Informatics For Materials Science And Engineering

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. 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 "

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. 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

Provides everything readers need to know for applying the power of informatics to materials science There is a tremendous interest in materials informatics and application of data mining to materials science. This book is a one-stop guide to the latest advances in these emerging fields. Bridging the gap between materials science and informatics, it introduces readers to up-to-date data mining and machine learning methods. It also provides an overview of state-of-the-art software and tools. Case studies illustrate the power of materials informatics in guiding the experimental discovery of new materials. Materials Informatics: Methods, Tools and Applications is presented in two parts?Methodological Aspects of Materials Informatics and Practical Aspects and Applications. The first part focuses on developments in software, databases, and high-throughput computational activities. Chapter topics include open quantum materials databases; the ICSD database; open crystallography databases; and more. The second addresses the latest developments in data mining and machine learning for materials science. Its chapters cover genetic algorithms and crystal structure prediction; MQSPR modeling in materials informatics; prediction of materials properties; amongst others. -Bridges the gap between materials science and informatics -Covers all the known methodologies and applications of materials informatics -Presents case studies that illustrate the power of materials informatics in guiding the experimental quest for new materials -Examines the state-of-the-art software and tools being used today Materials Informatics: Methods, Tools and Applications is a must-have resource for materials scientists, chemists, and engineers interested in the methods of materials informatics.

The discipline of informatics emerged from the need to translate biomedical research into evidence-based healthcare protocols and policy. Materials science informatics is rooted in an analogous need to “translate” physical sciences research and discoveries into materials-based solutions to address a broad range of issues and challenges for business, government, and the environment. Ontologies and databases are key elements of translational architectures and therefore are fundamental tools of the practice of informatics. Databases are tools for engineering data and information, while ontologies are tools for engineering knowledge and utility. Since knowledge and utility are the core objectives of informatics, correctly understanding and utilizing ontologies is critical to the development of effective materials informatics programs and tools. Rooted in philosophy, the term ontology appears most frequently today in connection with semantic web technology, where it refers to vocabularies used by inference engines to interpret human use of language. Materials science ontologies need to capture the scientific context of the defined concepts to support modeling and prediction of multidimensional structure–property relationships in variable environments and applications. Addressing the complexity of materials science ontologies requires a significant departure from traditional database and semantic web ontology approaches, including the use of neural networks that are capable of implementing methods for modeling context, relevance, complex systems, and human expertise. Pioneering efforts in this space include the Knowledge Engineering for Nanoinformatics Pilot (KENI) launched by the Nanoinformatics Society in 2010, and a collaborative Materials Genome Modeling Methodology initiative led by Iowa State University and initiated in 2011.

Volume is indexed by Thomson Reuters CPCI-S (WoS). The series, “Hungarian Conference and Exhibition on Materials Science, Testing and Informatics”, was founded in order to provide a forum in which Hungarian and foreign scientists and research groups - interested in metals and alloys, silicates, polymers and composites - would have the opportunity to exchange and publish ideas and to establish new integrated partnerships. The 4th Hungarian Conference and Exhibition on Materials Science, Testing and Informatics was held on the Balaton lakeside, at Balatonfüred, October 12-14th , 2003.

Selected, peer reviewed papers from the 8th Hungarian Conference on Materials Science, October 9-11, 2011, Balatonkenese, Hungary

Volume is indexed by Thomson Reuters CPCI-S (WoS). This collection includes state-of-the-art papers by scientists and research groups working in fields encompassing metals and alloys, silicates, polymers and composites.

Volume is indexed by Thomson Reuters CPCI-S (WoS). This collection comprises state-of-the-art papers written by scientists and research groups working in fields encompassing metals and alloys, silicates, polymers and composites.