Materials Informatics Methods (12 results)

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hardcover. Condition: Sehr gut. 304 Seiten; 9783527341214.2 Gewicht in Gramm: 1.

paperback. Condition: New. Language:Chinese.Paperback. Pub Date: 2024-12 Pages: 280 Publisher: National Defense Industry Press This book is co-authored by Professors Olexandriayev. Alexander Troha and Tefano Curtarolo. It is a new book that systematically introduces materials informatics. The content covers two parts: methods and tools of materials informatics. applicable aspects and application fields. It is divided into 9 chapters. The content of this book is clearly structured. from bottom to top. step by step. and .…

Taschenbuch. Condition: Neu. Materials Informatics I | Methods | Kunal Roy (u. a.) | Taschenbuch | Challenges and Advances in Computational Chemistry and Physics | xvii | Englisch | 2026 | Springer | EAN 9783031787386 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This contributed volume explores the integration of machine learning and cheminformatics within materials science, focusing on predictive modeling techniques. It begins with foundational concepts in materials informatics and cheminformatics, emphasizing quantitative structure-property relationships (QSPR). The volume then presents various methods and tools, including advanced QSPR models, quantitative read-across structure-property relationship (q-RASPR) models, optimization strategies with minimal data, and in silico studies using different descriptors. Additionally, it explores machine learning algorithms and their applications in materials science, alongside innovative modeling approaches for quantum-theoretic properties. Overall, the book serves as a comprehensive resource for understanding and applying machine learning in the study and development of advanced materials and is a useful tool for students, researchers and professionals working in these areas.…

Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This contributed volume explores the integration of machine learning and cheminformatics within materials science, focusing on predictive modeling techniques. It begins with foundational concepts in materials informatics and cheminformatics, emphasizing quantitative structure-property relationships (QSPR). The volume then presents various methods and tools, including advanced QSPR models, quantitative read-across structure-property relationship (q-RASPR) models, optimization strategies with minimal data, and in silico studies using different descriptors. Additionally, it explores machine learning algorithms and their applications in materials science, alongside innovative modeling approaches for quantum-theoretic properties. Overall, the book serves as a comprehensive resource for understanding and applying machine learning in the study and development of advanced materials and is a useful tool for students, researchers and professionals working in these areas.…

Condition: gut. 2019. Materials Informatics: Methods, Tools, and Applications In deutscher Sprache. pages.