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Full Description
Artificial Intelligence in Biomaterials Design and Development delves into the transformative role of artificial intelligence, particularly machine learning, in creating new biomaterials. Traditional challenges in this field, such as chemical waste, spatial constraints, and inadequate tools, have hindered the swift design and synthesis of versatile biomaterials. Machine learning methods address these barriers by enhancing discovery and development processes, reducing time, costs, and wastage. Generative models now enable the creation of novel molecular structures with desired properties, making inverse materials design a reality. This book is essential for those in materials science, machine learning, and biomedical engineering.
Additionally, this comprehensive resource explores the application of AI in various aspects of biomaterials science, from computational engineering to data science. The book provides insights into how novel machine learning models can expedite materials discovery and improve accuracy. It is an invaluable guide for academics and industry professionals alike, seeking to leverage AI for innovative biomaterials research and development.
Contents
1. Introduction to artificial intelligence, machine learning, and deep learning
2. Useful tools and datasets for materials science and engineering
3. Artificial neural networks
4. From human genome to materials genome
5. Biomaterials properties-prediction based on discriminative models
6. de novo materials design based on generative models
7. AI-assisted synthesis planning and optimization of biomaterials
8. AI-assisted characterization of biomaterials
9. AI-assisted evaluation of biomaterials
10. AI and biomaterials in drug and vaccine development
11. AI and biomaterials in protein engineering
12. AI in biopolymer design/discovery/engineering
13. AI in designing/discovery of other biomaterials
14. AI-assisted biomaterials structures at scales
15. AI-assisted materials/scientific discoveries: Beyond pure machine learning
16. State-of-the-art and future perspectives on ML-assisted biomaterials design/discovery
