ABSTRACT
Data analytics has become an integral part of materials science. This book provides the practical tools and fundamentals needed for researchers in materials science to understand how to analyze large datasets using statistical methods, especially inverse methods applied to microstructure characterization. It contains valuable guidance on essential topics such as denoising and data modeling. Additionally, the analysis and applications section addresses compressed sensing methods, stochastic models, extreme estimation, and approaches to pattern detection.
TABLE OF CONTENTS
part I|12 pages
Introduction
part II|68 pages
Emerging Data Science in Microstructure Characterization
part III|62 pages
Inverse Methods for Analysis of Data
chapter Chapter 7|16 pages
Statistical Reconstruction and Heterogeneity Characterization in 3-D Biological Macromolecular Complexes
part IV|58 pages
Structure Formation in Materials
part V|118 pages
Microstructure
chapter Chapter 14|18 pages
Computer Vision for Microstructural Image Representation: Methods and Applications
part VI|38 pages
Anomalies
part VII|82 pages
Sparse Methods