Kniha Informatics for Materials Science and Engineering Krishna Rajan

Informatics for Materials Science and Engineering

Autor: Krishna Rajan
Jazyk: Angličtina
Väzba: Pevná
Dostupnosť: Skladom u dodávateľa
Odosielame za 10-18 dní
201.65
Materials informatics: a 'hot topic' area in materials science, aims to combine traditionally bio-le...

Informácie o knihe

Jazyk
Angličtina
Väzba
Kniha - Pevná
Vydalo
2013
Stránok
542
EAN
9780123943996
ISBN
012394399X
Enbook ID
01321917
Hmotnosť
880
Rozmery
159 x 232 x 36

Kompletný popis

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. It identifies and analyzes interdisciplinary strategies (including combinatorial and high throughput approaches) that accelerate materials development cycle times and reduces associated costs. It offers mathematical and computational analysis that aids formulation of new structure-property correlations among large, heterogeneous, and distributed data sets. It includes practical examples, computational tools, and software analysis that benefits rapid identification of critical data and analysis of theoretical needs for future problems.

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