Effect of Submicron‐Scale MnS Inclusions on Hydrogen Trapping and HIC Susceptibility of X70 Pipeline Steels
Bibliographic record
Abstract
In this work, the non‐metallic inclusions contained in a trial X70 pipeline steels are characterized by optical microscopy, scanning electron microscopy, energy‐dispersive X‐ray spectrum, and transmission electron microscopy. Statistical analysis is conducted to summarize the size and shape of the inclusions. The hydrogen trapping and the resulting hydrogen‐induced cracking (HIC) susceptibility of the steels are tested. Density functional theory is used to calculate the binding energy of hydrogen at MnS inclusions, and the impact of MnS inclusions on hydrogen trapping and the HIC susceptibility is evaluated. It is found that the majority of submicron scale inclusions are MnS, which serve as irreversible hydrogen traps. The content of the trapped hydrogen can be effectively decreased by controlling the size of MnS inclusions below submicron scale and distributing the inclusions uniformly in the steel. As a result, the susceptibility of the steel to HIC is reduced.
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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 | 0.000 |
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".