Molecular Dynamics Simulations Of The Hydrogen Embrittlement Base Case: Atomic Hydrogen In A Defect Free Single Crystal
Bibliographic record
Abstract
While significant research has been conducted on the various mechanisms of hydrogen embrittlement, there remains a lack of quantitative understanding on the effect of atomic hydrogen concentration on mechanical properties. Previous experimental work suggests that an increased hydrogen concentration will degrade both the elastic modulus and yield stress. However, experimental samples often contain other atomistic defects that make it difficult to determine the role hydrogen alone plays on material behaviour. Further, experimental studies are often unable to directly quantify the effect of hydrogen concentration on modulus. Therefore, the purpose of this study was to use molecular dynamics simulations to quantify the effect of interstitial hydrogen on the mechanical properties of perfect single crystal alpha iron during loading. Results demonstrated the potential type used significantly affected predicted results. The EAM potential for Fe-H systems was selected as it accurately predicted both the hydrogen free modulus and diffusion coefficient of hydrogen in iron. Atomic hydrogen between 0.5 -5% was shown to linearly degrade the elastic modulus and stress to initiate dislocations at all temperatures considered. Increasing hydrogen concentration was shown to promote the formation of dislocations at a lower stress, resulting in a higher density of dislocation and shorter slip distances. Through demonstrating the effect of atomic hydrogen alone, without other atomistic defects, this study provides a foundation for better understanding the role of hydrogen on the degradation of mechanical properties during loading.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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".