Materials synthesis and processing involve many interconnected parameters, where even small variations can strongly affect material structure and properties. Yet the resulting data are often fragmented and inconsistently documented, making materials development difficult to reproduce and compare.

FAIRmat Area A connects data across the materials process chain, from synthesis and processing to structure and performance. By developing interoperable data models and workflows and combining experimental data with physical models and AI, Area A enables reproducible, predictive, and data-driven materials development.

Objectives

• Make synthesis and processing steps reproducible, traceable, and comparable.
• Connect synthesis and processing conditions with material structure, properties, and performance.
• Enable data to be shared and reused across different synthesis methods and application domains.
• Support predictive and AI-assisted approaches to materials synthesis and development.