Communication: a new paradigm for structure prediction in multicomponent systems.
Communication: a new paradigm for structure prediction in multicomponent systems.
复制标题
通信：多组分系统结构预测的新范例。
作者：
D. Schebarchov;D. Wales
我们分析了多组分体系全局优化的组合方面，这涉及到通过排列对应于不同物种的粒子来寻找最优的化学排序。假定整体组成是固定的，每次排列后几何形状都会松弛，以缓解局部应变。从用来解决图划分问题的想法出发，我们设计了一种确定性搜索方案，它的性能优于传统的和自我引导的盆地跳跃全局优化(以数量级为单位)。搜索是由交换粒子i和j(ΔEij)或改变粒子i的身份(ΔEi)所获得的能量来指导的。这些量是从潜在的(任意)能量函数导出的，因此不构成外部偏置，并且对于位置可分离的力场，每个ΔEi可以简单而有效地近似。在我们的自导式盆地跳跃变体中，当随机选择进行交换时，粒子按近似的ΔEI加权，从而显著改善了具有适度粒度不匹配的分离多组分系统。
We analyse the combinatorial aspect of global optimisation for multicomponent systems, which involves searching for the optimal chemical ordering by permuting particles corresponding to different species. The overall composition is presumed fixed, and the geometry is relaxed after each permutation in order to relieve local strain. From ideas used to solve graph partitioning problems we devise a deterministic search scheme that outperforms (by orders of magnitude) conventional and self-guided basin-hopping global optimisation. The search is guided by the energy gain from either swapping particles i and j (ΔEij) or changing the identity of particles i (ΔEi). These quantities are derived from the underlying (arbitrary) energy function, hence not constituting external bias, and for site-separable force fields each ΔEi can be approximated simply and efficiently. In our self-guided variant of basin-hopping, particles are weighted by an approximate ΔEi when randomly selected for an exchange, yielding a significant improvement for segregated multicomponent systems with modest particle size mismatch.