The development of new and superior materials is beneficial within industrial settings, as well as a topic of academic interest. By using computational modeling techniques, the probable application and performance of these materials can be easily evaluated.
Computational Approaches to Materials Design: Theoretical and Practical Aspects brings together empirical research, theoretical concepts, and the various approaches in the design and discovery of new materials. Highlighting optimization tools and soft computing methods, this publication is a comprehensive collection for researchers, both in academia and in industrial settings, and practitioners who are interested in the application of computational techniques in the field of materials engineering.
Table of Contents
Chapter 1: Computational Materials Design
Chapter 2: Successive Spin-Correlated Local Processes Underlying the Magnetism in Diluted Magnetic Semiconductors and Related Magnetic Materials
Chapter 3: Ab Initio-Based Stochastic Simulations of Kinetic Processes on Surfaces
Chapter 4: Computational Design of Microstructure
Chapter 5: Micromechanical and Finite Element Modeling for Composites
Chapter 6: Integrated Computational Materials Engineering for Determining the Set Points of Unit Operations for Production of a Steel Product Mix
Chapter 7: Informatics-Based Approaches for Accelerated Discovery of Functional Materials
Chapter 8: Applications of Feature Selection and Regression Techniques in Materials Design
Chapter 9: Imprecise Knowledge and Fuzzy Modeling in Materials Domain
Chapter 10: Artificial Neural Network and Its Application in Steel Industry
Chapter 11: Multi-Objective Evolutionary Algorithms
Chapter 12: Data-Driven Bi-Objective Genetic Algorithms EvoNN and BioGP and Their Applications in Metallurgical and Materials Domain
Chapter 13: Modeling of Steelmaking Processes