This perspective provides an experimentalist’s view on materials discovery in multinary materials systems—from nanoparticles over thin films to bulk—based on combinatorial thin-film synthesis and high-throughput characterization in connection with high-throughput calculations and materials informatics. Complete multinary materials systems as well as composition gradients which cover all materials compositions necessary for verification/falsification of hypotheses and predictions are efficiently fabricated by combinatorial synthesis of thin-film materials libraries. Automated high-quality high-throughput characterization methods enable comprehensive determination of compositional, structural and (multi)functional properties of the materials contained in the libraries. The created multidimensional datasets enable data-driven materials discoveries and support efficient optimization of newly identified materials, using combinatorial processing. Furthermore, these datasets are the basis for multifunctional existence diagrams, comprising correlations between composition, processing, structure and properties, which can be used for the design of future materials.

这种观点提供了实验者对多元材料系统中的材料发现（从薄膜上的纳米颗粒到块状材料）的观点，基于组合薄膜合成和高通量表征以及高通量计算和材料信息学。通过薄膜材料库的组合综合，可以有效地制造出完整的多元材料系统以及涵盖验证/伪造假设和预测所必需的所有材料成分的成分梯度。自动化的高质量高通量表征方法可以全面确定文库中所含材料的组成，结构和（多功能）性能。创建的多维数据集可通过组合处理实现数据驱动的材料发现，并支持对新识别的材料进行有效的优化。此外，这些数据集是多功能存在图的基础，包括组成，加工，结构和特性之间的相关性，可用于未来材料的设计。