Informatics for Materials Science and Engineering: Data-Driven Discovery for Accelerated Experimentation and Application (Hardcover)

Preface: A Reading Guide xiii Acknowledgment xv 1. Materials Informatics: An Introduction 1 2. Data Mining in Materials Science and Engineering 17 3. Novel Approaches to Statistical Learning in Materials Science 37 4. Cluster Analysis: Finding Groups in Data 53 5. Evolutionary Data-Driven Modeling 71 6. Data Dimensionality Reduction in Materials Science 97 7. Visualization in Materials Research: Rendering Strategies of Large Data Sets 121 8. Ontologies and Databases < Knowledge Engineering for Materials Informatics 147 9. Experimental Design for Combinatorial Experiments 189 10. Materials Selection for Engineering Design 219 11. Thermodynamic Databases and Phase Diagrams 245 12. Towards Rational Design of Sensing Materials from Combinatorial Experiments 271 13. High-Performance Computing for Accelerated Zeolitic Materials Modeling 315 14. Evolutionary Algorithms Applied to Electronic-Structure Informatics: Accelerated Materials Design Using Data Discovery vs. Data Searching 349 15. Informatics for Crystallography: Designing Structure Maps 365 16. From Drug Discovery QSAR to Predictive Materials QSPR: The Evolution of Descriptors, Methods, and Models 385 17. Organic Photovoltaics 423 18. Microstructure Informatics 443 19. Artworks and Cultural Heritage Materials: Using Multivariate Analysis to Answer Conservation Questions 467 20. Data Intensive Imaging and Microscopy: A Multidimensional Data Challenge 495 References 510 Index 513