Informatics for Materials Science and Engineering by Rajan, Krishna;

Data-driven Discovery for Accelerated Experimentation and Application

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A termék adatai:

Kiadó Elsevier Science
Megjelenés dátuma 2018. október 30.

ISBN 9780128101216
Kötéstípus Puhakötés
Terjedelem542 oldal
Méret 228x152 mm
Súly 450 g
Nyelv angol

Kategóriák

Gépészmérnöki tudományok Üzemmérnöki tudományok

Hosszú leírás:

"

Materials informatics: a 'hot topic' area in materials science, aims to combine traditionally bio-led informatics with computational methodologies, supporting more efficient research by identifying strategies for time- and cost-effective analysis.

The discovery and maturation of new materials has been outpaced by the thicket of data created by new combinatorial and high throughput analytical techniques. The elaboration of this ""quantitative avalanche""-and the resulting complex, multi-factor analyses required to understand it-means that interest, investment, and research are revisiting informatics approaches as a solution.

This work, from Krishna Rajan, the leading expert of the informatics approach to materials, seeks to break down the barriers between data management, quality standards, data mining, exchange, and storage and analysis, as a means of accelerating scientific research in materials science.

This solutions-based reference synthesizes foundational physical, statistical, and mathematical content with emerging experimental and real-world applications, for interdisciplinary researchers and those new to the field.

"

Több

Tartalomjegyzék:

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