Effect of De-icer and Anti-icer Chemicals on the Durability, Microstructure, and Properties of Cement-based Materials
Bibliographic record
Abstract
A comprehensive study was conducted on the effects of de-icer and anti-icer chemicals on cement-based materials. Portland cement mortars and concretes were exposed to over 16 chloride-based and non-chloride-based generic and commercial products and changes in cement-based material properties were measured. Deleterious chemical actions of several types of these products on cement-based materials were observed, departing from the well-known position that attributes the concrete damage from such salts mainly to physical actions under freezing and thawing exposure. \n\nIndependent of freezing and thawing exposure, mortars and concretes exposed to concentrated calcium chloride and magnesium chloride solutions were found to undergo severe deterioration whereas those exposed to sodium chloride did not. The mechanisms of deterioration are complex with factors such as concentration, temperature, and availability of calcium hydroxide playing important roles. It was found that the formation of calcium oxychloride of the form 3Ca(OH)2.CaCl2.12H2O, and the 3- and 5-form magnesium oxychloride, 3Mg(OH)2.MgCl2.8H2O and 5Mg(OH)2.MgCl2.8H2O, were the main causes for the severe deterioration, and to a lesser extent brucite, gypsum, and magnesium silicate hydrate (M-S-H). The instability of these oxychloride compounds when subjected to conditions normally encountered in sample preparation is suggested as the reason why field investigations have failed to relate distressed concrete to chemical attack by such de-icer and anti-icer chemicals.\n\nConcentrated solutions of calcium magnesium acetate were also found to be harmful to cement-based materials by dissolution of calcium hydroxide and formation of calcium acetate hydrate, whereas low concentrated solutions tended to cause slow deterioration by magnesium attack forming brucite, gypsum, and M-S-H. Potassium acetate chemicals did not cause significant deterioration in mortars when these products were diluted (25% by mass), but undiluted products (50% by mass) caused considerable distress in concrete specimens. \n\nThe combined effect of chemical attack impairing concrete mechanical properties and subsequent salt scaling damage was proposed as the most likely mechanisms of field deterioration.
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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".