Artificial Intelligence For Materials Science

Author : Yuan Cheng,Tian Wang,Gang Zhang
Publisher : Springer Nature
Page : 231 pages
File Size : 40,6 Mb
Release : 2021-03-26
Category : Technology & Engineering
ISBN : 9783030683108

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Artificial Intelligence for Materials Science by Yuan Cheng,Tian Wang,Gang Zhang Pdf

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.

Author : Rajesh Jha,Bimal Kumar Jha
Publisher : CRC Press
Page : 362 pages
File Size : 46,8 Mb
Release : 2022-03-16
Category : Technology & Engineering
ISBN : 9781000541335

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Artificial Intelligence-Aided Materials Design by Rajesh Jha,Bimal Kumar Jha Pdf

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.

Author : Ralph J. Harrison,Lewis D. Roth
Publisher : Unknown
Page : 226 pages
File Size : 50,7 Mb
Release : 1987
Category : Computers
ISBN : STANFORD:36105030032358

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Artificial Intelligence Applications in Materials Science by Ralph J. Harrison,Lewis D. Roth Pdf

Author : Abby L. Parrill,Kenny B. Lipkowitz
Publisher : John Wiley & Sons
Page : 480 pages
File Size : 41,6 Mb
Release : 2016-03-09
Category : Science
ISBN : 9781119157564

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Reviews in Computational Chemistry by Abby L. Parrill,Kenny B. Lipkowitz Pdf

The Reviews in Computational Chemistry series brings together leading authorities in the field to teach the newcomer and update the expert on topics centered on molecular modeling, such as computer-assisted molecular design (CAMD), quantum chemistry, molecular mechanics and dynamics, and quantitative structure-activity relationships (QSAR). This volume, like those prior to it, features chapters by experts in various fields of computational chemistry. Topics in Volume 29 include: Noncovalent Interactions in Density-Functional Theory Long-Range Inter-Particle Interactions: Insights from Molecular Quantum Electrodynamics (QED) Theory Efficient Transition-State Modeling using Molecular Mechanics Force Fields for the Everyday Chemist Machine Learning in Materials Science: Recent Progress and Emerging Applications Discovering New Materials via a priori Crystal Structure Prediction Introduction to Maximally Localized Wannier Functions Methods for a Rapid and Automated Description of Proteins: Protein Structure, Protein Similarity, and Protein Folding

Author : Parvathi Chundi,Venkataramana Gadhamshetty,Bharat K. Jasthi,Carol Lushbough
Publisher : CRC Press
Page : 249 pages
File Size : 50,8 Mb
Release : 2023-11-13
Category : Technology & Engineering
ISBN : 9781000987430

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Machine Learning in 2D Materials Science by Parvathi Chundi,Venkataramana Gadhamshetty,Bharat K. Jasthi,Carol Lushbough Pdf

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.

Author : Isao Tanaka
Publisher : Springer
Page : 298 pages
File Size : 44,5 Mb
Release : 2018-01-15
Category : Technology & Engineering
ISBN : 9789811076176

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Nanoinformatics by Isao Tanaka Pdf

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.

Author : Turab Lookman,Stephan Eidenbenz,Frank Alexander,Cris Barnes
Publisher : Springer
Page : 256 pages
File Size : 44,5 Mb
Release : 2018-09-22
Category : Science
ISBN : 9783319994659

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Materials Discovery and Design by Turab Lookman,Stephan Eidenbenz,Frank Alexander,Cris Barnes Pdf

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.

Author : Yoshiki Oshida
Publisher : Walter de Gruyter GmbH & Co KG
Page : 520 pages
File Size : 47,8 Mb
Release : 2021-10-11
Category : Technology & Engineering
ISBN : 9783110717853

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Artificial Intelligence for Medicine by Yoshiki Oshida Pdf

The use of artificial intelligence (AI) in various fields is of major importance to improve the use of resourses and time. This book provides an analysis of how AI is used in both the medical field and beyond. Topics that will be covered are bioinformatics, biostatistics, dentistry, diagnosis and prognosis, smart materials, and drug discovery as they intersect with AI. Also, an outlook of the future of an AI-assisted society will be explored.

