Introduction to High-Throughput Materials Discovery

Traditional materials development is notoriously slow, often taking decades to bring a new material from the lab to the market. High-throughput materials discovery changes this by combining automated synthesis, rapid screening, and data science to accelerate innovation. In this introductory course, you will learn how to design, execute, and analyze high-throughput experiments that dramatically speed up the discovery of new materials. You will transition from slow, trial-and-error laboratory methods to a modern, systematic, and data-driven approach to materials research. What you'll learn: - Understand the fundamental terminology and concepts of high-throughput and combinatorial materials science. - Explore modern techniques for automated synthesis and rapid characterization of materials libraries. - Apply basic data-driven workflows and materials informatics to analyze large experimental datasets. - Integrate open-source materials databases and active learning concepts to guide experimental design. - Evaluate high-throughput screening strategies for real-world applications in energy, electronics, and sustainability. The course begins with foundational definitions and historical context before guiding you through combinatorial synthesis, rapid screening methodologies, and the integration of modern data science tools. You will read through practical case studies and conceptual exercises designed to build your confidence in modern materials research. This course is designed for beginners, students, and researchers in chemistry, physics, or engineering who want to modernize their approach to materials science, with no prior experience in high-throughput methods required. Start reading today and learn how to accelerate the future of materials innovation.