Influence of carbon and sulfur on austenite grain boundary mobility
Bibliographic record
Abstract
The effects of carbon and residual sulfur on the grain boundary (GB) mobility in austenite were studied by in situ experiments, density functional theory (DFT) and mean field simulations. Fe-C samples with carbon contents ranging from 0.15 wt.-% to 0.46 wt.-%, containing impurities S (<25 wt. ppm) and P (<25 wt. ppm), were investigated under isothermal annealing conditions at 1050–1350 °C. High-temperature laser scanning confocal microscopy was used to observe and quantify in situ isothermal grain growth. The results demonstrated significant variations in grain growth kinetics and final grain size depending on C content and temperature. Above 0.25 wt.-% C, grain growth increased markedly, potentially due to increased GB segregation of C. To rationalize the experimental observations, a multiscale modeling workflow combining atomistic DFT calculations with mean field simulations of grain growth was used. The energy profiles of solute C and impurities S and P were determined for two different GB types ( Σ 5 and Σ 13 ). The segregation analysis revealed that C competes with P and S for grain boundary sites. Mean field simulations of GB enrichment and GB migration using DFT data provide an explanation for the increase in grain boundary mobility in alloys with sufficiently high C content. For lower C contents, the strong enrichment of S causes solute drag pressure, reducing the effective GB mobility. At higher C contents, C replaces S at the GB and thus significantly decreases the solute drag pressure. As a result, austenite grain growth accelerates with higher carbon contents.
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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) | 0.000 | 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".