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Nanoinformatics [electronic resource] / edited by Isao Tanaka.

Contributor(s): Material type: TextTextPublisher: Singapore : Springer Singapore : Imprint: Springer, 2018Edition: 1st ed. 2018Description: VIII, 298 p. 188 illus., 142 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9789811076176
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 620.115 23
LOC classification:
  • T174.7
  • TA418.9.N35
Online resources:
Contents:
1. Descriptors for Machine Learning of Materials Data -- 2. Potential Energy Surface Mapping of Charge Carriers in Ionic Conductors Based on a Gaussian Process Model -- 3. Machine learning predictions of factors affecting the activity of heterogeneous metal catalysts -- 4. Machine Learning-based Experimental Design in Materials Science -- 5. Persistent homology and materials informatics -- 6. Polyhedron and Polychoron codes for describing Atomic Arrangements -- 7. Topological Data Analysis for the Characterization of Atomic Scale Morphology from Atom Probe Tomography Images -- 8. Atomic-scale nanostructures by advanced electron microscopy and informatics -- 9. High spatial resolution hyperspectral imaging with machine-learning techniques -- 10. Fabrication, Characterization, and Modulation of Functional Nanolayers -- 11. Grain Boundary Engineering of Alumina Ceramics -- 12. Structural relaxation of oxide compounds from the high-pressure phase.-13.Synthesis and structures of novel solid-state electrolytes.
In: Springer eBooksSummary: This open access book brings out the state of the art on how informatics-based tools are used and expected to be used in nanomaterials research. There has been great progress in the area in which “big-data” generated by experiments or computations are fully utilized to accelerate discovery of new materials, key factors, and design rules. Data-intensive approaches play indispensable roles in advanced materials characterization. "Materials informatics" is the central paradigm in the new trend. "Nanoinformatics" is its essential subset, which focuses on nanostructures of materials such as surfaces, interfaces, dopants, and point defects, playing a critical role in determining materials properties. There have been significant advances in experimental and computational techniques to characterize individual atoms in nanostructures and to gain quantitative information. The collaboration of researchers in materials science and information science is growing actively and is creating a new trend in materials science and engineering. This book is open access under a CC BY license.
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1. Descriptors for Machine Learning of Materials Data -- 2. Potential Energy Surface Mapping of Charge Carriers in Ionic Conductors Based on a Gaussian Process Model -- 3. Machine learning predictions of factors affecting the activity of heterogeneous metal catalysts -- 4. Machine Learning-based Experimental Design in Materials Science -- 5. Persistent homology and materials informatics -- 6. Polyhedron and Polychoron codes for describing Atomic Arrangements -- 7. Topological Data Analysis for the Characterization of Atomic Scale Morphology from Atom Probe Tomography Images -- 8. Atomic-scale nanostructures by advanced electron microscopy and informatics -- 9. High spatial resolution hyperspectral imaging with machine-learning techniques -- 10. Fabrication, Characterization, and Modulation of Functional Nanolayers -- 11. Grain Boundary Engineering of Alumina Ceramics -- 12. Structural relaxation of oxide compounds from the high-pressure phase.-13.Synthesis and structures of novel solid-state electrolytes.

Open Access

This open access book brings out the state of the art on how informatics-based tools are used and expected to be used in nanomaterials research. There has been great progress in the area in which “big-data” generated by experiments or computations are fully utilized to accelerate discovery of new materials, key factors, and design rules. Data-intensive approaches play indispensable roles in advanced materials characterization. "Materials informatics" is the central paradigm in the new trend. "Nanoinformatics" is its essential subset, which focuses on nanostructures of materials such as surfaces, interfaces, dopants, and point defects, playing a critical role in determining materials properties. There have been significant advances in experimental and computational techniques to characterize individual atoms in nanostructures and to gain quantitative information. The collaboration of researchers in materials science and information science is growing actively and is creating a new trend in materials science and engineering. This book is open access under a CC BY license.

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