Abstract
Studying structure-property relationships is an accepted paradigm in materials science, yet these relationships are often not linear and the challenge is to seek patterns among multiple length and time scales. There is rarely a single multiscale theory or experiment that can meaningfully and accurately capture such information. In this chapter we introduce the rationale as to why we need informatics by briefly summarizing the challenges of information complexity one has to deal with in material science, in order to systematically establish structure-property-processing relationships. Some of the concepts and topics to be covered in this book are introduced, including information networks, data mining, databases, and combinatorial experiments to mention a few. The value of "materials informatics" lies in its ability to permit one to survey complex, multiscale information in a high-throughput, statistically robust and yet physically meaningful manner.
| Original language | English |
|---|---|
| Title of host publication | Informatics for Materials Science and Engineering |
| Subtitle of host publication | Data-Driven Discovery for Accelerated Experimentation and Application |
| Publisher | Elsevier Inc. |
| Pages | 1-16 |
| Number of pages | 16 |
| ISBN (Print) | 9780123943996 |
| DOIs | |
| State | Published - 2013 |
Keywords
- Combinatorial experiments
- Data mining
- Databases
- Informatics
- Information networks
- Structure-property relationships
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