Materials Informatics III

This contributed volume focuses on the application of machine learning and cheminformatics in predictive modeling for organic materials, polymers, solvents, and energetic materials. It provides an in-depth look at how machine learning is utilized to predict key properties of polymers, deep eutectic solvents, and ionic liquids, as well as to improve safety and performance in the study of energetic and reactive materials. With chapters covering polymer informatics, quantitative structure–property relationship (QSPR) modeling, and computational approaches, the book serves as a comprehensive resource for researchers applying predictive modeling techniques to advance materials science and improve material safety and performance.

• Erscheinungsdatum: 01.03.2025
• Autor/Autorin: Kunal Roy
• Reihe: Chemistry and Material Science (R0)
• Format: E-Book
• Dateiformat: PDF
• Kopierschutz: Wasserzeichen
• Dateigröße: 15.4 MB
• Verlag: SPRINGER
• Sprache: Englisch
• Umfang: 300 Seiten
• ISBN: 9783031787249
• Lieferung: Sofort per Download
• Hinweis: Sofort per Download lieferbar. Kein physischer Versand.
• Kompatibilität: Lesbar auf Geräten und Apps mit PDF-Unterstützung.