Corrosion Resistance of Sulfur–Selenium Alloy Coatings
Bibliographic record
Abstract
Despite decades of research, metallic corrosion remains a long-standing challenge in many engineering applications. Specifically, designing a material that can resist corrosion both in abiotic as well as biotic environments remains elusive. Here a lightweight sulfur-selenium (S-Se) alloy is designed with high stiffness and ductility that can serve as an excellent corrosion-resistant coating with protection efficiency of ≈99.9% for steel in a wide range of diverse environments. S-Se coated mild steel shows a corrosion rate that is 6-7 orders of magnitude lower than bare metal in abiotic (simulated seawater and sodium sulfate solution) and biotic (sulfate-reducing bacterial medium) environments. The coating is strongly adhesive, mechanically robust, and demonstrates excellent damage/deformation recovery properties, which provide the added advantage of significantly reducing the probability of a defect being generated and sustained in the coating, thus improving its longevity. The high corrosion resistance of the alloy is attributed in diverse environments to its semicrystalline, nonporous, antimicrobial, and viscoelastic nature with superior mechanical performance, enabling it to successfully block a variety of diffusing species.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".