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Informatics for Materials Science and Engineering

INFORMATICS FOR MATERIALS SCIENCE AND ENGINEERING

Engineering

Mathematics & Science

Materials Science

Gt Product Group

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B2B GT

CL Carton Count

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B2B & B2C

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.

POST SECONDARY FOUR YEAR

COLFR

COLJR

COLSO

COLSR

Duration

Duration Unit Of Measure

Transaction Type

Front Cover.
Half Title Page.
Title Page.
Copyright Page.
Contents.
Preface: A Reading Guide.
Acknowledgment.
1: Materials Informatics: An Introduction.
2: Data Mining in Materials Science and Engineering.
3: Novel Approaches to Statistical Learning in Materials Science.
4: Cluster Analysis: Finding Groups in Data.
5: Evolutionary Data-Driven Modeling.
6: Data Dimensionality Reduction in Materials Science.
7: Visualization in Materials Research: Rendering Strategies of Large Data Sets.
8: Ontologies and Databases &#x2013; Knowledge Engineering for Materials Informatics.
9: Experimental Design for Combinatorial Experiments.
10: Materials Selection for Engineering Design.
11: Thermodynamic Databases and Phase Diagrams.
12: Towards Rational Design of Sensing Materials from Combinatorial Experiments.
13: High-Performance Computing for Accelerated Zeolitic Materials Modeling.
14: Evolutionary Algorithms Applied to Electronic-Structure Informatics: Accelerated Materials Design Using Data Discovery vs. Data Searching.
15: Informatics for Crystallography: Designing Structure Maps.
16: From Drug Discovery QSAR to Predictive Materials QSPR: The Evolution of Descriptors, Methods, and Models.
17: Organic Photovoltaics.
18: Microstructure Informatics.
19: Artworks and Cultural Heritage Materials: Using Multivariate Analysis to Answer Conservation Questions.
20: Data Intensive Imaging and Microscopy: A Multidimensional Data Challenge.
Index.

Informatics for Materials Science and Engineering.css-1p8rvzy{position:absolute;padding-left:8px;}

Informatics for Materials Science and Engineering