Discovery of new materials is a key challenge in materials science: e.g. new materials for sustainable production/storage/conversion of energy carriers are necessary to improve existing and to enable future energy systems. Efficient methods for discovery and optimization of new materials are necessary: Thin-film combinatorial materials science (1) is presented as an effective means to produce large datasets on new materials. This approach is useful for validation of theoretical predictions (e.g. from high-throughput computations), and production of large, consistent and complete experimental datasets which can be used for materials informatics. The approach comprises fabrication and processing of thin-film materials libraries by combinatorial sputter deposition processes and optional post-deposition treatments, followed by the high-throughput characterization of the different thin-film samples contained in these libraries, and finally the organization of the acquired multi-dimensional data in adequate databases as well their effective computational analysis and visualization. The importance of defining adequate screening parameters and according designs of materials libraries is addressed. High-throughput material characterization methods are automated, fast, and mostly non-destructive: examples are EDX and RBS for composition, XRD for crystal structure, high-throughput test stands for temperature-dependent resistance (phase transformation), magnetic, optical and mechanical properties as well as scanning droplet cells for (photo)electrochemical properties screening. Results for up to quinary systems are visualized in the form of composition-processing-structure-function diagrams, interlinking compositional data with structural and functional properties. The talk will cover and discuss examples of combinatorial discoveries and development of new materials in different materials classes and forms (films, nanoparticles) with a focus on compositionally complex materials (e.g. (2)). Furthermore, a new approach (3) to accelerate atomic-scale measurements for complex alloys is presented as well as applications of materials informatics to accelerate and improve the materials discovery process (4, 5).

(1) A. Ludwig (2019) Discovery of new materials using combinatorial synthesis and high-throughput characterization of thin-film materials libraries combined with computational methods, npj computational materials 5, 70

(2) T. Löffler, H. Meyer, A. Savan, P. Wilde, A. Garzón Manjón, Y. T. Chen, E. Ventosa, C. Scheu, A. Ludwig, W. Schuhmann (2018) Discovery of a multinary noble metal free oxygen reduction catalyst, Adv. Energy Mater. 8, 1802269

(3) Y. J. Li, A. Savan, A. Kostka, H. S. Stein, A. Ludwig (2018) Accelerated atomic-scale exploration of phase evolution in compositionally complex materials, Materials Horizons 5, 86 - 92

(4) P. M. Maffettone, L. Banko, P. Cui, Y. Lysogorskiy, M. Little, D. Olds, A. Ludwig, A. I. Cooper (2021) Crystallography companion agent for high-throughput materials discovery, Nature Computational Science 1, 290 – 297.

(5) L. Banko, O. A. Krysiak, J. K. Pedersen, B. Xiao, A. Savan, T. Löffler, S. Baha, J. Rossmeisl, W. Schuhmann, A. Ludwig (2022) Unravelling composition-activity-stability trends in high entropy alloy electrocatalysts by using a data-guided combinatorial synthesis strategy and computational modelling, Adv. Energy Mater., 2103312