Download or read book Artificial Intelligence for Materials Science written by Yuan Cheng and published by Springer Nature. This book was released on 2021-03-26 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Artificial Intelligence Aided Materials Design written by Rajesh Jha and published by CRC Press. This book was released on 2022-03-15 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Artificial Intelligence Applications in Materials Science written by Ralph J. Harrison and published by . This book was released on 1987 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Materials Discovery and Design written by Turab Lookman and published by Springer. This book was released on 2018-09-22 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the current status, challenges and future directions of data-driven materials discovery and design. It presents the analysis and learning from data as a key theme in many science and cyber related applications. The challenging open questions as well as future directions in the application of data science to materials problems are sketched. Computational and experimental facilities today generate vast amounts of data at an unprecedented rate. The book gives guidance to discover new knowledge that enables materials innovation to address grand challenges in energy, environment and security, the clearer link needed between the data from these facilities and the theory and underlying science. The role of inference and optimization methods in distilling the data and constraining predictions using insights and results from theory is key to achieving the desired goals of real time analysis and feedback. Thus, the importance of this book lies in emphasizing that the full value of knowledge driven discovery using data can only be realized by integrating statistical and information sciences with materials science, which is increasingly dependent on high throughput and large scale computational and experimental data gathering efforts. This is especially the case as we enter a new era of big data in materials science with the planning of future experimental facilities such as the Linac Coherent Light Source at Stanford (LCLS-II), the European X-ray Free Electron Laser (EXFEL) and MaRIE (Matter Radiation in Extremes), the signature concept facility from Los Alamos National Laboratory. These facilities are expected to generate hundreds of terabytes to several petabytes of in situ spatially and temporally resolved data per sample. The questions that then arise include how we can learn from the data to accelerate the processing and analysis of reconstructed microstructure, rapidly map spatially resolved properties from high throughput data, devise diagnostics for pattern detection, and guide experiments towards desired targeted properties. The authors are an interdisciplinary group of leading experts who bring the excitement of the nascent and rapidly emerging field of materials informatics to the reader.

Download or read book AI in Material Science written by Syed Saad and published by CRC Press. This book was released on 2024-07-26 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Machine Learning in 2D Materials Science written by Parvathi Chundi and published by CRC Press. This book was released on 2023-11-13 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Handbook of Materials Modeling written by Sidney Yip and published by Springer Science & Business Media. This book was released on 2007-11-17 with total page 2903 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first reference of its kind in the rapidly emerging field of computational approachs to materials research, this is a compendium of perspective-providing and topical articles written to inform students and non-specialists of the current status and capabilities of modelling and simulation. From the standpoint of methodology, the development follows a multiscale approach with emphasis on electronic-structure, atomistic, and mesoscale methods, as well as mathematical analysis and rate processes. Basic models are treated across traditional disciplines, not only in the discussion of methods but also in chapters on crystal defects, microstructure, fluids, polymers and soft matter. Written by authors who are actively participating in the current development, this collection of 150 articles has the breadth and depth to be a major contributor toward defining the field of computational materials. In addition, there are 40 commentaries by highly respected researchers, presenting various views that should interest the future generations of the community. Subject Editors: Martin Bazant, MIT; Bruce Boghosian, Tufts University; Richard Catlow, Royal Institution; Long-Qing Chen, Pennsylvania State University; William Curtin, Brown University; Tomas Diaz de la Rubia, Lawrence Livermore National Laboratory; Nicolas Hadjiconstantinou, MIT; Mark F. Horstemeyer, Mississippi State University; Efthimios Kaxiras, Harvard University; L. Mahadevan, Harvard University; Dimitrios Maroudas, University of Massachusetts; Nicola Marzari, MIT; Horia Metiu, University of California Santa Barbara; Gregory C. Rutledge, MIT; David J. Srolovitz, Princeton University; Bernhardt L. Trout, MIT; Dieter Wolf, Argonne National Laboratory.

Download or read book Computational Technologies in Materials Science written by Shubham Tayal and published by CRC Press. This book was released on 2021-10-06 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: • Covers material testing and development using computational intelligence • Highlights the technologies to integrate computational intelligence and materials sciences • Discusses how computational tools can generate new materials with advanced applications • Details case studies and detailed applications • Investigates challenges in developing and using computational intelligence in materials science • Analyzes historic changes that are taking place in designing of materials

Download or read book AI in Material Science written by Syed Saad and published by . This book was released on 2024 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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"--

Download or read book The Materials Science of Semiconductors written by Angus Rockett and published by Springer Science & Business Media. This book was released on 2007-11-20 with total page 629 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes semiconductors from a materials science perspective rather than from condensed matter physics or electrical engineering viewpoints. It includes discussion of current approaches to organic materials for electronic devices. It further describes the fundamental aspects of thin film nucleation and growth, and the most common physical and chemical vapor deposition techniques. Examples of the application of the concepts in each chapter to specific problems or situations are included, along with recommended readings and homework problems.

