An Introduction to Materials Informatics and Catalysts Informatics

In this chapter, we delve into the fundamental concepts of materials informatics and catalysts informatics, shedding light on their origins and their relationship with the fields of materials and catalysts science. To begin, we explore the history of materials science and catalysts science, emphasizing the traditional approach of designing materials and catalysts based on researchers’ knowledge and a trial-and-error process. For a long time, the development of new materials and catalysts relied heavily on empirical observations, experimental iterations, and theoretical insights. This approach required significant time, resources, and expertise, often leading to slow progress and limited success in achieving desired material properties and catalyst performances. However, with the rapid advancements in data acquisition, storage, and analysis technologies, a new paradigm has emerged, known as materials informatics and catalysts informatics. These disciplines aim to leverage data science methodologies, such as statistical analysis, machine learning, and data visualization, to extract knowledge and insights from large datasets generated by experimental, theoretical, and computational studies. By employing materials informatics and catalysts informatics, researchers can overcome the limitations of the traditional approach. These emerging fields enable the systematic exploration and design of materials and catalysts by leveraging data-driven approaches. Rather than relying solely on researchers’ intuition and experience, materials informatics and catalysts informatics utilize data-driven models and algorithms to accelerate the discovery and design of materials and catalysts with desired properties and performances. The birth of materials informatics and catalysts informatics signifies a paradigm shift in materials and catalysts science. They allow researchers to harness the power of data to uncover hidden patterns, correlations, and structure-property relationships that were previously difficult to discern. This data-driven approach enables more efficient and targeted experimentation, reducing the time and resources required for materials and catalysts design. Throughout this chapter, we will delve deeper into the concepts of materials informatics and catalysts informatics, exploring their key principles, methodologies, and applications. We will examine how these disciplines have transformed the landscape of materials and catalysts research, paving the way for accelerated innovation, improved materials design, and enhanced catalyst performance.