Application Of Artificial Intelligence In New Materials Discovery

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Application of Artificial Intelligence in New Materials Discovery

Author : Inamuddin
Publisher : Materials Research Forum LLC
ISBN 13 : 1644902524
Total Pages : 147 pages
Book Rating : 4.6/5 (449 download)

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Book Synopsis Application of Artificial Intelligence in New Materials Discovery by : Inamuddin

Download or read book Application of Artificial Intelligence in New Materials Discovery written by Inamuddin and published by Materials Research Forum LLC. This book was released on 2023-07-05 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Materials Discovery and Design

Author : Turab Lookman
Publisher : Springer
ISBN 13 : 3319994654
Total Pages : 256 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Materials Discovery and Design by : Turab Lookman

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 256 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.

Accelerated Materials Discovery

Author : Phil De Luna
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110733250
Total Pages : 235 pages
Book Rating : 4.1/5 (17 download)

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Book Synopsis Accelerated Materials Discovery by : Phil De Luna

Download or read book Accelerated Materials Discovery written by Phil De Luna and published by Walter de Gruyter GmbH & Co KG. This book was released on 2022-02-21 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: Typical timelines to go from discovery to impact in the advanced materials sector are between 10 to 30 years. Advances in robotics and artificial intelligence are poised to accelerate the discovery and development of new materials dramatically. This book is a primer for any materials scientist looking to future-proof their careers and get ahead of the disruption that artificial intelligence and robotic automation is just starting to unleash. It is meant to be an overview of how we can use these disruptive technologies to augment and supercharge our abilities to discover new materials that will solve world’s biggest challenges. Written by world leading experts on accelerated materials discovery from academia (UC Berkeley, Caltech, UBC, Cornell, etc.), industry (Toyota Research Institute, Citrine Informatics) and national labs (National Research Council of Canada, Lawrence Berkeley National Labs).

Application of Artificial Intelligence in New Materials Discovery

Author : Inamuddin
Publisher : Materials Research Forum LLC
ISBN 13 : 1644902532
Total Pages : 147 pages
Book Rating : 4.6/5 (449 download)

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Book Synopsis Application of Artificial Intelligence in New Materials Discovery by : Inamuddin

Artificial Intelligence for Materials Science

Author : Yuan Cheng
Publisher : Springer Nature
ISBN 13 : 3030683109
Total Pages : 231 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Artificial Intelligence for Materials Science by : Yuan Cheng

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.

Machine Learning for Materials Discovery

Author : N. M. Anoop Krishnan
Publisher : Springer Nature
ISBN 13 : 3031446224
Total Pages : 287 pages
Book Rating : 4.0/5 (314 download)

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Book Synopsis Machine Learning for Materials Discovery by : N. M. Anoop Krishnan

Download or read book Machine Learning for Materials Discovery written by N. M. Anoop Krishnan and published by Springer Nature. This book was released on with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Artificial Intelligence-Aided Materials Design

Author : Rajesh Jha
Publisher : CRC Press
ISBN 13 : 1000541339
Total Pages : 363 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Artificial Intelligence-Aided Materials Design by : Rajesh Jha

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.

Accelerated Materials Discovery

Author : Phil De Luna
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110738082
Total Pages : 215 pages
Book Rating : 4.1/5 (17 download)

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Book Synopsis Accelerated Materials Discovery by : Phil De Luna

Download or read book Accelerated Materials Discovery written by Phil De Luna and published by Walter de Gruyter GmbH & Co KG. This book was released on 2022-02-21 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: Typical timelines to go from discovery to impact in the advanced materials sector are between 10 to 30 years. Advances in robotics and artificial intelligence are poised to accelerate the discovery and development of new materials dramatically. This book is a primer for any materials scientist looking to future-proof their careers and get ahead of the disruption that artificial intelligence and robotic automation is just starting to unleash. It is meant to be an overview of how we can use these disruptive technologies to augment and supercharge our abilities to discover new materials that will solve world’s biggest challenges. Written by world leading experts on accelerated materials discovery from academia (UC Berkeley, Caltech, UBC, Cornell, etc.), industry (Toyota Research Institute, Citrine Informatics) and national labs (National Research Council of Canada, Lawrence Berkeley National Labs).

