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Information Science for Materials Discovery and Design

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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 8: Optimal Dopant Selection for Water Splitting with Cerium Oxides: Mining and Screening First Principles Data
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