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Titel:AI-guided design and property prediction for zeolites and nanoporous materials
Mitwirkende:Sastre, German [HerausgeberIn]   i
 Daeyaert, Frederik F. [HerausgeberIn]   i
Verf.angabe:edited by German Sastre, Frits Daeyaert
Verlagsort:Hoboken, NJ
Verlag:John Wiley and Sons, Inc.
Jahr:2023
Umfang:1 online resource (xxvi, 431 pages)
Illustrationen:illustrations (chiefly color)
Fussnoten:Includes bibliographical references and index. - Description based on online resource; title from digital title page (viewed on April 27, 2023)
ISBN:978-1-119-81978-3
 1-119-81978-4
 978-1-119-81976-9
 1-119-81976-8
 978-1-119-81977-6
 1-119-81977-6
 978-1-119-81975-2
Abstract: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.
URL:Aggregator: https://learning.oreilly.com/library/view/-/9781119819752/?ar
Datenträger:Online-Ressource
Sprache:eng
Bibliogr. Hinweis:Erscheint auch als : Druck-Ausgabe
Sach-SW:Artificial intelligence
 Molecules ; Models
 Zeolites ; Analysis
K10plus-PPN:185415561X
 
 
Lokale URL UB: Zum Volltext
 
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 Klinikum MA Bestellen/Vormerken für Benutzer des Klinikums Mannheim
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Bibliothek/Idn:UW / m4362059415
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