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.
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Mohsen Khodadadi Yazdi is an experienced chemical/polymer engineer who received his BSc degree (chemical engineering) from the Ferdowsi University of Mashhad, Iran, followed by a MSc (2010) from the Sharif University of Technology, Tehran, Iran. He received his PhD (2017) in polymer engineering from the University of Tehran, Iran. He is currently a Senior Researcher at the Center of Excellence in Electrochemistry, University of Tehran, Iran. His research interests include smart hydrogel/biopolymers, carbon-based nanomaterial, conducting polymers, and machine learning for utilization in biomedical applications. He has contributed to >20 scientific papers and book chapters.
Payam Zarrintaj is Principal Scientist in the Biomedical and Pharmaceutical Science Department at the University of Montana, Montana, United States. He is an experienced polymer engineer; he received his BSc degree from Amirkabir University of Technology, Iran, followed by a MSc (2013) and PhD (2018) from Tehran University, Iran. His research interests include smart hydrogel/polymers and nanoparticles with well-controlled microstructures and properties for biomedical applications. He has contributed to >90 scientific papers and book chapters.
Dr. Mohammad Reza Saeb received his PhD in 2008 from Amirkabir University of Technology (Iran) and is currently a Professor at the Department of Pharmaceutical Chemistry, Medical University of Gdańsk (Poland). His research focuses on advanced materials and manufacturing processes, including polymer blends, composites, and nanocomposites, with particular emphasis on biomaterials and flame-retardant polymers, as well as the recycling and upcycling of polymer and biowastes. He has authored or co-authored more than 500 articles in high-impact journals and is currently serving as the Editor-in-Chief of Polymers from Renewable Resources, published by SAGE.
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Condición: New. Introduces the reader to core concepts in AI and machine learning in the context of biomaterials, as well as providing practical examples to aid understandingThoroughly reviews the role of AI and machine learning in the synthesis, character. Nº de ref. del artículo: 2072726286
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Taschenbuch. Condición: Neu. Neuware - 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. Nº de ref. del artículo: 9780323954648
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