Advanced high-throughput synthetic methods and parallel characterization tools for multinary materials

Hannah-Noa Barad
Max Planck Institute for Intelligent Systems, Heisenbergstr. 3, 70569 Stuttgart, Germany

EXTENDED ABSTRACT: In recent years, materials science has focused on finding new materials or improving existing materials for various applications, as well as refining device structures to advance applications from a device point of view. The search for new materials based on a large number of atoms (three or more) has raised much interest mainly due to functional materials of this kind that have shown outstanding properties, such as high-temperature superconductors, like YBa2Cu3O6+x (YBCO). To develop the research and design experiments, a considerable amount of prior knowledge is needed, since these functional materials cannot be stumbled upon by sheer luck. The design and learning about properties of known materials and the development of the new functional materials is time consuming, since it is based on trial and-error, and also uses resources that are not always available to the researcher. In addition, finding the new materials is complicated, as the new material characteristics depend on their compositions as well as the parameters used in the synthesis process, and the relationship between these components is not always straightforward. In order to accelerate the process of finding new advanced materials and device configurations one must utilize a combinatorial synthesis approach with high-throughput analysis techniques for the new materials and device structures. This method is referred to as combinatorial materials science. Combinatorial materials science (CMS) is a highly promising method for fast discovery of new functional materials, as shape-memory alloys and photoabsorbers. CMS has been used to form thin films with composition and thickness gradients, consequently, synthesizing, on a single substrate, known as a library, a range of samples with systematically varying properties, which is the first step in finding new materials and device structures. Apart from the composition or thickness, film morphology and nanostructuring can be especially important for an assortment of applications ranging from catalysis and photovoltaics to magnetic materials, as morphology governs the chemical reactivity, determines the surface area, and is important for charge mobility and recombination processes. However, heretofore CMS research did not encompass film morphology as a study parameter. Furthermore, measuring and analyzing the properties of combinatorial material libraries (CMLs) produced by CMS is not straightforward. Typically, the measurements entail serial methods that measure samples point by-point on pre-determined positions on the CMLs. While these measurements are often termed ‘high-throughput’ they are only so in the sense of generating over time large amounts of data. Especially, in the case of electrochemical measurements, the analysis can take a very long time, even days, to complete for one CML. Here we describe how we vary nano-scale morphology and material composition at the same time using an adapted shadow growth method based on glancing angle deposition (GLAD), which eliminates the commonly used wet chemical steps for nanostructure synthesis. In a one-step wellcontrolled growth we quickly obtain a large number of nano-columnar structures, including nanorods, nanohelices, and nano-zigzags, with varying material compositions. Adapting GLAD and introducing it into CMS, with accompanying high throughput characterization, constitutes an integrated approach for discovering new materials and structures for a multitude of applications in many scientific fields. We use this method to fabricate a multi-component nanocomposite electrolyzer and study its compositional and structural variations. The system is a multinary elemental metal-based library, where each material has an impact on the resulting nanostructure as well and the chemical composition and state. After investigating the physical and chemical properties of the library, it is then examined as an electrocatalyst for oxygen evolution reaction (OER). The OER activity shows a dependence on the nanostructuring of the library as well as on the chemical and compositional variation. By using CMS and high-throughput analysis, we are able to gain insights that the standard experimental techniques would not be able to achieve, thus indicating the importance and impact CMS has in the field of electrolyzers for the future. We further show a real high-throughput parallel method for determination of electrochemical properties. We do this using an array of ionsensing field effect transistors (ISFETs) that was specifically designed for high-throughput measurements. ISFET sensors are used to detect changes in concentrations of specific ions in a solution, and as such can follow changes in electrochemical reactions. For this work we chose to examine CMLs of electrolyzers for OER, which may form OH- or H+ intermediates during the reaction. In our setup, the sensor array is placed in solution directly above the studied CML, and we examine the as a result of the OER. The ISFET array allows us to quickly screen for material combinations of interest for OER, and generate large amounts of data in a short period of time, enabling parallel high-throughput CML characterization. We will share our most recent results in the generation of high-throughput CMLs [1] and analyzing these with similarly high-throughput parallel electrochemical measurements.

REFERENCES
[1] Hannah-Noa Barad, Mariana Alarcón-Correa, Gerardo Salinas, Eran Oren, Florian Peter, Alexander Kuhn and Peer Fischer; Combinatorial growth of multinary nanostructured thin functional films, in press, Materials Today, 2021.