| Description |
1 online resource (xxvi, 431 pages) : illustrations (chiefly color) |
| Bibliography |
Includes bibliographical references and index. |
| Contents |
The confluence of organo-cations, inorganic species, and molecular modeling on the discovery of new zeolite structures and compositions / Christopher M. Lew, Dan Xie, Joel E. Schmidt, Saleh Elomari, Tracy M. Davis, and Stacey I. Zones -- Efficient data utilization in training machine learning models for nanoporous materials screening / Jiham Kim. |
| Summary |
AI-Guided Design and Property Prediction for Zeolites and Nanoporous Materials A cohesive and insightful compilation of resources explaining the latest discoveries and methods in the field of nanoporous materials In Artificial Intelligence for Zeolites and Nanoporous Materials: Design, Synthesis and Properties Prediction a team of distinguished researchers delivers a robust compilation of the latest knowledge and most recent developments in computational chemistry, synthetic chemistry, and artificial intelligence as it applies to zeolites, porous molecular materials, covalent organic frameworks and metal-organic frameworks. The book presents a common language that unifies these fields of research and advances the discovery of new nanoporous materials. The editors have included resources that describe strategies to synthesize new nanoporous materials, construct databases of materials, structure directing agents, and synthesis conditions, and explain computational methods to generate new materials. They also offer material that discusses AI and machine learning algorithms, as well as other, similar approaches to the field. Readers will also find a comprehensive approach to artificial intelligence applied to and written in the language of materials chemistry, guiding the reader through the fundamental questions on how far computer algorithms and numerical representations can drive our search of new nanoporous materials for specific applications. Designed for academic researchers and industry professionals with an interest in synthetic nanoporous materials chemistry, Artificial Intelligence for Zeolites and Nanoporous Materials: Design, Synthesis and Properties Prediction will also earn a place in the libraries of professionals working in large energy, chemical, and biochemical companies with responsibilities related to the design of new nanoporous materials. |
| Subject |
Zeolites -- Analysis.
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Nanostructured materials -- Analysis.
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Molecules -- Models.
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Artificial intelligence.
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Zéolites -- Analyse. |
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Nanomatériaux -- Analyse. |
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Molécules -- Modèles. |
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Intelligence artificielle. |
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artificial intelligence. |
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Artificial intelligence |
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Molecules -- Models |
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Zeolites -- Analysis |
| Added Author |
Sastre, German, editor.
|
|
Daeyaert, Frederik F., editor.
|
| Other Form: |
Print version: AI-guided design and property prediction for zeolites and nanoporous materials Hoboken : John Wiley and Sons Ltd, 2023 9781119819752 (DLC) 2022042565 |
| ISBN |
9781119819783 electronic book |
|
1119819784 electronic book |
|
9781119819769 electronic book |
|
1119819768 electronic book |
|
9781119819776 electronic book |
|
1119819776 electronic book |
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hardcover |
| Standard No. |
10.1002/9781119819783 doi |
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