Structural evolution and atomic dynamics in Ni–Nb metallic glasses: A molecular dynamics study
Bibliographic record
Abstract
The composition and temperature dependence of static and dynamic structures in NixNb1−x (x = 50–70 at. %) were systematically studied using molecular dynamics with a new-released semi-empirical embedded atom method potential by Mendelev. The calculated pair correlation functions and the structure factor match well with the experimental data, demonstrating the reliability of the potential within relatively wide composition and temperature ranges. The local atomic structures were then characterized by bond angle distributions and Voronoi tessellation methods, demonstrating that the icosahedral ⟨0,0,12,0⟩ is only a small fraction in the liquid state but increases significantly during cooling and becomes dominant at 300 K. The most abundant clusters are identified as ⟨0,0,12,0⟩ and distorted icosahedron ⟨0,2,8,2⟩. The large fraction of these two clusters hints that the relatively good glass forming ability is near the eutectic point. Unlike Cu–Zr alloys, both the self-diffusion coefficient and shear viscosity are insensitive to compositions upon cooling in Ni–Nb alloys. The breakdown of the Stokes-Einstein relation happens at around 1.6Tg (Tg: glass transition temperature). In the amorphous state, the solid and liquid-like atoms can be distinguished based on the Debye-Waller factor ⟨u2⟩. The insensitivity of the dynamic properties of Ni–Nb alloys to compositions may result from the relatively simple solidification process in the phase diagram, in which only one eutectic point exists in the studied composition range.
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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".