Hierarchical Materials Informatics

Hierarchical Materials Informatics
Author: Surya R. Kalidindi
Publisher: Elsevier
Total Pages: 230
Release: 2015-08-06
Genre: Technology & Engineering
ISBN: 012410455X

Custom design, manufacture, and deployment of new high performance materials for advanced technologies is critically dependent on the availability of invertible, high fidelity, structure-property-processing (SPP) linkages. Establishing these linkages presents a major challenge because of the need to cover unimaginably large dimensional spaces. Hierarchical Materials Informatics addresses objective, computationally efficient, mining of large ensembles of experimental and modeling datasets to extract this core materials knowledge. Furthermore, it aims to organize and present this high value knowledge in highly accessible forms to end users engaged in product design and design for manufacturing efforts. As such, this emerging field has a pivotal role in realizing the goals outlined in current strategic national initiatives such as the Materials Genome Initiative (MGI) and the Advanced Manufacturing Partnership (AMP). This book presents the foundational elements of this new discipline as it relates to the design, development, and deployment of hierarchical materials critical to advanced technologies. - Addresses a critical gap in new materials research and development by presenting a rigorous statistical framework for the quantification of microstructure - Contains several case studies illustrating the use of modern data analytic tools on microstructure datasets (both experimental and modeling)

Metallurgy and Design of Alloys with Hierarchical Microstructures

Metallurgy and Design of Alloys with Hierarchical Microstructures
Author: Krishnan K. Sankaran
Publisher: Elsevier
Total Pages: 508
Release: 2017-06-14
Genre: Technology & Engineering
ISBN: 0128120258

Metallurgy and Design of Alloys with Hierarchical Microstructures covers the fundamentals of processing-microstructure-property relationships and how multiple properties are balanced and optimized in materials with hierarchical microstructures widely used in critical applications. The discussion is based principally on metallic materials used in aircraft structures; however, because they have sufficiently diverse microstructures, the underlying principles can easily be extended to other materials systems. With the increasing microstructural complexity of structural materials, it is important for students, academic researchers and practicing engineers to possess the knowledge of how materials are optimized and how they will behave in service. The book integrates aspects of computational materials science, physical metallurgy, alloy design, process design, and structure-properties relationships, in a manner not done before. It fills a knowledge gap in the interrelationships of multiple microstructural and deformation mechanisms by applying the concepts and tools of designing microstructures for achieving combinations of engineering properties—such as strength, corrosion resistance, durability and damage tolerance in multi-component materials—used for critical structural applications. - Discusses the science behind the properties and performance of advanced metallic materials - Provides for the efficient design of materials and processes to satisfy targeted performance in materials and structures - Enables the selection and development of new alloys for specific applications based upon evaluation of their microstructure as illustrated in this work

Architecting Robust Co-Design of Materials, Products, and Manufacturing Processes

Architecting Robust Co-Design of Materials, Products, and Manufacturing Processes
Author: Anand Balu Nellippallil
Publisher: Springer Nature
Total Pages: 368
Release: 2020-06-13
Genre: Technology & Engineering
ISBN: 3030453243

This book explores systems-based, co-design, introducing a “Decision-Based, Co-Design” (DBCD) approach for the co-design of materials, products, and processes. In recent years there have been significant advances in modeling and simulation of material behavior, from the smallest atomic scale to the macro scale. However, the uncertainties associated with these approaches and models across different scales need to be addressed to enable decision-making resulting in designs that are robust, that is, relatively insensitive to uncertainties. An approach that facilitates co-design is needed across material, product design and manufacturing processes. This book describes a cloud-based platform to support decisions in the design of engineered systems (CB-PDSIDES), which feature an architecture that promotes co-design through the servitization of decision-making, knowledge capture and use templates that allow previous solutions to be reused. Placing the platform in the cloud aids mass collaboration and open innovation. A valuable reference resource reference on all areas related to the design of materials, products and processes, the book appeals to material scientists, design engineers and all those involved in the emerging interdisciplinary field of integrated computational materials engineering (ICME).

