Enhancing Water Repellency in Cement Concrete Through PDMS-Based Superhydrophobic Coatings
Bibliographic record
Abstract
Surface coatings such as hydrophobic and transparent coatings were applied to cement concrete surfaces using Polydimethylsiloxane (PDMS) coatings, which have nanometer-sized particles. The degree of contact between the liquid and the coated surface reveals the surface’s ability to repel water, commonly referred to as hydrophobicity. By depositing silicon coating on the surface, we successfully achieved superhydrophobicity on cement concrete, providing excellent resistance against water damage. We are striving to replicate the natural superhydrophobic properties found in nature to create artificial surfaces with similar characteristics. In this study, we experimented to develop and evaluate superhydrophobic coatings on cement concrete. The application of PDMS on the cement concrete yielded fascinating results, with the typical contact angle of the coated layer measuring 178 degrees. We utilized ImageJ software to analyze the results. This innovative approach holds great promise for enhancing water repellency in the field of construction.
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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 | 0.000 |
| 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".