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Frustrated Materials and Ferroic Glasses / / edited by Turab Lookman, Xiaobing Ren
| Frustrated Materials and Ferroic Glasses / / edited by Turab Lookman, Xiaobing Ren |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (283 pages) |
| Disciplina | 620.11 |
| Collana | Springer Series in Materials Science |
| Soggetto topico |
Magnetism
Magnetic materials Ceramics Glass Composites (Materials) Composite materials Nanotechnology Nanochemistry Optical materials Electronic materials Solid state physics Magnetism, Magnetic Materials Ceramics, Glass, Composites, Natural Materials Nanotechnology and Microengineering Optical and Electronic Materials Solid State Physics |
| ISBN | 3-319-96914-5 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | List of Contributors -- Preface -- 1 What can spin glass theory and analogies tell us about ferroic glasses? -- 2 Spin glasses: Experimental signatures and salient outcomes -- 3 Frustration(s) and the Ice Rule: From Natural Materials to the Deliberate Design of Exotic Behaviors -- 4 Glassy phenomena and precursors in the lattice dynamics -- 5 Relaxor Ferroelectrics -- 6 Probing glassiness in Heuslers via density functional theory calculations -- 7 Strain glasses -- 8 Discrete pseudo spin and continuum models for strain glass -- 9 Mesoscopic modelling of strain glass -- 10 Phase field simulations of ferroic glasses. |
| Record Nr. | UNINA-9910300547303321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Information Science for Materials Discovery and Design / / edited by Turab Lookman, Francis J. Alexander, Krishna Rajan
| Information Science for Materials Discovery and Design / / edited by Turab Lookman, Francis J. Alexander, Krishna Rajan |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (316 p.) |
| Disciplina | 620.11 |
| Collana | Springer Series in Materials Science |
| Soggetto topico |
Nanotechnology
Engineering—Materials Data mining Statistical physics Dynamical systems Materials science Materials Engineering Data Mining and Knowledge Discovery Complex Systems Characterization and Evaluation of Materials Statistical Physics and Dynamical Systems |
| ISBN | 3-319-23871-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | From the Contents: Introduction -- Data-Driven Discovery of Physical, Chemical, and Pharmaceutical Materials -- Cross-Validation and Inference in Bioinformatics/Cancer Genomics -- Applying MQSPRs - New Challenges and Opportunities. |
| Record Nr. | UNINA-9910254043203321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Materials Discovery and Design : By Means of Data Science and Optimal Learning / / edited by Turab Lookman, Stephan Eidenbenz, Frank Alexander, Cris Barnes
| Materials Discovery and Design : By Means of Data Science and Optimal Learning / / edited by Turab Lookman, Stephan Eidenbenz, Frank Alexander, Cris Barnes |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (266 pages) |
| Disciplina | 006.312 |
| Collana | Springer Series in Materials Science |
| Soggetto topico |
Physics
Materials science Data mining Engineering—Materials Computer mathematics Numerical analysis Numerical and Computational Physics, Simulation Characterization and Evaluation of Materials Data Mining and Knowledge Discovery Materials Engineering Computational Science and Engineering Numerical Analysis |
| ISBN | 3-319-99465-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part 1: Learning from Data in Material Science -- Designing Novel Multifunctional Materials via Inverse Optimization Techniques -- Quantifying Uncertainties in First Principles Alloy Thermodynamics -- Forward Modeling of Electron Scattering Modalities for Microstructure Quantification -- The Potential of Network Analysis Strategies to HEDM Data: Classification of Microstructures and Prediction of Incipient Failure -- Part 2: Data and Inference -- Challenges of Diagram extraction and Understanding -- Integration of Computational Reasoning, Machine Learning, and Crowdsourcing for Accelerating Materials Discovery -- Computational Creativity for Materials Science -- Optimal Experimental Design Based on Uncertainty Quantification -- Part 3: High-Throughput Calculations and Experiments Functionality-Driven Design and Discovery -- The Use of Proxies and Data for Guiding Materials Synthesis: Examples of Phosphors and Thermoelectrics -- Big Data from Experiments -- Data-Driven Approaches to Combinatorial Materials Science -- Invariant Representations for Robust Materials Prediction -- Part 4: Data Optimization/Challenges in Analysis of Data for Facilities -- The MGI Data Infrastructure -- Is Rigorous Automated Materials Design and Discovery Possible? -- Improve your Monte Carlo: Learn a Control Variate and Correct it with Stacking -- X-ray Free Electron Laser Studies of Shock-Driven Deformation and Phase Transitions -- Coherent Diffraction Imaging Techniques at 3rd and 4th Generation Light Sources -- 3D Data Challenges from X-ray Synchrotron Tomography -- Part 5: Interference/HPC/Software Integration -- Optimal Bayesian Experimental Design: Formulations and New Computational Strategies -- Optimal Bayesian Inference with Missing Data -- Applying an Experimental Design Loop to Shape Memory Alloys -- Big Data Need Big Theory Too -- Combining Experiments, Simulation and Machine Learning in a Single Materials Platform - A Materials Informatics Approach -- Rethinking the HPC Programming Environment. |
| Record Nr. | UNINA-9910300537803321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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