Informatics for materials science and engineering : data-driven discovery for accelerated experimentation and application / edited by Krishna Rajan.

Machine generated contents note: 1.Materials Informatics: An Introduction / Krishna Rajan -- 1.The What and Why of Informatics -- 2.Learning from Systems Biology: An "OMICS" Approach to Materials Design -- 3.Where Do We Get the Information? -- 4.Data Mining: Data-Driven Materials Research -- References -- 2.Data Mining in Materials Science and Engineering / Ya Ju Fan -- 1.Introduction -- 2.Analysis Needs of Science Applications -- 3.The Scientific Data-Mining Process -- 4.Image Analysis -- 5.Dimension Reduction -- 6.Building Predictive and Descriptive Models -- 7.Further Reading -- Acknowledgments -- References -- 3.Novel Approaches to Statistical Learning in Materials Science / T. Lookman -- 1.Introduction -- 2.The Supervised Binary Classification Learning Problem -- 3.Incorporating Side Information -- 4.Conformal Prediction -- 5.Optimal Learning -- 6.Optimal Uncertainty Quantification -- 7.Clustering Including Statistical Physics Approaches --

Contents note continued: 8.Materials Science Example: The Search for New Piezoelectrics -- 9.Conclusion -- 10.Further Reading -- Acknowledgments -- References -- 4.Cluster Analysis: Finding Groups in Data / Somnath Datta -- 1.Introduction -- 2.Unsupervised Learning -- 3.Different Clustering Algorithms and their Implementations in R -- 4.Validations of Clustering Results -- 5.Rank Aggregation of Clustering Results -- 6.Further Reading -- Acknowledgments -- References -- 5.Evolutionary Data-Driven Modeling / Nirupam Chakraborti -- 1.Preamble -- 2.The Concept of Pareto Tradeoff -- 3.Evolutionary Neural Net and Pareto Tradeoff -- 4.Selecting the Appropriate Model in EvoNN -- 5.Conventional Genetic Programming -- 6.Bi-objective Genetic Programming -- 7.Analyzing the Variable Response In EvoNN and BioGP -- 8.An Application in the Materials Area -- 9.Further Reading -- References -- 6.Data Dimensionality Reduction in Materials Science / B. Ganapathysubramanian -- 1.Introduction --

Contents note continued: 2.Dimensionality Reduction: Basic Ideas and Taxonomy -- 3.Dimensionality Reduction Methods: Algorithms, Advantages, and Disadvantages -- 4.Dimensionality Estimators -- 5.Software -- 6.Analyzing Two Material Science Data Sets: Apatites and Organic Solar Cells -- 7.Further Reading -- References -- 7.Visualization in Materials Research: Rendering Strategies of Large Data Sets / Richard Lesar -- 1.Introduction -- 2.Graphical Tools for Data Visualization: Case Study for Combinatorial Experiments -- 3.Interactive Visualization: Querying Large Imaging Data Sets -- 4.Suggestions for Further Reading -- Acknowledgments -- References -- 8.Ontologies and Databases - Knowledge Engineering for Materials Informatics / Joseph Glick -- 1.Introduction -- 2.Ontologies -- 3.Databases -- 4.Conclusions and Further Reading -- References -- Websites -- 9.Experimental Design for Combinatorial Experiments / James N. Cawse -- 1.Introduction --

Contents note continued: 2.Standard Design of Experiments (DOE) Methods -- 3.Mixture (Formulation) Designs -- 4.Compound Designs -- 5.Restricted Randomization, Split-Plot, and Related Designs -- 6.Evolutionary Designs -- 7.Designs for Determination of Kinetic Parameters -- 8.Other Methods -- 9.Gradient Spread Designs -- 10.Looking Forward -- References -- 10.Materials Selection for Engineering Design / David Cebon -- 1.Introduction -- 2.Systematic Selection -- 3.Material Indices -- 4.Using Charts to Explore Material Properties -- 5.Practical Materials Selection: Tradeoff Methods -- 6.Material Substitution -- 7.Vectors for Material Development -- 8.Conclusions and Suggested Further Reading -- References -- 11.Thermodynamic Databases and Phase Diagrams / S.K. Saxena -- 1.Introduction -- 2.Thermodynamic Databases -- 3.Examples of Phase Diagrams -- References -- 12.Towards Rational Design of Sensing Materials from Combinatorial Experiments / Radislav Potyrailo -- 1.Introduction --

