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Materials informatics.. III,. Polymers, solvents and energetic materials

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Materials informatics./ edited by Kunal Roy, Arkaprava Banerjee.
其他題名:	Polymers, solvents and energetic materials
其他作者:	Roy, Kunal.
出版者:	Cham :Springer Nature Switzerland : : 2025.,
面頁冊數:	xv, 371 p. :ill. (some col.), digital ;24 cm.
內容註:	Part 1. Introduction -- Introduction to Machine Learning for Predictive Modeling II -- Introduction to predicting properties of organic materials -- Part 2. Cheminformatic and Machine Learning Models for Polymers -- Machine Learning Applications in Polymer Informatics - An Overview -- Applications of predictive modeling for selected properties of polymers -- Polymer Property Prediction using Machine Learning -- Applications of predictive modeling for polymers -- Part 3. Cheminformatic and Machine Learning Models for Solvents -- Applications of predictive QSPR modeling for deep eutectic solvents -- Applications of predictive modeling for various properties of ionic liquids -- Part 4. Cheminformatic and Machine Learning Models for Energetic Materials -- Improving Safety with Molecular-Scale Computational Approaches for Energetic and Reactive Materials -- Predictive modeling for energetic materials -- Modeling the performance of energetic materials -- Applications of predictive modeling for energetic materials.
Contained By:	Springer Nature eBook
標題:	Materials - Data processing. -
電子資源:	https://doi.org/10.1007/978-3-031-78724-9
ISBN:	9783031787249

Materials informatics.. III,. Polymers, solvents and energetic materials
Materials informatics.III,Polymers, solvents and energetic materials[electronic resource] /Polymers, solvents and energetic materialsedited by Kunal Roy, Arkaprava Banerjee. - Cham :Springer Nature Switzerland :2025. - xv, 371 p. :ill. (some col.), digital ;24 cm. - Challenges and advances in computational chemistry and physics,v. 412542-4483 ;. - Challenges and advances in computational chemistry and physics ;v. 41..

Part 1. Introduction -- Introduction to Machine Learning for Predictive Modeling II -- Introduction to predicting properties of organic materials -- Part 2. Cheminformatic and Machine Learning Models for Polymers -- Machine Learning Applications in Polymer Informatics - An Overview -- Applications of predictive modeling for selected properties of polymers -- Polymer Property Prediction using Machine Learning -- Applications of predictive modeling for polymers -- Part 3. Cheminformatic and Machine Learning Models for Solvents -- Applications of predictive QSPR modeling for deep eutectic solvents -- Applications of predictive modeling for various properties of ionic liquids -- Part 4. Cheminformatic and Machine Learning Models for Energetic Materials -- Improving Safety with Molecular-Scale Computational Approaches for Energetic and Reactive Materials -- Predictive modeling for energetic materials -- Modeling the performance of energetic materials -- Applications of predictive modeling for energetic materials.

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.

ISBN: 9783031787249

Standard No.: 10.1007/978-3-031-78724-9doiSubjects--Topical Terms:

755339
Materials
--Data processing.

LC Class. No.: TA404.23

Dewey Class. No.: 620.110285

Materials informatics.. III,. Polymers, solvents and energetic materials
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