Roy K. Materials Informatics II. Software Tools and Databases 2025 torrent

Textbook in PDF format

This contributed volume explores the application of machine learning in predictive modeling within the fields of materials science, nanotechnology, and cheminformatics. It covers a range of topics, including electronic properties of metal nanoclusters, carbon quantum dots, toxicity assessments of nanomaterials, and predictive modeling for fullerenes and perovskite materials. Additionally, the book discusses multiscale modeling and advanced decision support systems for nanomaterial risk management, while also highlighting various machine learning tools, databases, and web platforms designed to predict the properties of materials and molecules. It is a comprehensive guide and a great tool for researchers working at the intersection of machine learning and material sciences.
Introduction
Introduction to Machine Learning for Predictive Modeling I
Introduction to Machine Learning for Materials Property Modeling
Cheminformatic and Machine Learning Models for Nanomaterials
Machine Learning Models to Study Electronic Properties of Metal Nanoclusters
Applications of Machine Learning Predictive Modeling for Carbon Quantum Dots
Assessing the Toxicity of Quantum Dots in Healthy and Tumoral Cells with ProtoNANO, a Platform of Nano-QSAR Models to Predict the Toxicity of Inorganic Nanomaterials
Applications of Predictive Modeling for Fullerenes
Computational Analysis of Perovskite Materials AlXY3 (X = Cu, Mn; Y = Br, Cl, F) Invoking the DFT Method
Applications of Predictive Modeling for Dye-Sensitized Solar Cells (DSSCs)
Introduction to Multiscale Modeling for One Health Approaches
DIAGONAL Decision Support System (DSS) for Advanced Nanomaterial Risk Management Powered by Enalos Cloud Platform
Software Tools and Databases for Applications in Materials Science
Machine Learning Algorithms, Tools, and Databases for Applications in Materials Science
Machine Learning-Driven Web Tools for Predicting Properties of Materials and Molecules