Inhibition and compressive-strength performance of Na<sub>2</sub>Cr<sub>2</sub>O<sub>7</sub> and C<sub>10</sub>H<sub>14</sub>N<sub>2</sub>Na<sub>2</sub>O<sub>8</sub>·2H<sub>2</sub>O in steel-reinforced concrete in corrosive environments
Bibliographic record
Abstract
This paper studied corrosion-inhibition and compressive-strength performances of Na 2 Cr 2 O 7 (sodium dichromate) and C 10 H 14 N 2 Na 2 O 8 ·2H 2 O (ethylenediaminetetraacetic disodium salt: EDTA-Na 2 ) admixtures in steel-reinforced concrete immersed in NaCl and in H 2 SO 4 corrosive environments. Electrochemical methods were used for studying corrosion responses of different concentrations of the individual admixtures and their synergies, in the model that partially replace the toxic Na 2 Cr 2 O 7 by the environmentally-friendly C 10 H 14 N 2 Na 2 O 8 ·2H 2 O, in steel-reinforced concretes. After the electrochemical experiment, the steel-reinforced concrete samples were subjected to the compressive-strength testing and analyses of ASTM C39/C39M-03 and ASTM C267-01(2012). Results showed that the use of environmentally-friendly EDTA-Na 2 for partially replacing toxic Na 2 Cr 2 O 7 chemical exhibited better corrosion-inhibition and compressive-strength improvement in the NaCl-immersed concretes, than in the H 2 SO 4 -immersed concretes. The 2 g Na 2 Cr 2 O 7 + 6 g EDTA-Na 2 admixture (representing partial replacement model of 6 g Na 2 Cr 2 O 7 by 6 g EDTA-Na 2 ) exhibited optimal corrosion inhibition efficiency (η = 99.0%) and very good compressive-strength improvement advantage in the NaCl-immersed concretes. In contrast, comparatively low compressive-strength reduction trade-off with the good inhibition effectiveness of η = 79.9% support use of 6 g EDTA-Na 2 admixture only (i.e., without Na 2 Cr 2 O 7 addition) for inhibiting reinforcing-steel corrosion in the H 2 SO 4 -immersed concretes.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.006 | 0.007 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.005 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.007 |
| 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; both teacher heads agree on what is shown here.
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".