Supported nanostructured electroactive materials are known to boost the efficiency of electrocatalytic processes. Although they can be fabricated by multiple methods, electrodeposition offers several advantages, since the nanostructures are grown on the final support. However, the electrodeposition of nanostructures in a reproducible way requires a full understanding of the electrochemical nucleation and growth mechanisms at the nanoscale. Recently, we have developed an approach based on using carbon coated TEM grids as electrodes. This way, by combining atomic-scale TEM characterization with electron tomography and electrochemical measurements, we have found evidence that has led us to suggest an electrochemical aggregative growth mechanism [1]. It includes nanocluster surface diffusion, aggregation and coalescence as important elementary steps of the electrochemical growth process [2,3].

Due to the high level of complexity of the problem and the small timescales and lengthscales which need to be considered, electrochemical and surface characterization techniques feature inherent limitations. Therefore, a complementary approach based on numerical simulations is being evaluated. We have introduced 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 different factors: not only the overpotential, but the transport of active species and electrochemical kinetics are also evaluated, together with the surface diffusion and aggregation of adatoms and small nanoclusters [4].

The combined analysis of experimental and simulated data reveals that the relative surface mobility of nanoclusters compared to this of the adatoms plays a crucial role in the early growth stages. The number of clusters, their size and size dispersion are influenced more significantly by nanocluster mobility than by the applied overpotential itself. As a result, 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) should consider, not only an induction time that precedes cluster formation, but also the balance between cluster formation and aggregation. 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.

References

[1] Ustarroz, J.; Hammons, J. A.; Altantzis, T.; Hubin, A.; Bals, S.; Terryn, H. “A Generalized Electrochemical Aggregative Growth Mechanism.” Journal of the American Chemical Society 2013, 135, 11550–11561.

[2] Ustarroz, J.; Ke, X.; Hubin, A.; Bals, S.; Terryn, H. “New Insights into the Early Stages of Nanoparticle Electrodeposition”. The Journal of Physical Chemistry C 2012, 116, 2322–2329.

[3] Ustarroz, J.; Altantzis, T.; Hammons, J. A.; Hubin, A.; Bals, S.; Terryn, H. “The Role of Nanocluster Aggregation, Coalescence, and Recrystallization in the Electrochemical Deposition of Platinum Nanostructures”. Chemistry of Materials 2014, 26, 2396–2406.

[4] Haile Mamme, M.; Köhn, C.; Deconinck, J.; Ustarroz, J. “Numerical insights into the early stages of nanoscale electrodeposition: nanocluster surface diffusion and aggregative growth”, Manuscript under revision, 2017.