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Information Science for Materials Discovery and Design

Overview of attention for book
Cover of 'Information Science for Materials Discovery and Design'

Table of Contents

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    Book Overview
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    Chapter 1 A Perspective on Materials Informatics: State-of-the-Art and Challenges
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    Chapter 2 Information-Driven Experimental Design in Materials Science
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    Chapter 3 Bayesian Optimization for Materials Design
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    Chapter 4 Small-Sample Classification
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    Chapter 5 Data Visualization and Structure Identification
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    Chapter 6 Inference of Hidden Structures in Complex Physical Systems by Multi-scale Clustering
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    Chapter 7 On the Use of Data Mining Techniques to Build High-Density, Additively-Manufactured Parts
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    Chapter 8 Optimal Dopant Selection for Water Splitting with Cerium Oxides: Mining and Screening First Principles Data
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    Chapter 9 Toward Materials Discovery with First-Principles Datasets and Learning Methods
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    Chapter 10 Materials Informatics Using Ab initio Data: Application to MAX Phases
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    Chapter 11 Symmetry-Adapted Distortion Modes as Descriptors for Materials Informatics
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    Chapter 12 Discovering Electronic Signatures for Phase Stability of Intermetallics via Machine Learning
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    Chapter 13 Combinatorial Materials Science, and a Perspective on Challenges in Data Acquisition, Analysis and Presentation
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    Chapter 14 High Throughput Combinatorial Experimentation + Informatics = Combinatorial Science
Attention for Chapter 1: A Perspective on Materials Informatics: State-of-the-Art and Challenges
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Citations

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Summary Dimensions citations
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Chapter title
A Perspective on Materials Informatics: State-of-the-Art and Challenges
Chapter number 1
Book title
Information Science for Materials Discovery and Design
Published in
ADS, January 2016
DOI 10.1007/978-3-319-23871-5_1
Book ISBNs
978-3-31-923870-8, 978-3-31-923871-5
Authors

T. Lookman, P. V. Balachandran, D. Xue, G. Pilania, T. Shearman, J. Theiler, J. E. Gubernatis, J. Hogden, K. Barros, E. BenNaim, F. J. Alexander

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 13%
Researcher 3 13%
Student > Doctoral Student 2 8%
Professor 2 8%
Student > Bachelor 1 4%
Other 5 21%
Unknown 8 33%
Readers by discipline Count As %
Materials Science 7 29%
Chemical Engineering 3 13%
Engineering 2 8%
Medicine and Dentistry 1 4%
Linguistics 1 4%
Other 0 0%
Unknown 10 42%

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