of high-content rubber asphalt via precision devulcanization for enhanced performance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction The practical deployment of high-content rubberized asphalt is often hindered by its compromised workability and unstable performance. Moving beyond conventional devulcanization approaches, this study introduces an integrated strategy of interface-controlled devulcanization and microstructural tailoring to address these challenges. Methods A bespoke devulcanizing agent (RubberSynth-AP) was synthesized to promote selective scission of sulfur-based crosslinks and improve interfacial adhesion. Coupled with an optimized production process, this method allows the stable integration of crumb rubber at concentrations up to 30% by binder weight. Multi-scale rheological analyses—encompassing temperature sweeps, multiple stress creep recovery (MSCR), and linear amplitude sweep (LAS) tests—were employed. Results An optimum rubber content of 26% was identified, exhibiting a superior combination of properties: a failure temperature of 76.5 °C, 40% lower viscosity, 53.12% recovery rate, and enhanced fatigue resistance. Mechanistic analysis uncovered a microstructural evolution from a heterogeneous, stress-concentrating system to a homogeneous, elastic-network-dominated morphology. This structural improvement supported the adoption of a dense-graded AC-13 mixture design, achieving a remarkable dynamic stability of 3,850 cycles/mm. Economically and environmentally, this technique promotes the consumption of 18 tons of waste rubber per lane-kilometer with a cost reduction of approximately ¥17,000. Discussion Collectively, this study demonstrates that the interface-controlled devulcanization strategy enables the production of high-content rubberized asphalt (up to 30%) with superior and balanced rheological properties, overcoming the longstanding workability-performance trade-off. The findings provide a scientifically-grounded and economically viable solution for developing sustainable pavement materials.
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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 it