Insights on the effect of water content in carburizing gas mixtures on the metal dusting corrosion of iron
Bibliographic record
Abstract
Constituents of syngas, such as water, carbon monoxide and sulfides, can cause the degradation of the steel pipes they move through, leading to carbon dusting and corrosion. In spite of considerable attention to this process, many questions remain about its origin. We conduct reactive molecular dynamics simulations of multi-grain iron systems exposed to carburizing gas mixtures to investigate the effect of water content on metal dusting corrosion. To simulate carbon monoxide (CO) dissociation followed by carbon diffusion, we employ an extended-ReaxFF potential that allows accounting for both the high C atoms coordination in bulk iron as well as the lower C coordination at the iron surface and interfaces. The reactions happening in the sample at different water concentrations and at different time frames are explored. We demonstrate that the presence of water on a clean Fe surface promotes different catalytic reactions at the beginning of the simulations that boost the C, H, O diffusion into the sample. At later stage, the formation of oxide scale leads to an elevated concentration of H2O/OH molecules on the surface due to the decrease in Fe affinity to dissociate water. This results into blocking the Fe catalytic sites leading to lower C and O diffusion to the bulk of the sample.
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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 | 0.002 | 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) | 0.000 | 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".