Materials Informatics

Author : Olexandr Isayev
Publisher : John Wiley & Sons
ISBN 13 : 3527341218
Total Pages : 304 pages
Book Rating : 4.5/5 (273 download)

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Book Synopsis Materials Informatics by : Olexandr Isayev

Download or read book Materials Informatics written by Olexandr Isayev and published by John Wiley & Sons. This book was released on 2019-12-04 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides everything readers need to know for applying the power of informatics to materials science There is a tremendous interest in materials informatics and application of data mining to materials science. This book is a one-stop guide to the latest advances in these emerging fields. Bridging the gap between materials science and informatics, it introduces readers to up-to-date data mining and machine learning methods. It also provides an overview of state-of-the-art software and tools. Case studies illustrate the power of materials informatics in guiding the experimental discovery of new materials. Materials Informatics: Methods, Tools and Applications is presented in two parts?Methodological Aspects of Materials Informatics and Practical Aspects and Applications. The first part focuses on developments in software, databases, and high-throughput computational activities. Chapter topics include open quantum materials databases; the ICSD database; open crystallography databases; and more. The second addresses the latest developments in data mining and machine learning for materials science. Its chapters cover genetic algorithms and crystal structure prediction; MQSPR modeling in materials informatics; prediction of materials properties; amongst others. -Bridges the gap between materials science and informatics -Covers all the known methodologies and applications of materials informatics -Presents case studies that illustrate the power of materials informatics in guiding the experimental quest for new materials -Examines the state-of-the-art software and tools being used today Materials Informatics: Methods, Tools and Applications is a must-have resource for materials scientists, chemists, and engineers interested in the methods of materials informatics.

Artificial Intelligence Applications in Materials Science

Author : Ralph J. Harrison
Publisher :
ISBN 13 :
Total Pages : 226 pages
Book Rating : 4.F/5 ( download)

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Book Synopsis Artificial Intelligence Applications in Materials Science by : Ralph J. Harrison

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:

Neuromorphic Photonics

Author : Paul R. Prucnal
Publisher : CRC Press
ISBN 13 : 1498725244
Total Pages : 412 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Neuromorphic Photonics by : Paul R. Prucnal

Download or read book Neuromorphic Photonics written by Paul R. Prucnal and published by CRC Press. This book was released on 2017-05-08 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book sets out to build bridges between the domains of photonic device physics and neural networks, providing a comprehensive overview of the emerging field of "neuromorphic photonics." It includes a thorough discussion of evolution of neuromorphic photonics from the advent of fiber-optic neurons to today’s state-of-the-art integrated laser neurons, which are a current focus of international research. Neuromorphic Photonics explores candidate interconnection architectures and devices for integrated neuromorphic networks, along with key functionality such as learning. It is written at a level accessible to graduate students, while also intending to serve as a comprehensive reference for experts in the field.

Information Science for Materials Discovery and Design

Author : Turab Lookman
Publisher : Springer
ISBN 13 : 331923871X
Total Pages : 307 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Information Science for Materials Discovery and Design by : Turab Lookman

Download or read book Information Science for Materials Discovery and Design written by Turab Lookman and published by Springer. This book was released on 2015-12-12 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with an information-driven approach to plan materials discovery and design, iterative learning. The authors present contrasting but complementary approaches, such as those based on high throughput calculations, combinatorial experiments or data driven discovery, together with machine-learning methods. Similarly, statistical methods successfully applied in other fields, such as biosciences, are presented. The content spans from materials science to information science to reflect the cross-disciplinary nature of the field. A perspective is presented that offers a paradigm (codesign loop for materials design) to involve iteratively learning from experiments and calculations to develop materials with optimum properties. Such a loop requires the elements of incorporating domain materials knowledge, a database of descriptors (the genes), a surrogate or statistical model developed to predict a given property with uncertainties, performing adaptive experimental design to guide the next experiment or calculation and aspects of high throughput calculations as well as experiments. The book is about manufacturing with the aim to halving the time to discover and design new materials. Accelerating discovery relies on using large databases, computation, and mathematics in the material sciences in a manner similar to the way used to in the Human Genome Initiative. Novel approaches are therefore called to explore the enormous phase space presented by complex materials and processes. To achieve the desired performance gains, a predictive capability is needed to guide experiments and computations in the most fruitful directions by reducing not successful trials. Despite advances in computation and experimental techniques, generating vast arrays of data; without a clear way of linkage to models, the full value of data driven discovery cannot be realized. Hence, along with experimental, theoretical and computational materials science, we need to add a “fourth leg’’ to our toolkit to make the “Materials Genome'' a reality, the science of Materials Informatics.