Author : Mohsen Asadnia,Amir Razmjou,Amin Beheshti
Publisher : Academic Press
Page : 326 pages
File Size : 42,9 Mb
Release : 2022-02-09
Category : Computers
ISBN : 9780323905077

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Artificial Intelligence and Data Science in Environmental Sensing by Mohsen Asadnia,Amir Razmjou,Amin Beheshti Pdf

Artificial Intelligence and Data Science in Environmental Sensing provides state-of-the-art information on the inexpensive mass-produced sensors that are used as inputs to artificial intelligence systems. The book discusses the advances of AI and Machine Learning technologies in material design for environmental areas. It is an excellent resource for researchers and professionals who work in the field of data processing, artificial intelligence sensors and environmental applications. Presents tools, connections and proactive solutions to take sustainability programs to the next level Offers a practical guide for making students proficient in modern electronic data analysis and graphics Provides knowledge and background to develop specific platforms related to environmental sensing, including control water, air and soil quality, water and wastewater treatment, desalination, pollution mitigation/control, and resource management and recovery

Author : Aboul Ella Hassanien,Jyotir Moy Chatterjee,Vishal Jain
Publisher : Academic Press
Page : 264 pages
File Size : 42,5 Mb
Release : 2022-08-14
Category : Technology & Engineering
ISBN : 9780323906395

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Artificial Intelligence and Industry 4.0 by Aboul Ella Hassanien,Jyotir Moy Chatterjee,Vishal Jain Pdf

Artificial Intelligence and Industry 4.0 explores recent advancements in blockchain technology and artificial intelligence (AI) as well as their crucial impacts on realizing Industry 4.0 goals. The book explores AI applications in industry including Internet of Things (IoT) and Industrial Internet of Things (IIoT) technology. Chapters explore how AI (machine learning, smart cities, healthcare, Society 5.0, etc.) have numerous potential applications in the Industry 4.0 era. This book is a useful resource for researchers and graduate students in computer science researching and developing AI and the IIoT. Explores artificial intelligence applications within the industrial manufacturing and communications sectors Presents a wide range of machine learning, computer vision, and digital twin applications across the IoT sector Explores how deep learning and cognitive computing tools enable processing vast data sets, precise and comprehensive forecast of risks, and delivering recommended actions

Author : Sidney Yip
Publisher : Springer Science & Business Media
Page : 2903 pages
File Size : 55,8 Mb
Release : 2007-11-17
Category : Science
ISBN : 9781402032868

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Handbook of Materials Modeling by Sidney Yip Pdf

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.

Author : Yuebing Zheng,Zilong Wu
Publisher : Elsevier
Page : 444 pages
File Size : 44,9 Mb
Release : 2022-10-26
Category : Technology & Engineering
ISBN : 9780323901413

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Intelligent Nanotechnology by Yuebing Zheng,Zilong Wu Pdf

Intelligent Nanotechnology: Merging Nanoscience and Artificial Intelligence provides an overview of advances in science and technology made possible by the convergence of nanotechnology and artificial intelligence (AI). Sections focus on AI-enhanced design, characterization and manufacturing and the use of AI to improve important material properties, with an emphasis on mechanical, photonic, electronic and magnetic properties. Designing benign nanomaterials through the prediction of their impact on biology and the environment is also discussed. Other sections cover the use of AI in the acquisition and analysis of data in experiments and AI technologies that have been enhanced through nanotechnology platforms. Final sections review advances in applications enabled by the merging of nanotechnology and artificial intelligence, including examples from biomedicine, chemistry and automated research. Includes recent advances on AI-enhanced design, characterization and the manufacturing of nanomaterials Reviews AI technologies that have been enabled by nanotechnology Discusses potentially world-changing applications that could ensue as a result of merging these two fields

Author : Salunkhe, Sachin,Hussein, Hussein Mohammed Abdel Moneam,Davim, J. Paulo
Publisher : IGI Global
Page : 240 pages
File Size : 48,8 Mb
Release : 2021-12-31
Category : Technology & Engineering
ISBN : 9781799885184