Computational Materials System Design

Computational Materials System Design
Author: Dongwon Shin
Publisher: Springer
Total Pages: 239
Release: 2017-11-10
Genre: Technology & Engineering
ISBN: 3319682806

This book provides state-of-the-art computational approaches for accelerating materials discovery, synthesis, and processing using thermodynamics and kinetics. The authors deliver an overview of current practical computational tools for materials design in the field. They describe ways to integrate thermodynamics and kinetics and how the two can supplement each other.

Handbook On Big Data And Machine Learning In The Physical Sciences (In 2 Volumes)

Handbook On Big Data And Machine Learning In The Physical Sciences (In 2 Volumes)
Author:
Publisher: World Scientific
Total Pages: 1001
Release: 2020-03-10
Genre: Computers
ISBN: 9811204586

This compendium provides a comprehensive collection of the emergent applications of big data, machine learning, and artificial intelligence technologies to present day physical sciences ranging from materials theory and imaging to predictive synthesis and automated research. This area of research is among the most rapidly developing in the last several years in areas spanning materials science, chemistry, and condensed matter physics.Written by world renowned researchers, the compilation of two authoritative volumes provides a distinct summary of the modern advances in instrument — driven data generation and analytics, establishing the links between the big data and predictive theories, and outlining the emerging field of data and physics-driven predictive and autonomous systems.

Machine Learning in Molecular Sciences

Machine Learning in Molecular Sciences
Author: Chen Qu
Publisher: Springer Nature
Total Pages: 323
Release: 2023-11-02
Genre: Computers
ISBN: 3031371968

Machine learning and artificial intelligence have propelled research across various molecular science disciplines thanks to the rapid progress in computing hardware, algorithms, and data accumulation. This book presents recent machine learning applications in the broad research field of molecular sciences. Written by an international group of renowned experts, this edited volume covers both the machine learning methodologies and state-of-the-art machine learning applications in a wide range of topics in molecular sciences, from electronic structure theory to nuclear dynamics of small molecules, to the design and synthesis of large organic and biological molecules. This book is a valuable resource for researchers and students interested in applying machine learning in the research of molecular sciences.

Horizons in Materials

Horizons in Materials
Author: Nicola Maria Pugno
Publisher: Frontiers Media SA
Total Pages: 189
Release: 2022-08-23
Genre: Technology & Engineering
ISBN: 2889761630

The Frontiers in Materials Editorial Office team are delighted to present the “Horizons in Materials” article collection, showcasing high-impact, authoritative, and accessible Review articles covering important topics at the forefront of the materials science and engineering field. All contributing authors were nominated by the Chief Editors and Editorial Office in recognition of their prominence and influence in their respective fields. The cutting-edge work presented in this article collection highlights the diversity of research performed across the entire breadth of the materials science and engineering field and reflects on the latest advances in theory, experiment, and methodology with applications to compelling problems. This Editorial features the corresponding author(s) of each paper published within this important collection, ordered by section alphabetically, highlighting them as the great researchers of the future. The Frontiers in Materials Chief Editors and Editorial Office team would like to thank each researcher who contributed their work to this collection. We are excited to see each article gain the deserved visibility and traction within the wider community, ensuring the collection’s truly global impact and success. Emily Young Journal Manager

Homogenization and materials design of mechanical properties of textured materials based on zeroth-, first- and second-order bounds of linear behavior

Homogenization and materials design of mechanical properties of textured materials based on zeroth-, first- and second-order bounds of linear behavior
Author: Lobos Fernández, Mauricio
Publisher: KIT Scientific Publishing
Total Pages: 224
Release: 2018-07-09
Genre: Materials
ISBN: 3731507706

This work approaches the fields of homogenization and of materials design for the linear and nonlinear mechanical properties with prescribed properties-profile. The set of achievable properties is bounded by the zeroth-order bounds (which are material specific), the first-order bounds (containing volume fractions of the phases) and the second-order Hashin-Shtrikman bounds with eigenfields in terms of tensorial texture coefficients for arbitrarily anisotropic textured materials.