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Creators/Authors contains: "Nelson, Jocienne N."

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  1. Functional properties of transition-metal oxides strongly depend on crystallographic defects; crystallographic lattice deviations can affect ionic diffusion and adsorbate binding energies. Scanning x-ray nanodiffraction enables imaging of local structural distortions across an extended spatial region of thin samples. Yet, localized lattice distortions remain challenging to detect and localize using nanodiffraction, due to their weak diffuse scattering. Here, we apply an unsupervised machine learning clustering algorithm to isolate the low-intensity diffuse scattering in as-grown and alkaline-treated thin epitaxially strained SrIrO3 films. We pinpoint the defect locations, find additional strain variation in the morphology of electrochemically cycled SrIrO3, and interpret the defect type by analyzing the diffraction profile through clustering. Our findings demonstrate the use of a machine learning clustering algorithm for identifying and characterizing hard-to-find crystallographic defects in thin films of electrocatalysts and highlight the potential to study electrochemical reactions at defect sites in operando experiments.

    Free, publicly-accessible full text available October 11, 2023
  2. Tomographic spectroscopy reveals how the properties of topological materials can be engineered at interfaces.
  3. null (Ed.)
  4. The use of renewable electricity to prepare materials and fuels from abundant molecules offers a tantalizing opportunity to address concerns over energy and materials sustainability. The oxygen evolution reaction (OER) is integral to nearly all material and fuel electrosyntheses. However, very little is known about the structural evolution of the OER electrocatalyst, especially the amorphous layer that forms from the crystalline structure. Here, we investigate the interfacial transformation of the SrIrO 3 OER electrocatalyst. The SrIrO 3 amorphization is initiated by the lattice oxygen redox, a step that allows Sr 2+ to diffuse and O 2− to reorganize the SrIrO 3 structure. This activation turns SrIrO 3 into a highly disordered Ir octahedral network with Ir square-planar motif. The final Sr y IrO x exhibits a greater degree of disorder than IrO x made from other processing methods. Our results demonstrate that the structural reorganization facilitated by coupled ionic diffusions is essential to the disordered structure of the SrIrO 3 electrocatalyst.