Real World AI

Author : Alyssa Simpson Rochwerger
Publisher : Lioncrest Publishing
ISBN 13 : 9781544518831
Total Pages : 222 pages
Book Rating : 4.5/5 (188 download)

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Book Synopsis Real World AI by : Alyssa Simpson Rochwerger

Download or read book Real World AI written by Alyssa Simpson Rochwerger and published by Lioncrest Publishing. This book was released on 2021-03-16 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can you successfully deploy AI? When AI works, it's nothing short of brilliant, helping companies make or save tremendous amounts of money while delighting customers on an unprecedented scale. When it fails, the results can be devastating. Most AI models never make it out of testing, but those failures aren't random. This practical guide to deploying AI lays out a human-first, responsible approach that has seen more than three times the success rate when compared to the industry average. In Real World AI, Alyssa Simpson Rochwerger and Wilson Pang share dozens of AI stories from startups and global enterprises alike featuring personal experiences from people who have worked on global AI deployments that impact billions of people every day. AI for business doesn't have to be overwhelming. Real World AI uses plain language to walk you through an AI approach that you can feel confident about-for your business and for your customers.

Handbook of Materials Modeling

Author : Sidney Yip
Publisher : Springer Science & Business Media
ISBN 13 : 1402032862
Total Pages : 2903 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Handbook of Materials Modeling by : Sidney Yip

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.

Machine Learning in Chemistry

Author : Hugh M Cartwright
Publisher : Royal Society of Chemistry
ISBN 13 : 1839160241
Total Pages : 564 pages
Book Rating : 4.8/5 (391 download)

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Book Synopsis Machine Learning in Chemistry by : Hugh M Cartwright

Download or read book Machine Learning in Chemistry written by Hugh M Cartwright and published by Royal Society of Chemistry. This book was released on 2020-07-15 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: Progress in the application of machine learning (ML) to the physical and life sciences has been rapid. A decade ago, the method was mainly of interest to those in computer science departments, but more recently ML tools have been developed that show significant potential across wide areas of science. There is a growing consensus that ML software, and related areas of artificial intelligence, may, in due course, become as fundamental to scientific research as computers themselves. Yet a perception remains that ML is obscure or esoteric, that only computer scientists can really understand it, and that few meaningful applications in scientific research exist. This book challenges that view. With contributions from leading research groups, it presents in-depth examples to illustrate how ML can be applied to real chemical problems. Through these examples, the reader can both gain a feel for what ML can and cannot (so far) achieve, and also identify characteristics that might make a problem in physical science amenable to a ML approach. This text is a valuable resource for scientists who are intrigued by the power of machine learning and want to learn more about how it can be applied in their own field.

AI-Guided Design and Property Prediction for Zeolites and Nanoporous Materials

Author : German Sastre
Publisher : John Wiley & Sons
ISBN 13 : 1119819776
Total Pages : 468 pages
Book Rating : 4.1/5 (198 download)

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Book Synopsis AI-Guided Design and Property Prediction for Zeolites and Nanoporous Materials by : German Sastre

Download or read book AI-Guided Design and Property Prediction for Zeolites and Nanoporous Materials written by German Sastre and published by John Wiley & Sons. This book was released on 2023-01-25 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: AI-Guided Design and Property Prediction for Zeolites and Nanoporous Materials A cohesive and insightful compilation of resources explaining the latest discoveries and methods in the field of nanoporous materials In Artificial Intelligence for Zeolites and Nanoporous Materials: Design, Synthesis and Properties Prediction a team of distinguished researchers delivers a robust compilation of the latest knowledge and most recent developments in computational chemistry, synthetic chemistry, and artificial intelligence as it applies to zeolites, porous molecular materials, covalent organic frameworks and metal-organic frameworks. The book presents a common language that unifies these fields of research and advances the discovery of new nanoporous materials. The editors have included resources that describe strategies to synthesize new nanoporous materials, construct databases of materials, structure directing agents, and synthesis conditions, and explain computational methods to generate new materials. They also offer material that discusses AI and machine learning algorithms, as well as other, similar approaches to the field. Readers will also find a comprehensive approach to artificial intelligence applied to and written in the language of materials chemistry, guiding the reader through the fundamental questions on how far computer algorithms and numerical representations can drive our search of new nanoporous materials for specific applications. Designed for academic researchers and industry professionals with an interest in synthetic nanoporous materials chemistry, Artificial Intelligence for Zeolites and Nanoporous Materials: Design, Synthesis and Properties Prediction will also earn a place in the libraries of professionals working in large energy, chemical, and biochemical companies with responsibilities related to the design of new nanoporous materials.

Machine Learning in 2D Materials Science

Author : Parvathi Chundi
Publisher : CRC Press
ISBN 13 : 1000987434
Total Pages : 249 pages
Book Rating : 4.0/5 (9 download)

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Book Synopsis Machine Learning in 2D Materials Science by : Parvathi Chundi

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.