Download or read book Materials Science and Engineering Concepts Methodologies Tools and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2017-01-11 with total page 1837 pages. Available in PDF, EPUB and Kindle. Book excerpt: The design and study of materials is a pivotal component to new discoveries in the various fields of science and technology. By better understanding the components and structures of materials, researchers can increase its applications across different industries. Materials Science and Engineering: Concepts, Methodologies, Tools, and Applications is a compendium of the latest academic material on investigations, technologies, and techniques pertaining to analyzing the synthesis and design of new materials. Through its broad and extensive coverage on a variety of crucial topics, such as nanomaterials, biomaterials, and relevant computational methods, this multi-volume work is an essential reference source for engineers, academics, researchers, students, professionals, and practitioners seeking innovative perspectives in the field of materials science and engineering.

Download or read book Nanoinformatics written by Isao Tanaka and published by Springer. This book was released on 2018-01-15 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book brings out the state of the art on how informatics-based tools are used and expected to be used in nanomaterials research. There has been great progress in the area in which “big-data” generated by experiments or computations are fully utilized to accelerate discovery of new materials, key factors, and design rules. Data-intensive approaches play indispensable roles in advanced materials characterization. "Materials informatics" is the central paradigm in the new trend. "Nanoinformatics" is its essential subset, which focuses on nanostructures of materials such as surfaces, interfaces, dopants, and point defects, playing a critical role in determining materials properties. There have been significant advances in experimental and computational techniques to characterize individual atoms in nanostructures and to gain quantitative information. The collaboration of researchers in materials science and information science is growing actively and is creating a new trend in materials science and engineering.

Download or read book Human Centered AI written by Ben Shneiderman and published by Oxford University Press. This book was released on 2022 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: The remarkable progress in algorithms for machine and deep learning have opened the doors to new opportunities, and some dark possibilities. However, a bright future awaits those who build on their working methods by including HCAI strategies of design and testing. As many technology companies and thought leaders have argued, the goal is not to replace people, but to empower them by making design choices that give humans control over technology. In Human-Centered AI, Professor Ben Shneiderman offers an optimistic realist's guide to how artificial intelligence can be used to augment and enhance humans' lives. This project bridges the gap between ethical considerations and practical realities to offer a road map for successful, reliable systems. Digital cameras, communications services, and navigation apps are just the beginning. Shneiderman shows how future applications will support health and wellness, improve education, accelerate business, and connect people in reliable, safe, and trustworthy ways that respect human values, rights, justice, and dignity.

Download or read book Artificial Intelligence in Healthcare written by Adam Bohr and published by Academic Press. This book was released on 2020-06-21 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data

Download or read book Tech Trends in Practice written by Bernard Marr and published by John Wiley & Sons. This book was released on 2020-04-09 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: ***BUSINESS BOOK AWARDS - FINALIST 2021*** Discover how 25 powerful technology trends are transforming 21st century businesses How will the latest technologies transform your business? Future Tech Trends in Practice will give you the knowledge of today’s most important technology trends, and how to take full advantage of them to grow your business. The book presents25 real-world technology trends along with their potential contributions to organisational success. You’ll learn how to integrate existing advancements and plan for those that are on the way. In this book, best-selling author, strategic business advisor, and respected futurist Bernard Marr explains the role of technology in providing innovative businesses solutions for companies of varying sizes and across different industries. He covers wide-ranging trends and provides an overview of how companies are using these new and emerging technologies in practice. You, too, can prepare your company for the potential and power of trending technology by examining these and other areas of innovation described in Future Tech Trends in Practice: Artificial intelligence, including machine and deep learning The Internet of Things and the rise of smart devices Self-driving cars and autonomous drones 3D printing and additive manufacturing Blockchain technology Genomics and gene editing Augmented, virtual and mixed reality When you understand the technology trends that are driving success, now and into the future, you’ll be better positioned to address and solve problems within your organisation.

Download or read book Combinatorial and Artificial Intelligence Methods in Materials Science II written by Radislav A. Potyrailo and published by Cambridge University Press. This book was released on 2014-06-05 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past two years, combinatorial and artificial intelligence methods in materials science have become more accepted as a means to synthesize, test, characterize, and predict promising candidate materials. These methods open up the exploration of multidimensional chemical composition and process parameter space at a previously unavailable level of detail and can rapidly optimize molecular properties and process conditions that are difficult to predict using existing knowledge. Scientists from academic, industrial and governmental laboratories worldwide come together here with interdisciplinary presentations that: identify gaps in cross-discipline knowledge that hinder further research; outline emerging development areas; and stimulate nontraditional solutions to difficult multidisciplinary problems in high-throughput materials research. Topics include: combinatorial approaches to electronics materials, polymers and coatings, and nanomaterials and catalysts; instrumentation and methods for high-throughput analysis; and library design, data management and informatics. In particular, the book demonstrates that combinatorial methods have matured in catalyst research. Several remarkable scale-up reports are presented signifying the power of this new scientific methodology.

Download or read book The Economics of Artificial Intelligence written by Ajay Agrawal and published by University of Chicago Press. This book was released on 2024-03-05 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.