Halim Harry H, Morikawa Yoshitada
Department of Precision Engineering, Graduate School of Engineering, Osaka University, 2-1, Yamada-oka, Suita, Osaka565-0871, Japan.
Elements Strategy Initiative for Catalysts and Batteries (ESICB), Kyoto University, Goryo-Ohara, Nishikyo-ku, Kyoto615-8245, Japan.
ACS Phys Chem Au. 2022 Jun 15;2(5):430-447. doi: 10.1021/acsphyschemau.2c00017. eCollection 2022 Sep 28.
The Cu-Zn surface alloy has been extensively involved in the investigation of the true active site of Cu/ZnO/AlO, the industrial catalyst for methanol synthesis which remains under controversy. The challenge lies in capturing the interplay between the surface and reaction under operating conditions, which can be overcome given that the explicit dynamics of the system is known. To provide a better understanding of the dynamic of Cu-Zn surface at the atomic level, the structure and the formation process of the Cu-Zn surface alloy on Cu(997) were investigated by machine-learning molecular dynamics (MD). Gaussian process regression aided with on-the-fly learning was employed to build the force field used in the MD. The simulation reveals atomistic details of the alloying process, that is, the incorporation of deposited Zn adatoms to the Cu substrate. The surface alloying is found to start at upper and lower terraces near the step edge, which emphasize the role of steps and kinks in the alloying. The incorporation of Zn at the middle terrace was found at the later stage of the simulation. The rationalization of alloying behavior was performed based on statistics and barriers of various elementary events that occur during the simulation. It was observed that the alloying scheme at the upper terrace is dominated by the confinement of Zn step adatoms by other adatoms, highlighting the importance of step fluctuations in the alloying process. On the other hand, the alloying scheme at the lower terrace is dominated by direct exchange between the Zn step adatom and the Cu atom underneath. The alloying at the middle terrace is dominated by the wave deposition mechanism and deep confinement of Zn adatoms. The short propagation of alloyed Zn in the middle terrace was observed to proceed by means of indirect exchange instead of local exchange as proposed in the previous scanning tunneling microscopy (STM) observation. The comparison of migration rate and activation energies to the result of STM observation is also made. We have found that at a certain distance from the surface, the STM tip significantly affects the elementary events such as vacancy formation and direct exchange.
铜锌表面合金已广泛应用于对铜/氧化锌/氧化铝(甲醇合成工业催化剂,其真实活性位点仍存在争议)真实活性位点的研究。挑战在于捕捉操作条件下表面与反应之间的相互作用,鉴于系统的明确动力学已知,这一挑战是可以克服的。为了在原子层面更好地理解铜锌表面的动力学,通过机器学习分子动力学(MD)研究了铜(997)上铜锌表面合金的结构和形成过程。采用带实时学习的高斯过程回归来构建MD中使用的力场。模拟揭示了合金化过程的原子细节,即沉积的锌吸附原子融入铜基底的过程。发现表面合金化始于靠近台阶边缘的上下平台,这突出了台阶和扭结在合金化中的作用。在模拟后期发现锌在中间平台的融入。基于模拟过程中发生的各种基本事件的统计和势垒对合金化行为进行了合理化分析。观察到上平台的合金化方案主要由其他吸附原子对锌台阶吸附原子的限制主导,突出了台阶波动在合金化过程中的重要性。另一方面,下平台的合金化方案主要由锌台阶吸附原子与下方铜原子之间的直接交换主导。中间平台的合金化主要由波沉积机制和锌吸附原子的深度限制主导。观察到中间平台合金化锌的短程传播是通过间接交换而非先前扫描隧道显微镜(STM)观察中提出的局部交换进行的。还将迁移率和活化能的模拟结果与STM观察结果进行了比较。我们发现,在距表面一定距离处,STM针尖会显著影响诸如空位形成和直接交换等基本事件。