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Materials Informatics

  • ID: 4470756
  • Book
  • September 2020
  • Region: Global
  • 450 Pages
  • John Wiley and Sons Ltd
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A one–stop source on recent advances in the application of data mining to materials science, this book provides an up–to–date overview of the latest software and tools.

Clearly structured and divided into two parts, the first focuses on current progress in data mining and machine learning for materials science, while the second part addresses developments in software, databases and high–throughput computational activities.

Successful case studies illustrate the power of materials informatics in guiding the experimental discovery of novel materials. A practical approach is maintained throughout, with hints on how to use already existing databases of materials′ properties and an accompanying website with interactive applications.

A must–have for material scientists, chemists and engineers interested in these time–saving methods.
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METHODOLOGICAL ASPECTS OF MATERIALS INFORMATICS

Big Data in Chemistry

Genetic Algorithms, Crystal Structure Prediction

Machine Learning in Materials Science

MQSPR Modeling in Materials Informatics

Machine Learning Predictions of Molecular Properties

Statistical Modeling for Material Databases

Machine Learning Models in Chemical Space

Big Data in Materials Informatics

Topological Analysis of Crystal Structures

SOFTWARE AND TOOLS FOR MATERIALS INFORMATICS

AFLOWLIB

Harvard Clean Energy

Python Software for MI

High–Throughput Computational Screening of Materials

Open Quantum Materials Database

Computational Materials Repository

ICSD Database

Open Crystallography Database
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Olexandr Isayev
Alexander Tropsha
Stefano Curtarolo
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