通过多面纳米粒子的均方场模型探测吸附剂诱导的 Rh50Pd50 纳米粒子重构的纳米级驱动力

IF 4.2 3区 化学 Q2 CHEMISTRY, PHYSICAL
Shuqiao Wang , Alyssa J. R. Hensley
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引用次数: 0

摘要

与单金属催化剂相比,双金属催化剂经常表现出协同性能,但在暴露于反应条件下时,会发生由吸附剂引起的表面离析和重构。尽管实验和计算方法对此类现象进行了广泛研究,但对吸附剂-表面和吸附剂-吸附剂相互作用对此类重构的影响仍缺乏深入了解。此外,目前捕捉这种重构的计算方法需要昂贵而耗时的多尺度模拟。在这里,我们通过结合密度泛函理论(DFT)、库比谐波插值和平衡极限下的微动力学建模,开发出一种快速准确的平均场方法来模拟多面纳米粒子,从而解决了吸附剂诱导的双金属纳米粒子重构建模所面临的这些挑战。我们通过对循环氧化和还原条件下 Rh50Pd50 纳米粒子重构的案例研究,证明了我们的方法的强大功能。利用 DFT,我们绘制了与 O* 吸附和表面形成能相关的覆盖面、切面和表面成分图,从而建立了均场模型。然后对一系列温度和压力条件下的多面 Rh50Pd50 纳米粒子进行建模。由此得出的纳米粒子上的 O* 覆盖率和表面层组成表明,高吸引力的 O*-Rh 相互作用是重构的主要原因,但也受到排斥性 O*-O* 相互作用的影响,因此没有这种 O*-O* 相互作用就无法再现已知的实验趋势。总之,我们的多层面双金属纳米粒子建模方法采用简洁的均场模型,能更快但仍然准确地预测表面重构行为。这样就能确定导致双金属纳米粒子重构的反应条件和纳米尺度相互作用,并使反应条件诱导的可调双金属纳米粒子工程成为可能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Probing the nanoscale driving forces for adsorbate-induced Rh50Pd50 nanoparticle reconstruction via mean-field models of multi-faceted nanoparticles†

Probing the nanoscale driving forces for adsorbate-induced Rh50Pd50 nanoparticle reconstruction via mean-field models of multi-faceted nanoparticles†

Probing the nanoscale driving forces for adsorbate-induced Rh50Pd50 nanoparticle reconstruction via mean-field models of multi-faceted nanoparticles†

Bimetallic catalysts frequently exhibit synergistic performance as compared to their monometallic constituents but will undergo adsorbate-induced surface segregation and reconstruction upon exposure to reaction conditions. Although such phenomena have been extensively studied by both experimental and computational approaches, there is still a lack of insight into the impact of adsorbate–surface and adsorbate–adsorbate interactions on such reconstruction. Furthermore, current computational approaches for capturing such reconstruction require expensive and time-consuming multi-scale simulations. Here, we address these challenges to modeling adsorbate-induced bimetallic nanoparticle reconstruction by developing a fast and accurate mean-field approach to modeling multi-faceted nanoparticles through a combination of density functional theory (DFT), kubic harmonics interpolation, and microkinetic modeling taken at the equilibrium limit. The power of our approach is demonstrated via a case study of Rh50Pd50 nanoparticle reconstruction under cyclical oxidizing and reducing conditions. Using DFT, we mapped the coverage, facet, and surface composition dependent O* adsorption and surface formation energies to develop mean-field models. Multi-faceted Rh50Pd50 nanoparticles under a range of temperature and pressure conditions were then modeled. The resulting O* coverage and surface layer compositions over the nanoparticles showed that highly attractive O*–Rh interactions are predominantly responsible for reconstruction but are modified by repulsive O*–O* interactions such that the absence of such O*–O* interactions fail to reproduce known experimental trends. Overall, our multi-faceted bimetallic nanoparticle modeling approach supplies faster, but still accurate predictions of surface reconstruction behaviors with a concise mean-field model. This allows for the identification of the reaction conditions and nanoscale interactions that lead to bimetallic nanoparticle reconstruction, as well as enabling the potential for tunable bimetallic nanoparticle engineering induced by reaction conditions.

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来源期刊
Catalysis Science & Technology
Catalysis Science & Technology CHEMISTRY, PHYSICAL-
CiteScore
8.70
自引率
6.00%
发文量
587
审稿时长
1.5 months
期刊介绍: A multidisciplinary journal focusing on cutting edge research across all fundamental science and technological aspects of catalysis. Editor-in-chief: Bert Weckhuysen Impact factor: 5.0 Time to first decision (peer reviewed only): 31 days
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