Synthesis and Characterization of Benzilate Esters as Aqueous Corrosion Inhibitors for Mild Steel and 2024, 6061, and 7075 Aluminum Alloys
Bibliographic record
Abstract
In this investigation, synthesis and characterization of environmentally friendly metallo-organic corrosion inhibitors for protection of mild steel and certain aluminum alloys are being sought to replace hexavalent chromium based corrosion inhibitors. For this reason, several corrosion inhibiting species such as benzilic acid and metal oxyanions were combined in a single compound with the general formula, (M)x(benzilicacid)y(M?aOb)z. First group of such compounds were synthesized in a similar study of the first author reported in another study with the title of “Synthesis and Characterization of Salts and Esters of Hydroxy Acids as Corrosion Inhibitors for Mild Steel and Aluminum Alloys” and this work aims to build on the success of those compounds since theoretically, there is no reason why benzilates cannot be good replacements for a-hydroxy acids such as gluconates. Additionally, benzilates are less soluble in general than hydroxyl acids, which could result in a corrosion inhibiting compound with an optimum window of solubility. Practical results have mostly proven the hypothesized advantages of benzilates correct and yielded that certain salts and esters of benzilates can be suitable corrosion inhibitors for certain metals and their alloys.
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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 | 0.001 |
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".