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Bücher Englische Bücher Wissen & Bildung Naturwissenschaft, Medizin, Informatik, Technik Physik & Astronomie Theoretische Physik Artificial Intelligence driven Materials Design
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Artificial Intelligence driven Materials Design
Piyush Tagade, Shashishekar P. Adiga (Gebundene Ausgabe, Englisch)
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Beschreibung
This book presents the application of machine learning and deep learning to Materials Design. Traditional materials design relies on a trial and error based iterative approach towards attaining target material properties often interspersed with accidental discoveries. This approach is very time consuming as both processing/fabrication, characterization of new compositions/structures are quite… laborious. The field of machine learning and deep learning can greatly benefit expediting this approach by narrowing down the search space and reducing the number of compounds/structures that are explored in the lab. This book covers the fundamentals of how one goes about applying Artificial Intelligence to materials design followed by specific examples. The book contains 4 sections. In the first section, fundamentals of AI, materials structure representation/digitization and theoretical framework are discussed. In the second section, materials optimization using evolutionary algorithms is discussed. In the third section, application of AI for forward prediction, i.e., given a material structure, how to predict properties, is considered. In the fourth section, we cover inverse prediction or inverse materials design, that is, predicting materials/structures with target properties. The inverse design of materials is an emerging field of materials design and the techniques we present are very novel. We provide examples from both organic and inorganic materials space with diverse fields of applications. The book includes sample codes for these example problems to help readers gain hands-on experience. Dieses Produkt haben wir gerade leider nicht auf Lager.
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Technische Daten
Erscheinungsdatum
12.12.2032
Sprache
Englisch
EAN
9789811922619
Herausgeber
Springer Singapore
Sonderedition
Nein
Autor
Piyush Tagade, Shashishekar P. Adiga
Auflage
1
Einbandart
Gebundene Ausgabe
Einbandart Details
Fadenbindung
Schlagwörter
Monte Carlo Tree Search, Density Functional Theory (DFT), Inverse Materials Design, Machine Learning (ML), Deep Learning (DL), Materials Characterization, Inverse Prediction, Electron Affinity in Organic Molecules
Thema-Inhalt
PHU - Mathematische Physik
TGM - Materialwissenschaft
UYQ - Künstliche Intelligenz
UYQM - Maschinelles Lernen
PN - Chemie
TGMT - Werkstoffprüfung
Höhe
235 mm
Breite
15.5 cm
Transparenz & Sicherheit
Hersteller: Springer Nature Singapore, ProductSafety@springernature.com, Springer Nature Customer Service Center GmbH
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