Computational materials discovery / edited by Artem R. Oganov, Gabriele Saleh, Alexander G. Kvashnin.
A unique and timely book providing an overview of both the methodologies and applications of computational materials design.
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Format: | eBook |
Language: | English |
Published: |
Cambridge :
Royal Society of Chemistry,
2018.
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Subjects: |
MARC
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245 | 0 | 0 | |a Computational materials discovery / |c edited by Artem R. Oganov, Gabriele Saleh, Alexander G. Kvashnin. |
264 | 1 | |a Cambridge : |b Royal Society of Chemistry, |c 2018. | |
300 | |a 1 online resource. | ||
336 | |a text |b txt |2 rdacontent. | ||
337 | |a computer |b c |2 rdamedia. | ||
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505 | 0 | |a Cover; Copyright; Editor Biographies; Contents; Chapter 1 Computational Materials Discovery: Dream or Reality?; Acknowledgements; References; Chapter 2 Computational Materials Discovery Using Evolutionary Algorithms; 2.1 A Bit of Theory; 2.1.1 Combinatorial Complexity of the Problem; 2.2 How the Method Works; 2.2.1 Initialization; 2.2.2 Representation; 2.2.3 Fitness Function; 2.2.4 Selection; 2.2.5 Variation Operators; 2.2.6 How to Avoid Getting Stuck to Local Minima; 2.2.7 Extension to Variable-composition Systems; 2.2.8 Extension to Molecular Crystals. | |
505 | 8 | |a 2.2.9 A Few Comments on the Performance of the Method2.3 A Few Illustrations of the Method; 2.3.1 Novel Chemistry of the Elements Under Pressure; 2.3.2 Low-dimensional States of the Elements; 2.3.3 Discovering New Chemical Compounds at High Pressure ... and Even at Zero Pressure; 2.3.4 Hunt for High-Tc Superconductivity; 2.3.5 Low-dimensional Systems: Surfaces, Polymers, Nanoparticles, Proteins; 2.4 Conclusions; Acknowledgements; References; Chapter 3 Applications of Machine Learning for Representing Interatomic Interactions; 3.1 Introduction; 3.1.1 Quantum-mechanical Models. | |
505 | 8 | |a 3.1.2 Empirical Interatomic Potentials3.1.3 Machine Learning Interatomic Potentials; 3.2 Simple Problem: Fitting of Potential Energy Surfaces; 3.2.1 Representation of Atomic Systems; 3.2.2 An Overview of Machine Learning Methods; 3.3 Machine Learning Interatomic Potentials; 3.3.1 Representation of Atomic Environments; 3.3.2 Existing MLIPs; 3.4 Fitting and Testing of Interatomic Potentials; 3.4.1 Optimization Algorithms; 3.4.2 Validation and Cross-validation; 3.4.3 Learning on the Fly; 3.5 Discussion; 3.5.1 Which Potential Is Better?; 3.5.2 Open Problems in MLIP Development. | |
505 | 8 | |a 3.6 Further ReadingReferences; Chapter 4 Embedding Methods in Materials Discovery; 4.1 Preamble; 4.2 Background; 4.3 Embedding Methods; 4.3.1 Partitioning of the Structure and Interactions; 4.3.2 Self-consistent Embedding; 4.3.3 Beyond DFT Treatment of the Cluster Part -- Viva Quantum Chemistry; 4.4 Applications; 4.4.1 Why Embedding?; 4.4.2 Energetics; 4.4.3 Spectroscopic Properties; 4.4.4 Electronic Properties; 4.4.5 Hybrid Embedding Approach; 4.4.6 Derivation of Model Parameters; 4.5 Outlook; Acknowledgements; References; Chapter 5 Chemical Bonding Investigations for Materials. | |
520 | |a A unique and timely book providing an overview of both the methodologies and applications of computational materials design. | ||
588 | 0 | |a Print version record. | |
650 | 0 | |a Materials science |x Computer simulation. | |
650 | 0 | |a Materials |x Mathematical models. | |
650 | 7 | |a Materials |x Mathematical models. |2 fast |0 (OCoLC)fst01011852. | |
650 | 7 | |a Materials science |x Computer simulation. |2 fast |0 (OCoLC)fst01011959. | |
700 | 1 | |a Oganov, Artem R. |q (Artem Romaevich), |e editor. |0 http://id.loc.gov/authorities/names/nb2010032224 |1 http://isni.org/isni/0000000108498235. | |
700 | 1 | |a Saleh, Gabriele, |e editor. | |
700 | 1 | |a Kvashnin, Alexander G., |e editor. | |
776 | 0 | 8 | |i Print version: |t Computational materials discovery. |d Cambridge : Royal Society of Chemistry, 2018 |z 9781782629610 |w (OCoLC)1064679432. |
856 | 4 | 0 | |u https://colorado.idm.oclc.org/login?url=https://app.knovel.com/hotlink/toc/id:kpCMD00016/computational-materials-discovery?kpromoter=marc |z Full Text (via Knovel) |
880 | 8 | |6 505-00/(S |a 5.1 Introduction5.2 Paradigms of Chemistry and Chemical Bonding Descriptors; 5.2.1 Topological Methods, Quantum Chemical Topology and Beyond; 5.2.2 Orbital Based Methods; 5.3 Selected Applications; 5.3.1 Charge Transfer and Bonding in γ-Boron; 5.3.2 Xe Oxides; 5.3.3 He Forms Compounds at High Pressure; 5.3.4 Phase Change Materials; 5.4 Conclusion; Acknowledgements; References; Chapter 6 Computational Design of Photovoltaic Materials; 6.1 Introduction; 6.2 The Design Process; 6.2.1 Requirements; 6.2.2 Design; 6.2.3 Development; 6.2.4 Testing; 6.3 Practical Computational Techniques. | |
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