Abstract
This chapter provides a discussion of how informatics tools can address one of the fundamental historical developments in crystal chemistry, that of structure maps. Such maps serve as a means to explore how specific parameters associated with crystal and electronic structure can serve as a way to rationalize groupings, or classifications, relating structure and chemistry. Historically, structure maps have evolved through a variety of heuristic approaches that define a priori how parameters may be important, and then classifications are discovered as one populates these maps with data. The resulting clustering of data serves as a heuristic tool to rationalize new discoveries and new structure-bonding relationships.
| 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 | 365-383 |
| Number of pages | 19 |
| ISBN (Print) | 9780123943996 |
| DOIs | |
| State | Published - 2013 |
Keywords
- Crystal chemistry
- Crystallography
- Data mining
- Structure maps
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