Artificial Intelligence Driven Materials Design
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Artificial Intelligence Driven Materials Design
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Author : Piyush Tagade
language : en
Publisher: Springer
Release Date : 2024-10-01
Artificial Intelligence Driven Materials Design written by Piyush Tagade and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-01 with Science categories.
This book presents the application of machine learning and deep learning to Materials Design. Traditional materials design relies on a trial and error based iterative approach towards attaining target material properties often interspersed with accidental discoveries. This approach is very time consuming as both processing/fabrication, characterization of new compositions/structures are quite laborious. The field of machine learning and deep learning can greatly benefit expediting this approach by narrowing down the search space and reducing the number of compounds/structures that are explored in the lab. This book covers the fundamentals of how one goes about applying Artificial Intelligence to materials design followed by specific examples. The book contains 4 sections. In the first section, fundamentals of AI, materials structure representation/digitization and theoretical framework are discussed. In the second section, materials optimization using evolutionary algorithms is discussed. In the third section, application of AI for forward prediction, i.e., given a material structure, how to predict properties, is considered. In the fourth section, we cover inverse prediction or inverse materials design, that is, predicting materials/structures with target properties. The inverse design of materials is an emerging field of materials design and the techniques we present are very novel. We provide examples from both organic and inorganic materials space with diverse fields of applications. The book includes sample codes for these example problems to help readers gain hands-on experience.
Artificial Intelligence Aided Materials Design
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Author : Rajesh Jha
language : en
Publisher: CRC Press
Release Date : 2022-03-15
Artificial Intelligence Aided Materials Design written by Rajesh Jha and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-15 with Technology & Engineering categories.
This book describes the application of artificial intelligence (AI)/machine learning (ML) concepts to develop predictive models that can be used to design alloy materials, including hard and soft magnetic alloys, nickel-base superalloys, titanium-base alloys, and aluminum-base alloys. Readers new to AI/ML algorithms can use this book as a starting point and use the MATLAB® and Python implementation of AI/ML algorithms through included case studies. Experienced AI/ML researchers who want to try new algorithms can use this book and study the case studies for reference. Offers advantages and limitations of several AI concepts and their proper implementation in various data types generated through experiments and computer simulations and from industries in different file formats Helps readers to develop predictive models through AI/ML algorithms by writing their own computer code or using resources where they do not have to write code Covers downloadable resources such as MATLAB GUI/APP and Python implementation that can be used on common mobile devices Discusses the CALPHAD approach and ways to use data generated from it Features a chapter on metallurgical/materials concepts to help readers understand the case studies and thus proper implementation of AI/ML algorithms under the framework of data-driven materials science Uses case studies to examine the importance of using unsupervised machine learning algorithms in determining patterns in datasets This book is written for materials scientists and metallurgists interested in the application of AI, ML, and data science in the development of new materials.
Ai Material Design
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Author : Kai Turing
language : en
Publisher: Publifye AS
Release Date : 2025-03-04
Ai Material Design written by Kai Turing and has been published by Publifye AS this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-04 with Technology & Engineering categories.
""AI Material Design"" explores how artificial intelligence is revolutionizing materials science, speeding up the discovery of materials with specific properties. One intriguing aspect is using AI to predict material properties like strength or conductivity, potentially cutting down on traditional trial-and-error methods. The book also highlights AI's role in optimizing material synthesis and processing, leading to efficient production of high-quality materials. The book uniquely positions AI as more than just a tool; instead, it demonstrates how AI is essential for designing and discovering materials with unprecedented functionalities. Beginning with machine learning principles, the approach progresses to detailing how AI algorithms predict material properties and optimize synthesis techniques. Real-world case studies illustrate the effectiveness of AI in overcoming materials design challenges, making it valuable for researchers and industry professionals alike.
Artificial Intelligence For Materials Informatics
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Author : S. Sachin Kumar
language : en
Publisher: Springer Nature
Release Date : 2025-07-29
Artificial Intelligence For Materials Informatics written by S. Sachin Kumar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-29 with Computers categories.
