Publication date: 10th April 2024
Ionic defects are essential building blocks for properties of complex oxides, including mixed ionic and electronic conductivity, surface kinetics and reactivity, lattice expansion and dynamics, which are important for applications ranging from energy (e.g., fuel cells and electrocatalysts) to information (e.g., memristors, neuromorphic computing devices). In this talk, I am going to cover two fronts of harnessing ionic defects for tailed oxide thin film properties. Firstly, to accurately predict electrochemical driving force needed for manipulating ionic defects for designed properties, constructing phase diagrams that correlates physical properties (conductivity, (chemical) diffusivity, lattice constant, etc.) and ionic defect concentration is essential. However, such tasks often require a large number of samples and can be susceptible to artefacts introduced by sample-to-sample variations. To tackle this challenge, we have developed a new electrochemical device that can introduce spatially-graded ionic defect concentrations in one single oxide thin film sample. Combined with materials characterization tools with high spatial resolution, we achieved high-throughput construction of phase diagrams controlled by ionic defect concentration [1,2]. Secondly, we established a comprehensive theoretical framework to understand the pivotal role of ionic defects (e.g., oxygen vacancies) in determining the activity of oxide electrocatalysts for both high-temperature [3] (>500°C, solid/gas interfaces) and low-temperature [4] (<100°C, solid/liquid interfaces) oxygen evolution reactions (OER). We found that, in both scenarios, alterations in ionic defect concentrations contribute significantly to what we refer to as “chemical overpotential”, which represents a substantial portion of the total overpotential. Overall, our work provides a holistic understanding of both “static” and “dynamic” effect of ionic defects in determining the properties and functionality of oxide thin films.
[1] H. Chen, Q. Lu* et al., Nano Letters, 22 (2022), 8983-8990
[2] Y. Lu, Q. Lu* et al., ACS Nano, 17 (2023), 14005−14013
[3] K. Yang, Q. Lu* et al., JACS 145 (2023), 25806–25814
[4] Y. Hu, Q. Lu* et al., in prep.