SearcharxivSearch

arXiv subjects

Yaohong Suo

Publications and source records attributed to Yaohong Suo.

2 recordsLinked to original sources

Primary damage and mechanical degradation of WTaCrV refractory high-entropy alloy: effects of solid-solution and chemical ordering

As advanced nuclear reactors demand novel irradiation-tolerant materials, this study investigates the radiation damage and mechanical degradation of the promising WTaCrV refractory high-entropy alloy (RHEA). To isolate complex nanoscale chemical effects, we propose an atomistic modeling strategy comparing Average-Atom (AA), random solid-solution (RSS), and local chemical order (LCO) configurations using newly developed interatomic potentials. Collision cascades simulations reveal that the number of Frenkel pairs follow NRSS > NLCO > NAA at the same radiation dose. While the RSS effect accelerates defect generation due to rugged energy landscapes, LCO enhances lattice cohesion to mitigate radiation damage. Despite more primary defects in the RSS and LCO configurations compared with the AA configurations, the RSS and LCO effects can suppress radiation-induced mechanical degradation. Irradiation severely degrade the homogenized AA model but exert a limited impact on the strength and flow stress of the RSS and LCO models. This exceptional resistance is driven by inherent lattice distortion resulting from interactions among different alloy elements, which outweighs point defect induced lattice disruptions. Moreover, the complex interactions between deformation twins and point defects cause confined plastic flow, elevating flow stress in the RSS and LCO models. The findings provide atomistic guidance for performance assessment of next-generation structural materials for extreme nuclear environments.

cond-mat.mtrl-sci

Size-Dependent Tensile Behavior of Nanocrystalline HfNbTaTiZr High-Entropy Alloy: Roles of Solid-Solution and Short-Range Order

This study investigates the size-dependent mechanical behavior of the HfNbTaTiZr refractory high-entropy alloy (RHEA) under uniaxial tension, with a focus on the effects of random solid-solution (RSS) and chemical short-range order (CSRO). A machine learning framework is developed to accelerate the parameterization of interatomic force fields (FFs), enabling molecular dynamics simulations of three nanocrystalline models: (i) a meta-atom (MA) mode representing the RHEA as a hypothetical sing-element system with averaged properties, (ii) a quinary RSS model with randomly distributed constituent atoms, and (iii) a Monte Carlo (MC) model with internal CSRO. The results reveal that RSS enhances strength, while CSRO reduces flow stress level but improves strain hardening and failure resistance. A transition from Hall-Petch (HP) strengthening to inverse Hall-Petch (IHP) softening is observed, with CSRO suppressing this transition. The underlying plastic mechanisms (i.e., dislocation slip, deformation twinning, phase transformation and grain boundary movements) are analyzed from both nanostructural and energetic perspectives. Theoretical models are established to describe the size-dependent yield strength and predict the critical grain size. Additionally, the contributions of different plastic mechanisms to the overall stress response are separately quantified. These findings provide new insights into the design and performance optimization of RHEAs through nanostructural engineering.

cond-mat.mtrl-sci