This comprehensive book explores the transformative impact of AI on materials informatics, delving into machine learning/deep learning, and material knowledge representation. Embracing the transformative power of artificial intelligence (AI), the field of materials informatics has witnessed a remarkable revolution in its methodology and applications. AI has revolutionized the field of materials informatics, enabling researchers to discover, design, and optimize materials with enhanced properties at an accelerated pace. It showcases how AI is accelerating materials discovery, property prediction, providing case studies, and a comprehensive bibliography for further exploration. This essential resource equips researchers, scientists, and engineers with the knowledge and tools to harness the power of AI for groundbreaking advancements in materials science.
Ai In Material Science
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Author : Syed Saad
language : en
Publisher: CRC Press
Release Date : 2024-07-26
Ai In Material Science written by Syed Saad and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-26 with Technology & Engineering categories.
This book explores the transformative impact of artificial intelligence on material science and construction practices in the Industry 4.0 landscape. It enquires into AI history and applications, examining material optimization, smart materials, and AI in construction. Covering automation, robotics, and AI-assisted design, the book provides insights into ethical considerations and future trends. A modern reference for scholars and professionals, it bridges academia and practical applications in the dynamic intersection of AI and materials science.
Artificial Intelligence Driven Models For Environmental Management
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Author : Shrikaant Kulkarni
language : en
Publisher: John Wiley & Sons
Release Date : 2025-08-19
Artificial Intelligence Driven Models For Environmental Management written by Shrikaant Kulkarni and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-19 with Science categories.
Step-by-step guidelines for the development of artificial neural network-based environmental pollution models Artificial Intelligence-Driven Models for Environmental Management delves into the application of AI across a plethora of areas in environmental management, including climate forecasting, natural resource optimization, waste management, and biodiversity conservation. This book shows how AI can help in monitoring, predicting, and mitigating environmental impacts with tremendous accuracy and speed by leveraging machine learning, deep learning, and other data-driven models. The methodologies explored in this volume reflect a synthesis of computational intelligence, data science, and ecological expertise, underscoring how AI-driven systems have been making strides in managing and preserving our planet's natural resources. The text is structured to guide readers through numerous AI models and their practical environmental management applications, showcasing theoretical foundations as well as case studies. This book also addresses the challenges and ethical considerations related to deploying AI in ecological contexts, underscoring the importance of transparency, inclusivity, and alignment with sustainability goals. Sample topics discussed in Artificial Intelligence-Driven Models for Environmental Management include: Tools and methods for monitoring and predicting environmental pollutants faster and more accurately AI technology for the protection of water supplies from contamination to produce healthier foods Use of AI for the evaluation of the impacts of environmental pollution on human health AI and waste management technologies for sustainable agriculture and soil management The role of AI in environmental research and sustainability and key social and economic aspects of natural resource management through AI Artificial Intelligence-Driven Models for Environmental Management is a timely, forward-thinking resource for a diverse readership, including researchers, policymakers, environmental scientists, and AI practitioners.
Proceedings Of The Rilem Spring Convention And Conference 2024
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Author : Liberato Ferrara
language : en
Publisher: Springer Nature
Release Date : 2024-11-06
Proceedings Of The Rilem Spring Convention And Conference 2024 written by Liberato Ferrara and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-06 with Technology & Engineering categories.
This book gathers peer-reviewed contributions presented at the RILEM Spring Convention and Conference, held in Milan, Italy on April 7-12, 2024. The theme of the Conference was “Advanced construction materials and processes for a carbon neutral society”, which was aimed at discussing advanced construction/eco-friendly materials and processes, for new and existing structures, towards a carbon neutral society. The volume covers the current and emerging approaches that lead to an optimized design and maintenance of constructions and systems. It includes the development of materials and structural service life models and life cycle design, in order to maximise longevity and level of service while minimising the environmental impact of constructions and systems. It also includes the analysis and design of larger systems, such as communities, cities or regions, aiming at reducing risk andincreasing resilience. The following subtopics are included: advanced materials and structural concept to enhance the resilience and robustness of the built environment and communities at local and global scales; risk based inspection and maintenance; life cycle analysis and service models; performance based design; improved design strategies by integrating materials and structures.
