Artificial Intelligence In Material Science

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Artificial Intelligence Applications In Materials Science

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Author : Ralph J. Harrison
language : en
Publisher:
Release Date : 1987

Artificial Intelligence Applications In Materials Science written by Ralph J. Harrison and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1987 with Computers categories.

Artificial Intelligence For Materials Science

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Author : Yuan Cheng
language : en
Publisher:
Release Date : 2021

Artificial Intelligence For Materials Science written by Yuan Cheng and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Electronic books 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.

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 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.

Application Of Artificial Intelligence In New Materials Discovery

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Author : Inamuddin
language : en
Publisher: Materials Research Forum LLC
Release Date : 2023-07-05

Application Of Artificial Intelligence In New Materials Discovery written by Inamuddin and has been published by Materials Research Forum LLC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-05 with Technology & Engineering categories.

The book is concerned with the use of Artificial Intelligence in the discovery, production and application of new engineering materials. Topics covered include nano-robots. data mining, solar energy systems, materials genomics, polymer manufacturing, and energy conversion issues. Keywords: Artificial Intelligence, Mathematical Models, Machine Learning, Artificial Neural Networks, Bayesian Analysis, Vector Machines, Heuristics, Crystal Structure, Component Prediction, Process Optimization, Density Functional Theory, Monitoring, Classification, Nano-Robots, Data Mining, Solar Photovoltaics, Renewable Energy Systems, Alternative Energy Sources, Material Genomics, Polymer Manufacturing, Energy Conversion.

Ai In Material Science

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Author : Syed Saad
language : en
Publisher:
Release Date : 2024

Ai In Material Science written by Syed Saad and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024 with Architecture categories.

"AI in Material Science: Revolutionizing Construction in the Age of Industry 4.0 is a comprehensive guide for professionals and researchers in the fields of artificial intelligence, material science, and construction. The book explores the latest research and developments in the field of AI-assisted material science, and its use to revolutionize the construction industry in the age of Industry 4.0. The book provides real-world examples and case studies of AI-assisted material science in the construction sector, giving readers practical and actionable insights. It covers a wide range of applications of AI in material science, from design and modeling to fabrication and construction, making it a valuable resource for professionals in the field. The book also focuses on how artificial intelligence in material science can help drive the construction industry towards Industry 4.0, making it an important resource for professionals looking to stay ahead of the curve in this rapidly advancing field"--

Machine Learning For Materials Discovery

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Author : N. M. Anoop Krishnan
language : en
Publisher: Springer Nature
Release Date : 2024-05-06

Machine Learning For Materials Discovery written by N. M. Anoop Krishnan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-06 with Technology & Engineering categories.

Focusing on the fundamentals of machine learning, this book covers broad areas of data-driven modeling, ranging from simple regression to advanced machine learning and optimization methods for applications in materials modeling and discovery. The book explains complex mathematical concepts in a lucid manner to ensure that readers from different materials domains are able to use these techniques successfully. A unique feature of this book is its hands-on aspect—each method presented herein is accompanied by a code that implements the method in open-source platforms such as Python. This book is thus aimed at graduate students, researchers, and engineers to enable the use of data-driven methods for understanding and accelerating the discovery of novel materials.

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.

Materials Data Science

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Author : Stefan Sandfeld
language : en
Publisher: Springer Nature
Release Date : 2024-05-08

Materials Data Science written by Stefan Sandfeld and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-08 with Technology & Engineering categories.

This text covers all of the data science, machine learning, and deep learning topics relevant to materials science and engineering, accompanied by numerous examples and applications. Almost all methods and algorithms introduced are implemented “from scratch” using Python and NumPy. The book starts with an introduction to statistics and probabilities, explaining important concepts such as random variables and probability distributions, Bayes’ theorem and correlations, sampling techniques, and exploratory data analysis, and puts them in the context of materials science and engineering. Therefore, it serves as a valuable primer for both undergraduate and graduate students, as well as a review for research scientists and practicing engineers. The second part provides an in-depth introduction of (statistical) machine learning. It begins with outlining fundamental concepts and proceeds to explore a variety of supervised learning techniques for regression and classification, including advanced methods such as kernel regression and support vector machines. The section on unsupervised learning emphasizes principal component analysis, and also covers manifold learning (t-SNE and UMAP) and clustering techniques. Additionally, feature engineering, feature importance, and cross-validation are introduced. The final part on neural networks and deep learning aims to promote an understanding of these methods and dispel misconceptions that they are a “black box”. The complexity gradually increases until fully connected networks can be implemented. Advanced techniques and network architectures, including GANs, are implemented “from scratch” using Python and NumPy, which facilitates a comprehensive understanding of all the details and enables the user to conduct their own experiments in Deep Learning.

Advances In Sustainable Materials

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Author : Ajay Kumar
language : en
Publisher: Elsevier
Release Date : 2024-11-05

Advances In Sustainable Materials written by Ajay Kumar and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-05 with Technology & Engineering categories.

Advances in Sustainable Materials: Fundamentals, Modelling and Characterization provides a comprehensive review of recent technological developments and research accomplishments in this important field.The chapters cover characterization techniques, modeling of sustainable materials, the role of artificial intelligence, Industry 4.0, nature-inspired algorithms, and optimization possibilities. Various computational and simulation approaches for maintaining the sustainability of materials are also covered in detail. In addition to the above, various case studies are also included on the application of sustainable materials in medical, environmental, production, mechanical, and civil engineering.This collection of state-of-the-art techniques, with an emphasis on using various analytical strategies, and computational and simulation approaches, as well as artificial intelligence will encourage researchers, as well as manufacturers to develop more innovative sustainable materials. - Covers various types of sustainable materials, including polymers, metals, ceramics, composites, biomaterials, biodegradable materials, smart materials, and functionallygraded materials - Focuses on characterization, modeling, and applications of sustainable materials - Describes the outstanding properties of various classes of materials and their suitability for different types of industrial applications