| Increasing demand for novel electrochemical catalysts for kinetically difficult processes, such as CO2 reduction or water oxidation, has pushed catalytic material design toward the nano-regime. While nanomaterials containing earth abundant elements such as Mn, Fe, and Ni has shown promising catalytic activity, they are still limited by poor bulk electrical conductivity. Mimics of enzymatic clusters presents the most advantageous direction for novel earth abundant electrocatalysts, but the fabrication of said clusters for electrochemical catalysis is experimentally challenging. This dissertation aims to show through the use of the self-limiting and conformal nature of atomic layer deposition (ALD), one can develop a means of growing enzymatic cluster mimics from the substrate up in order to address their electrocatalytic activity.;This dissertation will demonstrate how ALD can be used to understand fundamental electron transfer (eT) phenomenon. By depositing significantly thick layers of TiO2 on SnO2 electrodes, eT transitioned from quantum mechanical tunneling to thickness independent eT. The thickness independent mechanism is facilitated by trap states in the band gap of the as-deposited TiO2 layer, the rate of eT through this mechanism decreases significantly upon annealing.;Additionally, unexplored ALD precursors will be used to grow alpha-Fe 2O33 and Cu2O at milder conditions compared to ubiquitous ALD processes. A previously overlooked iron bisamidinate precursor was used to confirm a minimum thickness needed for optimal photocatalysis using alpha-Fe2O3. Additionally, Cu(II) bis(dimethylamino-2-propoxide) was observed to grow amorphous Cu2O films using water as a co-reactant, illustrating the Cu(II) precursor can easily self-reduce without a reducing agent. The development of these new recipes opens up these materials to deposit in a wide range of "softer" organic containing substrates.;Finally, this dissertation will show for the first time, the development of a novel methodology for quantifying ALD nucleation events in self-assembled monolayers using an analytic model and in-situ measurements. By using the island growth model, this dissertation will illustrate how to achieve site-selective ALD using porphyrin nucleation platforms to induce defined MnO island growth. The techniques developed herein will lay the foundation for the growth and analysis of enzymatic clusters mimics using ALD. |