Artificial Intelligence For Materials Science
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Author : Yuan Cheng
language : en
Publisher: Springer Nature
Release Date : 2021-03-26
Artificial Intelligence For Materials Science written by Yuan Cheng and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-26 with Technology & Engineering categories.
Machine learning methods have lowered the cost of exploring new structures of unknown compounds, and can be used to predict reasonable expectations and subsequently validated by experimental results. As new insights and several elaborative tools have been developed for materials science and engineering in recent years, it is an appropriate time to present a book covering recent progress in this field. Searchable and interactive databases can promote research on emerging materials. Recently, databases containing a large number of high-quality materials properties for new advanced materials discovery have been developed. These approaches are set to make a significant impact on human life and, with numerous commercial developments emerging, will become a major academic topic in the coming years. This authoritative and comprehensive book will be of interest to both existing researchers in this field as well as others in the materials science community who wish to take advantage of these powerful techniques. The book offers a global spread of authors, from USA, Canada, UK, Japan, France, Russia, China and Singapore, who are all world recognized experts in their separate areas. With content relevant to both academic and commercial points of view, and offering an accessible overview of recent progress and potential future directions, the book will interest graduate students, postgraduate researchers, and consultants and industrial engineers.
Nanorevolution
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Author : Abderrahman Abbassi
language : en
Publisher: CRC Press
Release Date : 2025-06-16
Nanorevolution written by Abderrahman Abbassi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-16 with Technology & Engineering categories.
As the global push toward energy accelerates, NanoRevolution: Unveiling the Future of Energy through Advanced Materials and Digital Technologies brings forward a powerful vision of how advanced materials and digital technologies are redefining energy solutions. This comprehensive resource navigates the frontiers of nanotechnology, artificial intelligence (AI), and IoT applications within the renewable energy sector, presenting innovative strategies that address today’s most pressing energy challenges. Across 15 chapters, NanoRevolution covers transformative advancements in photovoltaic and energy storage technologies. It explores the application of density functional theory (DFT) in developing high-efficiency, lead-free solar cells, new methodologies for enhancing MXenes-based materials, and emerging AI-powered solutions for energy optimization and predictive maintenance. The book also examines IoT-driven innovations in photovoltaic systems and provides a high-level overview of blockchain's potential in secure energy transactions. This book is an invaluable guide for researchers, engineers, and industry professionals focused on next-generation energy solutions, offering both theoretical depth and practical applications to drive progress toward a sustainable energy future.
Material Science Breakthroughs
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Author : Aiden Feynman
language : en
Publisher: Publifye AS
Release Date : 2025-03-04
Material Science Breakthroughs written by Aiden Feynman and has been published by Publifye AS this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-04 with Science categories.
Material Science Breakthroughs explores the atomic-level innovations transforming our world through advanced materials. It highlights how manipulating matter at its most fundamental levelâleveraging nanotechnology and computational modelingâis leading to unprecedented technological advancements in energy storage, advanced transportation, and quantum communication. For example, strategically designed materials are not merely incremental improvements, but fundamental catalysts for technological revolutions that help overcome previously insurmountable limitations. The book begins with the foundational principles of material science before delving into specific applications. It examines advanced battery technologies and next-generation solar cells for energy, lightweight composites and high-strength alloys for transportation, and quantum materials for secure communication. Readers will appreciate how these material innovations, supported by peer-reviewed research and expert insights, are paving the way for a more efficient and sustainable future. This book distinguishes itself by emphasizing the design principles driving innovation rather than simply cataloging existing materials. It adopts a forward-looking perspective, highlighting the integration of artificial intelligence and machine learning in material design. By connecting chemistry, engineering, and environmental science, Material Science Breakthroughs provides a comprehensive view of the transformative potential and ethical considerations surrounding the ongoing material revolution.