{"product_id":"informatics-for-materials-science-and-engineering-data-driven-discovery-for-accelerated-experimentation-and-application-hardback-9780123943996","title":"Informatics for Materials Science and Engineering; Data-driven Discovery for Accelerated Experimentation and Application (Hardback) 9780123943996","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eInformatics for Materials Science and Engineering\u003c\/font\u003e\u003cbr\u003e\r\n\u003cfont size=\"5\"\u003eData-driven Discovery for Accelerated Experimentation and Application\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cem\u003e\u003cp\u003eEncompasses the mathematical and computational foundations of materials informatics, from experimental to real-world applications\u003c\/p\u003e\u003c\/em\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003cp\u003e\u003cfont size=\"4\"\u003eKrishna Rajan (Edited by)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9780123943996, Elsevier Science\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 15 July 2013\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e542 pages, 80 illustrations\u003cbr\u003e22.9 x 15.1 x 3.1 cm, 0.91 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cem\u003e\u003cfont size=\"3\"\u003e\u003cp\u003e\"The first half of the volume sets out foundational aspects of data science, and the second half surveys applications in materials science using a case-study approach. The topics include novel approaches to statistical learning in materials science, data dimensionality reduction in materials science,…. high-performance computing for accelerated zeolitic materials modeling, and using multivariate analysis to answer questions concerning the conservation of artworks and cultural heritage materials.\" --\u003cb\u003eReference \u0026amp; Research Book News, December 2013\u003c\/b\u003e\u003c\/p\u003e\u003c\/font\u003e\u003c\/em\u003e\u003c\/p\u003e\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003e\u003cp\u003eMaterials 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. \u003c\/p\u003e \u003cp\u003eThe 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. \u003c\/p\u003e \u003cp\u003eThis 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. \u003c\/p\u003e \u003cp\u003eThis 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.\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e\u003cp\u003ePreface: A Reading Guide xiii Acknowledgment xv 1. Materials Informatics: An Introduction 1 2. Data Mining in Materials Science and Engineering 17 3. Novel Approaches to Statistical Learning in Materials Science 37 4. Cluster Analysis: Finding Groups in Data 53 5. Evolutionary Data-Driven Modeling 71 6. Data Dimensionality Reduction in Materials Science 97 7. Visualization in Materials Research: Rendering Strategies of Large Data Sets 121 8. Ontologies and Databases \u0026lt; Knowledge Engineering for Materials Informatics 147 9. Experimental Design for Combinatorial Experiments 189 10. Materials Selection for Engineering Design 219 11. Thermodynamic Databases and Phase Diagrams 245 12. Towards Rational Design of Sensing Materials from Combinatorial Experiments 271 13. High-Performance Computing for Accelerated Zeolitic Materials Modeling 315 14. Evolutionary Algorithms Applied to Electronic-Structure Informatics: Accelerated Materials Design Using Data Discovery vs. Data Searching 349 15. Informatics for Crystallography: Designing Structure Maps 365 16. From Drug Discovery QSAR to Predictive Materials QSPR: The Evolution of Descriptors, Methods, and Models 385 17. Organic Photovoltaics 423 18. Microstructure Informatics 443 19. Artworks and Cultural Heritage Materials: Using Multivariate Analysis to Answer Conservation Questions 467 20. Data Intensive Imaging and Microscopy: A Multidimensional Data Challenge 495 References 510 Index 513\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Materials science [\u003ca title=\"See our other books on Materials science\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Materials%20science%20%5BTGM%5D%22\"\u003eTGM\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Butterworth-Heinemann","offers":[{"title":"Default Title","offer_id":46649331122456,"sku":"9780123943996","price":125.99,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/products\/9780123943996.jpg?v=1694099773","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/informatics-for-materials-science-and-engineering-data-driven-discovery-for-accelerated-experimentation-and-application-hardback-9780123943996","provider":"Freshly Printed Books","version":"1.0","type":"link"}