LC3 cementitious binder incorporating microencapsulated phase change materials for self-defrosting traffic surfaces
Bibliographic record
Abstract
Exposed surfaces of bridge decks, viaducts and pavements incur ice formation and accumulation of snow in cold seasons, which threatens traffic safety. Mitigating this problem using traditional methods such as deicing salts have caused ecosystem damage and inflicted substantial reinforcement corrosion and surface scaling to bridge decks and pavements, thus compromising their service life and causing colossal economic loss. This paper presents an alternative solution to overcome this problem through the development of a sustainable LC 3 cementitious material incorporating micro-encapsulated phase change material (MEPCM) with low phase transition temperature to delay the surface temperature drop and mitigate snow accumulation and ice formation. MEPCM was incorporated in the cementitious matrix at 0 %, 10 % and 20 % by binder mass. Paste and mortar mixtures were prepared to investigate the microstructural, mechanical, physical, and thermal properties. Test results showed that incorporating MEPCM in the LC 3 matrix achieved adequate compressive strength. Thermal simulations and visual observations conducted on mortar samples in the laboratory and outdoor exposure showed that MEPCM can effectively regulate the surface temperature of the LC 3 matrix and mitigate temperature drops as well as snow accumulation. Analysis of temperature data in the 2023–2024 winter season of Hamilton, Ontario, Canada indicated that the MEPCM incorporated in mortar samples could effectively regulate 40 % of the total days considered and mitigate surface ice formation and snow accumulation, which provides both economic and environmental benefits.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".