Materials Informatics & the Future of Advanced Material Development

Materials informatics is a burgeoning field that takes computational theory and ascribes it to material sciences. Its potential to transform the way scientists test, formulate, and produce new chemistries is limited only by the technology available to make use of the data they collect along the way. 

This guide will help you understand the key components of a materials informatics strategy, evaluate the technology that supports it, and identify new workflows to maximize your R&D data. After you’ve read it, you should feel confident in your next steps toward a more scalable, efficient materials development process.

What Is Materials Informatics?

Until recently, applying cutting-edge computer science and data techniques like machine learning and advanced statistical analysis made sense only in data-rich industries where data is relatively cheap, structured, and plentiful. They include sectors that benefit the most from advances in big data, like financial services, insurance, and information technology. It is only in the last few years that these methods have been adapted for the more complex data environments familiar to materials R&D practitioners.

Materials informatics takes the study of computational systems—how information is processed and transformed—and applies it to the development of industrial materials like polymers and ceramics. The goal of the field is to use best practices learned from data-rich industries, including the collection and management of large datasets, the infrastructure needed to process and learn from them, and advanced machine learning techniques to make faster, more focused progress in new materials discovery and the development of existing materials.

Organizations up and down the materials value chain—from raw material suppliers and university research labs to aerospace OEMs and multinational polymer manufacturers—use materials informatics to drive innovation and jumpstart development on next-generation products. The same technology that powers fields like robotics and autonomous vehicles is now being used by R&D teams to make leaps in materials development faster than ever.

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