Contents note continued: 2.General Principles of Combinatorial Materials Screening -- 3.Opportunities for Sensing Materials -- 4.Designs of Combinatorial Libraries of Sensing Materials -- 5.Optimization of Sensing Materials Using Discrete Arrays -- 6.Optimization of Sensing Materials Using Gradient Arrays -- 7.Summary and Outlook -- 8.Further Reading -- Acknowledgments -- References -- 13.High-Performance Computing for Accelerated Zeolitic Materials Modeling / Pierre Collet -- 1.Introduction -- 2.GPGPU-Based Genetic Algorithms -- 3.Standard Optimization Benchmarks -- 4.Fast Generation of Four-Connected 3D Nets for Modeling Zeolite Structures -- 5.Real Zeolite Problem -- 6.Further Reading -- References -- 14.Evolutionary Algorithms Applied to Electronic-Structure Informatics: Accelerated Materials Design Using Data Discovery vs. Data Searching / Duane D. Johnson -- 1.Introduction -- 2.Intuitive Approach to Correlations -- 3.Genetic Programming for Symbolic Regression --

Contents note continued: 4.Constitutive Relations Via Genetic Programming -- 5.Further Reading -- Acknowledgments -- References -- 15.Informatics for Crystallography: Designing Structure Maps / Krishna Rajan -- 1.Introduction -- 2.Structure Map Design for Complex Inorganic Solids Via Principal Component Analysis -- 3.Structure Map Design for Intermetallics Via Recursive Partioning -- 4.Further Reading -- References -- 16.From Drug Discovery QSAR to Predictive Materials QSPR: The Evolution of Descriptors, Methods, and Models / Curt M. Breneman -- 1.Historical Perspective -- 2.The Science of MQSPR: Choice and Design of Material Property Descriptors -- 3.Mathematical Methods for QSPR/QSAR/MQSPR -- 4.Integration of Physical and MQSPR Models for Nanocomposite -- Materials Modeling -- 5.The Future of Materials Informatics Applications -- References -- 17.Organic Photovoltaics / Alan Aspuru-Guzik -- 1.Chemical Space, Energy Sources, and the Clean Energy Project --

Contents note continued: 2.The Molecular Library -- 3.Merit Figures for Organic Photovoltaics -- 4.Descriptors for Organic Photovoltaics -- 5.Predictions from Cheminformatics -- 6.Conclusions -- Acknowledgments -- References -- 18.Microstructure Informatics / Surya R. Kalidindi -- 1.Introduction -- 2.Microstructure Quantification Using Higher-Order Spatial Correlations -- 3.Objective Reduced-Order Representation of Microstructure -- 4.Data Science-Enabled Formulation of Structure-Property-Processing (SPP) Linkages -- 5.Computationally Efficient Scale-Bridging for Multiscale Materials Modeling -- 6.Further Reading -- Acknowledgments -- References -- 19.Artworks and Cultural Heritage Materials: Using Multivariate Analysis to Answer Conservation Questions / Carl Villis -- 1.Rock Art Petroglyphs Examined with Reflectance NIR Spectroscopy and PCA -- 2.Adhesives Study of Cypriot Pottery Collection with FTIR Spectroscopy and PCA --

Contents note continued: 3.Egyptian Sarcophagus Examined with ToF-SIMS, XANES, and PCA -- 4.Attribution Studies of an Italian Renaissance Painting: ESEM Imaging -- 5.Ochre Pigments Imaged Using Synchrotron XRF -- 6.General Summary and Conclusions -- References -- 20.Data Intensive Imaging and Microscopy: A Multidimensional Data Challenge / Krishna Rajan -- 1.Introduction -- 2.Chemical Imaging in Materials Science: Linking Signal and Spatial Domains -- 3.Contrast Mining in Spectroscopy: Tracking Processing-Property Relationships -- 4.Further Reading -- References.