Synergistic effects of temperature and strain rate on tensile properties of simulated Ni-6Cu alloy with Σ3 non-Arrhenius grain boundary
Bibliographic record
Abstract
Comprehending the mechanical response of materials on an atomic level is pivotal in the optimisation of advanced materials with superior mechanical properties. This research article utilises the atomistic-scale based molecular dynamics simulations to report the uniaxial tensile behaviour of bicrystalline Ni-6Cu (Nickel – 94% and Copper – 6%) alloy incorporated with pre-existing faceted Σ3 [111] 60° {11 8 5} grain boundaries. The primary aim of this investigation is to comprehend the performance of bicrystalline Ni-6Cu alloy under varying thermodynamic conditions and to assess the influence of pre-existing faceted grain boundaries on its tensile behaviour. This work encompasses a range of strain rates (108 to 1010 1/s) and temperatures (spanning from 100 to 900 K) for the uniaxial tensile deformation simulations. The outcomes unveil that the Young’s modulus of Ni-6Cu alloy (with pre-existing faceted grain boundaries embedded in its domain) was inversely proportional to temperature and constant with respect to strain rate. For the same configuration, yield stress was inversely and directly proportional to temperature and strain rate, respectively. Interestingly, incipient plasticity in the tensile stress–strain response was observed at lower temperature and lower strain rate. From the microstructural point of view, at lower temperatures, the incoherent twin boundary served as a source for the nucleation of stacking faults; however, as the temperature increased, both the incoherent twin boundary and the tips of coherent twin boundary function as the source for stacking faults formation. Our simulations also verified the GB’s anti-thermal (or non-Arrhenius) migration behaviour even under tensile load.
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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 | 0.001 |
| 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".