New Class of Reactive Polymer Modifiers for Asphalt: Mitigation of Low-Temperature Damage
Bibliographic record
Abstract
Results from the low-temperature performance evaluation of a new class of reactive polymer modifiers designed to improve binder-aggregate adhesion in asphalt concrete are discussed. A living free radical polymerization process was used to prepare polyisoprene (PI) with short blocks of reactive silane-functional monomer at one end of the polymer chain. Performance was evaluated with the thermal stress restrained specimen test at a cooling rate of-10°C/h. The results obtained were compared with those for unmodified and styrene-butadiene (SB)-modified mixes. When added at 3 and 6 percent by weight of the binder, SB reduced the fracture temperature of the asphalt concrete by 6°C and 9°C, respectively. Similar results were obtained with the reactive polymers. However, although all the SB-modified samples failed in a catastrophic mode, none of the samples containing the silane-functional PI did. It is hypothesized that these polymers toughened the asphalt to an extent that cracks were only able to grow in a stable mode as opposed to an unstable mode or that localized yielding occurred. The method for obtaining the desired toughening effect is flexible; lower-cost monomers, such as butadiene, and more common polymerization methods, such as emulsion or anionic polymerization techniques, could be used equally well to produce polymers with similar or better performance characteristics. An added benefit is that the tested polymers were able to improve the stripping resistance of the mix significantly.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".