Molecular dynamics study of the ordering of carbon in highly supersaturated<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:mi>α</mml:mi><mml:mtext>-Fe</mml:mtext></mml:mrow></mml:math>
Bibliographic record
Abstract
A recently developed Fe-C interatomic potential has been used to investigate carbon in highly supersaturated $\ensuremath{\alpha}$ iron with an emphasis on the possible ways in which carbon can arrange itself on the octahedral sites of the tetragonally distorted $\ensuremath{\alpha}$-iron lattice. Focusing particularly on the composition ${\text{Fe}}_{16}{\text{C}}_{2}$, the embedded atom method potential used gives the same ground-state structure of ${\text{Fe}}_{16}{\text{C}}_{2}$ as density-functional-theory calculations. Moreover, when computing C-C interactions between two carbon atoms at 0 K with energy minimization, the preferred separation distance corresponds exactly to the octahedral site positions expected in ${\text{Fe}}_{16}{\text{C}}_{2}$. It has been shown with molecular dynamics that the carbon atoms in ${\text{Fe}}_{16}{\text{C}}_{2}$ change how they order on octahedral sites during heating and during cooling. Finally, when investigating the interaction energy of ${\text{Fe}}_{1\ensuremath{-}x}{\text{C}}_{x}$ for different carbon compositions, it is found that there is a clear minimum at $x=0.11$ for the fully ordered structure, corresponding to ${\text{Fe}}_{16}{\text{C}}_{2}$ composition. The results of these calculations are discussed with particular reference to carbon ordering in ferrous martensite.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".