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arXiv 2407.13643cond-mat.mtrl-scicond-mat.mes-hallphysics.app-phphysics.comp-ph
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纳米颗粒催化剂中的表面粗糙化

Surface roughening in nanoparticle catalysts

Cameron J. Owen, Nicholas Marcella, Christopher R. O'Connor, Taek-Seung Kim, Ryuichi Shimogawa, Clare Yijia Xie, Ralph G. Nuzzo, Anatoly I. Frenkel, Christian Reece, Boris Kozinsky

AI总结:

该研究结合原位光谱与机器学习力场分子动力学模拟,揭示金属纳米颗粒在反应环境中表面发生粗糙化重构,证明理想化小面模型不适用于真实催化系统,需采用真实表面结构以准确预测催化剂性能。

摘要:

负载型金属纳米颗粒(NP)催化剂对于化学品的可持续生产至关重要,但其设计和应用受到识别和表征与高催化活性相关的结构和原子位点能力的限制。这些“活性位点”的识别在很大程度上依赖于从理想化表面的研究外推到负载型纳米颗粒系统,实验上使用单晶或负载型纳米颗粒,而这些在计算上总是用平板或规则多面体模型来模拟。然而,这些方法预测催化活性的能力充其量仍是定性的,因为金属纳米颗粒在反应环境中的结构仅从间接实验观察中推测,或者完全未知。在此,通过规避高精度模拟方法的这些局限性,我们结合原位光谱学和由机器学习力场驱动的分子动力学模拟,提供了金属纳米颗粒动态重构的直接原子级见解。我们发现,在反应环境中,纳米颗粒表面演化为原子序度差的状态,而纳米颗粒的核心可能保持类块体结构。这些见解证明,基于小金属纳米颗粒系统理想化小面化的长期概念模型不能代表真实系统在反应环境暴露下的情况。我们展示了所得结构可以通过结合先进光谱学和计算工具来阐明。这一发现表明,为了实现催化剂功能和稳定性的忠实定量预测,我们必须超越理想化小面的实验和理论模型,转而采用包含响应相关物理和化学条件的真实表面结构的系统。

英文摘要:

Supported metal nanoparticle (NP) catalysts are vital for the sustainable production of chemicals, but their design and implementation are limited by the ability to identify and characterize their structures and atomic sites that are correlated with high catalytic activity. Identification of these ''active sites'' has relied heavily on extrapolation to supported NP systems from investigation of idealized surfaces, experimentally using single crystals or supported NPs which are always modelled computationally using slab or regular polyhedra models. However, the ability of these methods to predict catalytic activity remains qualitative at best, as the structure of metal NPs in reactive environments has only been speculated from indirect experimental observations, or otherwise remains wholly unknown. Here, by circumventing these limitations for highly accurate simulation methods, we provide direct atomistic insight into the dynamic restructuring of metal NPs by combining in situ spectroscopy with molecular dynamics simulations powered by a machine learned force field. We find that in reactive environments, NP surfaces evolve to a state with poorly defined atomic order, while the core of the NP may remain bulk-like. These insights prove that long-standing conceptual models based on idealized faceting for small metal NP systems are not representative of real systems under exposure to reactive environments. We show that the resultant structure can be elucidated by combining advanced spectroscopy and computational tools. This discovery exemplifies that to enable faithful quantitative predictions of catalyst function and stability, we must move beyond idealized-facet experimental and theoretical models and instead employ systems which include realistic surface structures that respond to relevant physical and chemical conditions.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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