Informatics for Materials Science and Engineering

1st Edition

Data-driven Discovery for Accelerated Experimentation and Application

Print ISBN: 9780128101216
eBook ISBN: 9780123946140
Imprint: Butterworth-Heinemann
Published Date: 15th July 2013
Page Count: 542
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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.

Key Features

  • Identifies and analyzes interdisciplinary strategies (including combinatorial and high throughput approaches) that accelerate materials development cycle times and reduces associated costs

  • Mathematical and computational analysis aids formulation of new structure-property correlations among large, heterogeneous, and distributed data sets
  • Practical examples, computational tools, and software analysis benefits rapid identification of critical data and analysis of theoretical needs for future problems


Computational materials scientists, combinatorial and high-throughput experimentalists and affiliated applications specialists.

Table of Contents

Preface: A Reading Guide


Chapter 1. Materials Informatics: An Introduction

1 The What and Why of Informatics

2 Learning from Systems Biology: An “Omics” Approach to Materials Design

3 Where Do We Get the Information?

4 Data Mining: Data-Driven Materials Research


Chapter 2. Data Mining in Materials Science and Engineering

1 Introduction

2 Analysis Needs of Science Applications

3 The Scientific Data-Mining Process

4 Image Analysis

5 Dimension Reduction

6 Building Predictive and Descriptive Models

7 Further Reading



Chapter 3. Novel Approaches to Statistical Learning in Materials Science

1 Introduction

2 The Supervised Binary Classification Learning Problem

3 Incorporating Side Information

4 Conformal Prediction

5 Optimal Learning

6 Optimal Uncertainty Quantification

7 Clustering Including Statistical Physics Approaches

8 Materials Science Example: The Search for New Piezoelectrics

9 Conclusion

10 Further Reading



Chapter 4. Cluster Analysis: Finding Groups in Data

1 Introduction

2 Unsupervised Learning

3 Different Clustering Algorithms and their Implementations in R

4 Validations of Clustering Results

5 Rank Aggregation of Clustering Results

6 Further Reading



Chapter 5. Evolutionary Data-Driven Modeling

1 Preamble

2 The Concept of Pareto Tradeoff

3 Evolutionary Neural Net and Pareto Tradeoff

4 Selecting the Appropriate Model in EvoNN

5 Conventional Genetic Programming

6 Bi-Objective Genetic Programming

7 Analyzing the Variable Response in EvoNN and BioGP

8 An Application in


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"The first half of the volume sets out foundational aspects of data science, and the second half surveys applications in materials science using a case-study approach. The topics include novel approaches to statistical learning in materials science, data dimensionality reduction in materials science,…. high-performance computing for accelerated zeolitic materials modeling, and using multivariate analysis to answer questions concerning the conservation of artworks and cultural heritage materials."--Reference & Research Book News, December 2013