1st Edition
Statistical Methods for Materials Science The Data Science of Microstructure Characterization
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.
Chapter 1 Materials Science vs. Data Science
Jeff Simmons, Lawrence Drummy, Charles Bouman, Marc De Graef
Chapter 2 Emerging Digital Data Capabilities
Stephen Mick
Chapter 3 Cultural Differences
Mary Comer, Charles Bouman, Jeff Simmons
Chapter 4 Forward Modeling
Marc De Graef
Chapter 5 Inverse Problems and Sensing
Charles Bouman
Chapter 6 Model-Based Iterative Reconstruction for Electron Tomography
Singanallur Venkatakrishnan, Lawrence Drummy
Chapter 7 Statistical reconstruction and heterogeneity characterization in 3-D biological macromolecular complexes
Qiu Wang, Peter C. Doerschuk
Chapter 8 Object Tracking through Image Sequences
Song Wang, Hongkai Yu, Youjie Zhou, Jeff Simmons, Craig Przybyla
Chapter 9 Grain Boundary Characteristics
Hossein Beladi, Gregory S. Rohrer
Chapter 10 Interface Science and the Formation of Structure
Ming Tang, Jian Luo
Chapter 11 Hierarchical Assembled Structures from Nanoparticles
Dhriti Nepal, Sushil Kanel, Lawrence Drummy
Chapter 12 Estimating Orientation Statistics
Stephen R. Niezgoda
Chapter 13 Representation of Stochastic Microstructures
Stephen R. Niezgoda
Chapter 14 Computer Vision for Microstructure Representation
Brian DeCost, Elizabeth Holm
Chapter 15 Topological Analysis of Local Structure
Emanuel Lazar, David Srolovitz
Chapter 16 Markov Random Fields for Microstructure Simulation
Veera Sundararaghavan
Chapter 17 Distance Measures for Microstructures
Patrick Callahan
Chapter 18 Industrial Applications
David Furrer, David Brough, Ryan Noraas
Chapter 19 Anomaly Testing
James Theiler
Chapter 20 Anomalies in Microstructures
Stephen Bricker, Craig Przybyla, Jeff Simmons, Russel Hardie
Chapter 21 Denoising Methods with Applications to Microscopy
Rebecca Willett
Chapter 22 Compressed Sensing for Imaging Applications
Justin Romberg
Chapter 23 Dictionary Methods for Compressed Sensing
Saiprasad Ravishankar, Raj Rao Nadakuditi
Chapter 24 Sparse Sampling in Microscopy
Kurt Larson, Hyrum Anderson, Jason Wheeler
Biography
Jeffrey P. Simmons, Lawrence F. Drummy, Charles A. Bouman, Marc De Graef
