论文标题
加速高渗透合金的计算建模和设计
Accelerating computational modeling and design of high-entropy alloys
论文作者
论文摘要
凭借具有独特化学和机械性能的巨大设计空间，我们使用元启发式混合杜鹃搜索（CS）删除了{高凝胶合金}的计算设计的障碍，用于“在实时”构建超级细胞随机近似（scraps）具有针对性的原子位点，并且具有针对性的原子能位点，并具有对自调晶体晶体的成对概率。我们的Hybrid-CS模式通过超快全局解决方案克服了大型，离散的组合优化，这些解决方案在系统大小上线性扩展，并在类似地上进行缩小，例如一个4元素，128个原子模型[$ 10^{73+} $ space]以秒为单位 - 比当前策略减少了13,000多。通过消除模型生成作为瓶颈，可以执行目前不可能或不切实际的计算合金设计。我们展示了具有不同短距离顺序的真实合金的方法。作为问题敏捷，我们的Hybrid-CS模式在不同领域提供了许多应用。
With huge design spaces for unique chemical and mechanical properties, we remove a roadblock to computational design of {high-entropy alloys} using a metaheuristic hybrid Cuckoo Search (CS) for "on-the-fly" construction of Super-Cell Random APproximates (SCRAPs) having targeted atomic site and pair probabilities on arbitrary crystal lattices. Our hybrid-CS schema overcomes large, discrete combinatorial optimization by ultrafast global solutions that scale linearly in system size and strongly in parallel, e.g. a 4-element, 128-atom model [a $10^{73+}$ space] is found in seconds -- a reduction of 13,000+ over current strategies. With model-generation eliminated as a bottleneck, computational alloy design can be performed that is currently impossible or impractical. We showcase the method for real alloys with varying short-range order. Being problem-agnostic, our hybrid-CS schema offers numerous applications in diverse fields.