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Applications of Artificial Intelligence in Additive Manufacturing by Salunkhe, Sachin,Hussein, Hussein Mohammed Abdel Moneam,Davim, J. Paulo Pdf

After the recent launch of home-based personal 3D printers as well as government funding and company investments in advancing manufacturing initiatives, additive manufacturing has rapidly come to the forefront of discussion and become a more approachable lucrative career of particular interest to the younger generation. It is essential to identify the long-term competitive advantages and how to teach, inspire, and create a resolute community of supporters, learners, and new leaders in this important industry progression. Applications of Artificial Intelligence in Additive Manufacturing provides instruction on how to use artificial intelligence to produce additively manufactured parts. It discusses an overview of the field, the strategic blending of artificial intelligence and additive manufacturing, and features case studies on the various emerging technologies. Covering topics such as artificial intelligence models, experimental investigations, and online detections, this book is an essential resource for engineers, manufacturing professionals, computer scientists, AI scientists, researchers, educators, academicians, and students.

Author : K. Shankar,Eswaran Perumal,Deepak Gupta
Publisher : CRC Press
Page : 216 pages
File Size : 40,6 Mb
Release : 2021-05-10
Category : Computers
ISBN : 9781000374292

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Artificial Intelligence for the Internet of Health Things by K. Shankar,Eswaran Perumal,Deepak Gupta Pdf

This book discusses research in Artificial Intelligence for the Internet of Health Things. It investigates and explores the possible applications of machine learning, deep learning, soft computing, and evolutionary computing techniques in design, implementation, and optimization of challenging healthcare solutions. This book features a wide range of topics such as AI techniques, IoT, cloud, wearables, and secured data transmission. Written for a broad audience, this book will be useful for clinicians, health professionals, engineers, technology developers, IT consultants, researchers, and students interested in the AI-based healthcare applications. Provides a deeper understanding of key AI algorithms and their use and implementation within the wider healthcare sector Explores different disease diagnosis models using machine learning, deep learning, healthcare data analysis, including machine learning, and data mining and soft computing algorithms Discusses detailed IoT, wearables, and cloud-based disease diagnosis model for intelligent systems and healthcare Reviews different applications and challenges across the design, implementation, and management of intelligent systems and healthcare data networks Introduces a new applications and case studies across all areas of AI in healthcare data K. Shankar (Member, IEEE) is a Postdoctoral Fellow of the Department of Computer Applications, Alagappa University, Karaikudi, India. Eswaran Perumal is an Assistant Professor of the Department of Computer Applications, Alagappa University, Karaikudi, India. Dr. Deepak Gupta is an Assistant Professor of the Department Computer Science & Engineering, Maharaja Agrasen Institute of Technology (GGSIPU), Delhi, India.

Author : Joern Helbert,Mario D'Amore,Michael Aye,Hannah Kerner
Publisher : Elsevier
Page : 234 pages
File Size : 44,7 Mb
Release : 2022-03-22
Category : Science
ISBN : 9780128187227

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Machine Learning for Planetary Science by Joern Helbert,Mario D'Amore,Michael Aye,Hannah Kerner Pdf

Machine Learning for Planetary Science presents planetary scientists with a way to introduce machine learning into the research workflow as increasingly large nonlinear datasets are acquired from planetary exploration missions. The book explores research that leverages machine learning methods to enhance our scientific understanding of planetary data and serves as a guide for selecting the right methods and tools for solving a variety of everyday problems in planetary science using machine learning. Illustrating ways to employ machine learning in practice with case studies, the book is clearly organized into four parts to provide thorough context and easy navigation. The book covers a range of issues, from data analysis on the ground to data analysis onboard a spacecraft, and from prioritization of novel or interesting observations to enhanced missions planning. This book is therefore a key resource for planetary scientists working in data analysis, missions planning, and scientific observation. Includes links to a code repository for sharing codes and examples, some of which include executable Jupyter notebook files that can serve as tutorials Presents methods applicable to everyday problems faced by planetary scientists and sufficient for analyzing large datasets Serves as a guide for selecting the right method and tools for applying machine learning to particular analysis problems Utilizes case studies to illustrate how machine learning methods can be employed in practice