Role of Crystal Orientation, Temperature, and Strain Rate on the Mechanical Characterization of Nickel: An Atomistic-scale investigation
Bibliographic record
Abstract
In this article, the influence of crystallographic orientation on the mechanical properties of pristine nickel (Ni) during uniaxial tensile deformation was explored by utilizing molecular dynamics simulations. To study the influence of [0 01] and [11 8 5] crystal orientations on the mechanical properties and microstructural evolution of pristine Ni, simulations were performed at different temperatures ranging from 100 K to 900 K and at strain rates ranging from 10 7 to 10 10 s –1 . The results revealed that Ni with [11 8 5] orientation showed a higher elastic modulus than Ni with [0 0 1] orientation, whereas the yield strength of [0 0 1] orientation was higher than [11 8 5] orientation for a combination of temperatures and strain rates. Also, in comparison to [11 8 5] crystal orientation, the system with [0 0 1] orientation showed a high amount of dislocation density at the yield strain point for lower strain rates. At higher strain rates, the face-centered cubic to body-centered cubic transition was more prominent in the Ni system with [0 0 1] orientation, and it tends to decrease with the increase in temperature. Our present work may help materials scientists design materials with different crystal orientations that can perform according to the applied strain rates and temperatures. It is also proposed that tailoring of mechanical properties is achievable by exposing Ni with different crystal orientations to various environmental conditions (cryogenic, ambient, and elevated temperatures with different applied strain rates).
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 | 0.000 |
| 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 | 0.001 | 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".