Although tremendous applications for metal nanoparticles have been found in modern technologies, the understanding of their stability as related to morphology (size and shape) and chemical ordering (e.g., in bimetallics) remains limited. First-principles methods such as density functional theory (DFT) are capable of capturing accurate nanoalloy energetics; however, they are limited to very small nanoparticle sizes (<2 nm in diameter) due to their computational cost. Herein, we propose a bond-centric (BC) model able to capture cohesive energy trends over a range of monometallic and bimetallic nanoparticles and mixing behavior (excess energy) of nanoalloys, in great agreement with DFT calculations. We apply the BC model to screen the energetics of a recently reported 23 196-atom FePt nanoalloys (Yang et al. Nature 2017, 542, 75−79), offering insights into both segregation and bulk-chemical ordering behavior. Because the BC model utilizes tabulated data (diatomic bond energies and bulk cohesive energies) and structural information on nanoparticles (coordination numbers), it can be applied to calculate the energetics of any nanoparticle morphology and chemical composition, thus significantly accelerating nanoalloy design.

中文翻译：

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金属纳米颗粒稳定性预测的尺寸，形状和成分相关模型

尽管在现代技术中已经发现了金属纳米颗粒的巨大应用，但是对它们与形态（尺寸和形状）和化学有序性（例如，双金属化合物）的稳定性的了解仍然有限。诸如密度泛函理论（DFT）之类的第一性原理方法能够捕获准确的纳米合金能量。然而，由于它们的计算成本，它们被限制在非常小的纳米颗粒尺寸（直径<2 nm）中。在此，我们提出了一种以键为中心的模型（BC），该模型能够捕获一系列单金属和双金属纳米颗粒的内聚能趋势以及纳米合金的混合行为（过量能量），这与DFT计算非常吻合。我们应用BC模型来筛选最近报道的23 196个原子的FePt纳米合金的能量学（Yang等，自然 2017年，542，75-79），发行见解既隔离和散装化学定购行为。由于BC模型利用列表数据（原子键能和本体凝聚能）和纳米粒子的结构信息（配位数），因此可以用于计算任何纳米粒子形态和化学成分的能级，从而显着加速了纳米合金的设计。