Microscopic self-healing of multi-walled carbon nanotube-modified asphalt based on the dual diffusion-energy theory
Bibliographic record
Abstract
To investigate the self-healing performance of multi-walled carbon nanotube-modified asphalt and its influencing mechanism, the asphalt molecular self-healing models were established by the molecular dynamics method. The results were analyzed based on molecular diffusion theory and surface energy repair theory. Based on the Arrhenius model, two theories were combined, and a new index healing factor was proposed to evaluate the self-healing performance by considering the diffusion characteristics and energy changes of asphalt molecules. The results show that multi-walled carbon nanotubes can accelerate the diffusion behavior of molecules in the temperature of 278--318 K to improve the self-healing properties of asphalt. Based on the proposed surface free energy equation, the self-healing properties are reasonably evaluated; the enthalpy change can be used as an index for judging the self-healing performance. The transformation model of the diffusion coefficient and cohesive work and the new index can reflect the self-healing performance more comprehensively.
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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 | 0.001 |
| 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".