Vrije Universiteit Brussel (VUB), Research Group Electrochemical and Surface Engineering (SURF), Pleinlaan 2, 1050 Brussels, Belgium.
Nanoscale. 2018 Apr 19;10(15):7194-7209. doi: 10.1039/c7nr08529j.
Fundamental understanding of the early stages of electrodeposition at the nanoscale is key to address the challenges in a wide range of applications. Despite having been studied for decades, a comprehensive understanding of the whole process is still out of reach. In this work, we introduce a novel modelling approach that couples a finite element method (FEM) with a random walk algorithm, to study the early stages of nanocluster formation, aggregation and growth, during electrochemical deposition. This approach takes into account not only electrochemical kinetics and transport of active species, but also the surface diffusion and aggregation of adatoms and small nanoclusters. The simulation results reveal that the relative surface mobility of the nanoclusters compared to that of the adatoms plays a crucial role in the early growth stages. The number of clusters, their size and their size dispersion are influenced more significantly by nanocluster mobility than by the applied overpotential itself. Increasing the overpotential results in shorter induction times and leads to aggregation prevalence at shorter times. A higher mobility results in longer induction times, a delayed transition from nucleation to aggregation prevalence, and as a consequence, a larger surface coverage of smaller clusters with a smaller size dispersion. As a consequence, it is shown that a classical first-order nucleation kinetics equation cannot describe the evolution of the number of clusters with time, N(t), in potentiostatic electrodeposition. Instead, a more accurate representation of N(t) is provided. We show that an evaluation of N(t), which neglects the effect of nanocluster mobility and aggregation, can induce errors of several orders of magnitude in the determination of nucleation rate constants. These findings are extremely important towards evaluating the elementary electrodeposition processes, considering not only adatoms, but also nanoclusters as building blocks.
纳米尺度上电沉积初期的基本理解是解决广泛应用中挑战的关键。尽管已经研究了几十年，但对整个过程的全面理解仍然难以实现。在这项工作中，我们引入了一种新的建模方法，该方法将有限元方法 (FEM) 与随机漫步算法相结合，以研究电化学沉积过程中纳米团簇形成、聚集和生长的早期阶段。该方法不仅考虑了电化学动力学和活性物质的传输，还考虑了吸附原子和小纳米团簇的表面扩散和聚集。模拟结果表明，与吸附原子相比，纳米团簇的相对表面迁移率在早期生长阶段起着至关重要的作用。团簇的数量、大小及其大小分散度受纳米团簇迁移率的影响比受外加过电位本身的影响更大。增加过电位会导致较短的诱导时间，并导致较短时间内的聚集倾向。较高的迁移率会导致较长的诱导时间、从成核到聚集倾向的转变延迟，以及更小的尺寸分散度和更大的较小团簇的表面覆盖率。因此，结果表明，经典的一级成核动力学方程不能描述恒电位电沉积中随时间变化的团簇数量 N(t)的演变。相反，提供了更准确的 N(t)表示。我们表明，忽略纳米团簇迁移率和聚集效应的 N(t)评估可能会导致在确定成核速率常数时产生几个数量级的误差。这些发现对于评估基本的电沉积过程非常重要，不仅要考虑吸附原子，还要考虑纳米团簇作为构建块。
