Deformation mechanisms and compressive response of NbTaTiZr alloy via machine learning potentials
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866910036639350784 |
|---|---|
| author | Liu, Hongyang Chen, Bo Chen, Rong Kang, Dongdong Dai, Jiayu |
| author_facet | Liu, Hongyang Chen, Bo Chen, Rong Kang, Dongdong Dai, Jiayu |
| contents | Refractory multi-principal element alloys (MPEAs) are key research focus for excellent high-temp properties and engineering potential. Deformation mechanisms/mechanical behaviors of quaternary NbTaTiZr MPEA under high strain rates/extreme temps remain unclear. We built a variable-composition ML potential for NbTaTiZr, combined with MD simulations to study effects of crystal orientation, strain rate, temp, composition on compressive mechanics. NbTaTiZr shows structural/mechanical anisotropy in compression [111] max yield strength, [110] min (prone to twinning), [100] via local disorder/dislocation slip (dominant 1/2<111> dislocations). At 10^10 s^-1, yield strength rises sharply, disordered structures increase; high strain rates suppress dislocations to promote disordering. Retains high strength at 2100 K. Higher Nb/Ta boosts yield strength, Ti/Zr reduce it. Reveals MPEA mechanical anisotropy and strain-rate-dependent disordering, guiding high-performance refractory alloy design. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_00726 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Deformation mechanisms and compressive response of NbTaTiZr alloy via machine learning potentials Liu, Hongyang Chen, Bo Chen, Rong Kang, Dongdong Dai, Jiayu Materials Science Computational Physics Refractory multi-principal element alloys (MPEAs) are key research focus for excellent high-temp properties and engineering potential. Deformation mechanisms/mechanical behaviors of quaternary NbTaTiZr MPEA under high strain rates/extreme temps remain unclear. We built a variable-composition ML potential for NbTaTiZr, combined with MD simulations to study effects of crystal orientation, strain rate, temp, composition on compressive mechanics. NbTaTiZr shows structural/mechanical anisotropy in compression [111] max yield strength, [110] min (prone to twinning), [100] via local disorder/dislocation slip (dominant 1/2<111> dislocations). At 10^10 s^-1, yield strength rises sharply, disordered structures increase; high strain rates suppress dislocations to promote disordering. Retains high strength at 2100 K. Higher Nb/Ta boosts yield strength, Ti/Zr reduce it. Reveals MPEA mechanical anisotropy and strain-rate-dependent disordering, guiding high-performance refractory alloy design. |
| title | Deformation mechanisms and compressive response of NbTaTiZr alloy via machine learning potentials |
| topic | Materials Science Computational Physics |
| url | https://arxiv.org/abs/2603.00726 |