Artificial Intelligence In Computational Materials Science
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Artificial Intelligence In Computational Materials Science
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Author : Amodini Mishra
language : en
Publisher:
Release Date : 2025-06-20
Artificial Intelligence In Computational Materials Science written by Amodini Mishra and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-20 with Computers categories.
This book presents an overview of how AI is transforming materials science to meet the challenges of everyday life and across various technological domains. The author delves into various AI techniques such as machine learning, deep learning, and data-driven approaches, showcasing their application in materials discovery, characterization, and property prediction. As a reference, the book provides researchers and academicians established, state-of-the-science insights into the integration of AI with computational methods like molecular dynamics simulations, density functional theory calculations, and multiscale modelling, enhancing accuracy and efficiency in material research. In addition, the book highlights the successful applications of AI in optimizing material performance, accelerating materials development cycles, and enabling novel discoveries in the fields ranging from energy to environment materials. Artificial Intelligence in Computational Materials Science: Methods and Applications serves as a vital resource for researchers, engineers, and students interested in harnessing the potential of AI's for the advancement of materials science, innovating across industries, and addressing complex scientific challenges.
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.
Artificial Intelligence In Material Science
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Author : Mohamed Arezki Mellal
language : en
Publisher: CRC Press
Release Date : 2024-12-11
Artificial Intelligence In Material Science written by Mohamed Arezki Mellal and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-11 with Technology & Engineering categories.
Artificial intelligence (AI) in the form of machine learning and nature-inspired optimization algorithms are vastly used in material science. These techniques improve many quality metrics, such as reliability and ergonomics. This book highlights the recent challenges in this field and helps readers to understand the subject and develop future works. It reviews the latest methods and applications of AI in material science. It covers a wide range of topics, including Material processing; Properties prediction; Conventional machining, such as turning, boring, grinding, and milling; non-conventional machining, such as electrical discharge machining, electrochemical machining, laser machining, plasma machining, ultrasonic machining, chemical machining, and water-jet machining; Machine tools, such as programming, design, and maintenance. AI techniques reviewed in the book include Machine learning, Fuzzy logic, Genetic algorithms, Particle swarm optimization, Cuckoo search, Grey wolf optimizer, and Ant colony optimization.
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.
Machine Learning In 2d Materials Science
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Author : Parvathi Chundi
language : en
Publisher: CRC Press
Release Date : 2023-11-13
Machine Learning In 2d Materials Science written by Parvathi Chundi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-13 with Computers categories.
Data science and machine learning (ML) methods are increasingly being used to transform the way research is being conducted in materials science to enable new discoveries and design new materials. For any materials science researcher or student, it may be daunting to figure out if ML techniques are useful for them or, if so, which ones are applicable in their individual contexts, and how to study the effectiveness of these methods systematically. KEY FEATURES Provides broad coverage of data science and ML fundamentals to materials science researchers so that they can confidently leverage these techniques in their research projects Offers introductory material in topics such as ML, data integration, and 2D materials Provides in-depth coverage of current ML methods for validating 2D materials using both experimental and simulation data, researching and discovering new 2D materials, and enhancing ML methods with physical properties of materials Discusses customized ML methods for 2D materials data and applications and high-throughput data acquisition Describes several case studies illustrating how ML approaches are currently leading innovations in the discovery, development, manufacturing, and deployment of 2D materials needed for strengthening industrial products Gives future trends in ML for 2D materials, explainable AI, and dealing with extremely large and small, diverse datasets Aimed at materials science researchers, this book allows readers to quickly, yet thoroughly, learn the ML and AI concepts needed to ascertain the applicability of ML methods in their research.
Machine Learning And Data Mining In Materials Science
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Author : Norbert Huber
language : en
Publisher: Frontiers Media SA
Release Date : 2020-04-22
Machine Learning And Data Mining In Materials Science written by Norbert Huber and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-22 with categories.
Pattern Recognition
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Author : Huimin Lu
language : en
Publisher: Springer Nature
Release Date : 2023-11-04
Pattern Recognition written by Huimin Lu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-04 with Computers categories.
This three-volume set LNCS 14406-14408 constitutes the refereed proceedings of the 7th Asian Conference on Pattern Recognition, ACPR 2023, held in Kitakyushu, Japan, in November 2023. The 93 full papers presented were carefully reviewed and selected from 164 submissions. The conference focuses on four important areas of pattern recognition: pattern recognition and machine learning, computer vision and robot vision, signal processing, and media processing and interaction, covering various technical aspects.
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.
Artificial Intelligence For Science A Deep Learning Revolution
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Author : Alok Choudhary
language : en
Publisher: World Scientific
Release Date : 2023-03-21
Artificial Intelligence For Science A Deep Learning Revolution written by Alok Choudhary and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-21 with Computers categories.
This unique collection introduces AI, Machine Learning (ML), and deep neural network technologies leading to scientific discovery from the datasets generated both by supercomputer simulation and by modern experimental facilities.Huge quantities of experimental data come from many sources — telescopes, satellites, gene sequencers, accelerators, and electron microscopes, including international facilities such as the Large Hadron Collider (LHC) at CERN in Geneva and the ITER Tokamak in France. These sources generate many petabytes moving to exabytes of data per year. Extracting scientific insights from these data is a major challenge for scientists, for whom the latest AI developments will be essential.The timely handbook benefits professionals, researchers, academics, and students in all fields of science and engineering as well as AI, ML, and neural networks. Further, the vision evident in this book inspires all those who influence or are influenced by scientific progress.
Evolving Landscapes Of Research And Development Trends Challenges And Opportunities
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Author : Datta, Dhananjoy
language : en
Publisher: IGI Global
Release Date : 2025-02-05
Evolving Landscapes Of Research And Development Trends Challenges And Opportunities written by Datta, Dhananjoy and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-05 with Business & Economics categories.
The landscape of research and development is undergoing transformations driven by rapid technological advancements, evolving global challenges, and shifting market demands. As industries and academic institutions adapt to these changes, new trends emerge that shape the direction of innovation, from interdisciplinary collaborations and open-source platforms to the integration of artificial intelligence and big data analytics. However, alongside these opportunities come significant challenges, including funding constraints, ethical considerations, and the need for effective knowledge management. Further exploration into the challenges faced by researchers and organizations may help provide better solutions to navigate complexities and harness research and developments full potential for social progress. Evolving Landscapes of Research and Development: Trends, Challenges, and Opportunities explores research and development, delving into its foundations, emerging technologies, collaborative approaches, and social impact. It addresses the evolving landscape of research and development, discussing the importance of sustainability and ethical considerations, highlighting future perspectives and challenges, and offering guidance on funding and resource management. This book covers topics such as green technology, research methods, and knowledge management, and is a useful resource for academicians, researchers, business owners, engineers, sociologists, and scientists.