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Nanoinformatics

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Cover of 'Nanoinformatics'

Table of Contents

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    Book Overview
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    Chapter 1 Descriptors for Machine Learning of Materials Data
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    Chapter 2 Potential Energy Surface Mapping of Charge Carriers in Ionic Conductors Based on a Gaussian Process Model
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    Chapter 3 Machine Learning Predictions of Factors Affecting the Activity of Heterogeneous Metal Catalysts
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    Chapter 4 Machine Learning-Based Experimental Design in Materials Science
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    Chapter 5 Persistent Homology and Materials Informatics
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    Chapter 6 Polyhedron and Polychoron Codes for Describing Atomic Arrangements
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    Chapter 7 Topological Data Analysis for the Characterization of Atomic Scale Morphology from Atom Probe Tomography Images
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    Chapter 8 Atomic-Scale Nanostructures by Advanced Electron Microscopy and Informatics
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    Chapter 9 High Spatial Resolution Hyperspectral Imaging with Machine-Learning Techniques
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    Chapter 10 Fabrication, Characterization, and Modulation of Functional Nanolayers
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    Chapter 11 Grain Boundary Engineering of Alumina Ceramics
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    Chapter 12 Structural Relaxation of Oxide Compounds from the High-Pressure Phase
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    Chapter 13 Synthesis and Structures of Novel Solid-State Electrolytes
Attention for Chapter 6: Polyhedron and Polychoron Codes for Describing Atomic Arrangements
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