| computational materials science impact factor: Artificial Intelligence for Materials Science Yuan Cheng, Tian Wang, Gang Zhang, 2021-03-26 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. |
| computational materials science impact factor: Computational Materials Science: Theory and Applications Lily Chen, 2018-02-19 Computational materials science is a fast growing field. It involves computational tools for solving problems related to materials science. Different mathematical models are used for developing a better understanding of material structures and properties. Most research done in this field focuses on the behavior of materials at varied levels. This book on computational materials science is a collective contribution of a renowned group of international experts. It aims to serve as a resource guide for students and experts alike and contribute to the growth of the discipline. |
| computational materials science impact factor: International Journal of Surface Engineering and Interdisciplinary Materials Science (IJSEIMS). J. Paulo Davim, 2015 |
| computational materials science impact factor: Computational Electronics Dragica Vasileska, Stephen M. Goodnick, Gerhard Klimeck, 2017-12-19 Starting with the simplest semiclassical approaches and ending with the description of complex fully quantum-mechanical methods for quantum transport analysis of state-of-the-art devices, Computational Electronics: Semiclassical and Quantum Device Modeling and Simulation provides a comprehensive overview of the essential techniques and methods for effectively analyzing transport in semiconductor devices. With the transistor reaching its limits and new device designs and paradigms of operation being explored, this timely resource delivers the simulation methods needed to properly model state-of-the-art nanoscale devices. The first part examines semiclassical transport methods, including drift-diffusion, hydrodynamic, and Monte Carlo methods for solving the Boltzmann transport equation. Details regarding numerical implementation and sample codes are provided as templates for sophisticated simulation software. The second part introduces the density gradient method, quantum hydrodynamics, and the concept of effective potentials used to account for quantum-mechanical space quantization effects in particle-based simulators. Highlighting the need for quantum transport approaches, it describes various quantum effects that appear in current and future devices being mass-produced or fabricated as a proof of concept. In this context, it introduces the concept of effective potential used to approximately include quantum-mechanical space-quantization effects within the semiclassical particle-based device simulation scheme. Addressing the practical aspects of computational electronics, this authoritative resource concludes by addressing some of the open questions related to quantum transport not covered in most books. Complete with self-study problems and numerous examples throughout, this book supplies readers with the practical understanding required to create their own simulators. |
| computational materials science impact factor: Electronic Structure Richard M. Martin, 2004-04-08 An important graduate textbook in condensed matter physics by highly regarded physicist. |
| computational materials science impact factor: Integrated Computational Materials Engineering National Research Council, Division on Engineering and Physical Sciences, National Materials Advisory Board, Committee on Integrated Computational Materials Engineering, 2008-10-24 Integrated computational materials engineering (ICME) is an emerging discipline that can accelerate materials development and unify design and manufacturing. Developing ICME is a grand challenge that could provide significant economic benefit. To help develop a strategy for development of this new technology area, DOE and DoD asked the NRC to explore its benefits and promises, including the benefits of a comprehensive ICME capability; to establish a strategy for development and maintenance of an ICME infrastructure, and to make recommendations about how best to meet these opportunities. This book provides a vision for ICME, a review of case studies and lessons learned, an analysis of technological barriers, and an evaluation of ways to overcome cultural and organizational challenges to develop the discipline. |
| computational materials science impact factor: Parallel Algorithms in Computational Science and Engineering Ananth Grama, Ahmed H. Sameh, 2020-07-06 This contributed volume highlights two areas of fundamental interest in high-performance computing: core algorithms for important kernels and computationally demanding applications. The first few chapters explore algorithms, numerical techniques, and their parallel formulations for a variety of kernels that arise in applications. The rest of the volume focuses on state-of-the-art applications from diverse domains. By structuring the volume around these two areas, it presents a comprehensive view of the application landscape for high-performance computing, while also enabling readers to develop new applications using the kernels. Readers will learn how to choose the most suitable parallel algorithms for any given application, ensuring that theory and practicality are clearly connected. Applications using these techniques are illustrated in detail, including: Computational materials science and engineering Computational cardiovascular analysis Multiscale analysis of wind turbines and turbomachinery Weather forecasting Machine learning techniques Parallel Algorithms in Computational Science and Engineering will be an ideal reference for applied mathematicians, engineers, computer scientists, and other researchers who utilize high-performance computing in their work. |
| computational materials science impact factor: Introduction to Materials Science and Engineering Yip-wah Chung, Monica Kapoor, 2022 Updated to reflect the many societal and technological changes in the field since publication of the first edition, Introduction to Materials Science and Engineering, Second Edition offers an interdisciplinary view, emphasizing the importance of materials to engineering applications, and builds the basis needed to select, modify, and create materials to meet specific criteria. Written for advanced undergraduate students and readers interested in introductory materials science and engineering concepts, this concise textbook provides a strong foundation in MSE and its applications. The textbook offers a solutions manual and PowerPoint lecture slides for adopting professors-- |
| computational materials science impact factor: Electronic Materials Yuriy M. Poplavko, 2018-11-23 Mechanical and thermal properties are reviewed and electrical and magnetic properties are emphasized. Basics of symmetry and internal structure of crystals and the main properties of metals, dielectrics, semiconductors, and magnetic materials are discussed. The theory and modern experimental data are presented, as well as the specifications of materials that are necessary for practical application in electronics. The modern state of research in nanophysics of metals, magnetic materials, dielectrics and semiconductors is taken into account, with particular attention to the influence of structure on the physical properties of nano-materials. The book uses simplified mathematical treatment of theories, while emphasis is placed on the basic concepts of physical phenomena in electronic materials. Most chapters are devoted to the advanced scientific and technological problems of electronic materials; in addition, some new insights into theoretical facts relevant to technical devices are presented. Electronic Materials is an essential reference for newcomers to the field of electronics, providing a fundamental understanding of important basic and advanced concepts in electronic materials science. Provides important overview of the fundamentals of electronic materials properties significant for device applications along with advanced and applied concepts essential to those working in the field of electronics Takes a simplified and mathematical approach to theories essential to the understanding of electronic materials and summarizes important takeaways at the end of each chapter Interweaves modern experimental data and research in topics such as nanophysics, nanomaterials and dielectrics |
| computational materials science impact factor: Computational Retinal Image Analysis Emanuele Trucco, Tom MacGillivray, Yanwu Xu, 2019-11-20 Computational Retinal Image Analysis: Tools, Applications and Perspectives gives an overview of contemporary retinal image analysis (RIA) in the context of healthcare informatics and artificial intelligence. Specifically, it provides a history of the field, the clinical motivation for RIA, technical foundations (image acquisition modalities, instruments), computational techniques for essential operations, lesion detection (e.g. optic disc in glaucoma, microaneurysms in diabetes) and validation, as well as insights into current investigations drawing from artificial intelligence and big data. This comprehensive reference is ideal for researchers and graduate students in retinal image analysis, computational ophthalmology, artificial intelligence, biomedical engineering, health informatics, and more. |
| computational materials science impact factor: Mesoscopic Dynamics of Fracture Hiroshi Kitagawa, Tomoyasu Jr. Aihara, Yoshiyuki Kawazoe, 2013-11-09 This book introduces recent theoretical developments concerning the dynamic behaviour of fracture. Readers learn how the recent development of molecular dynamics and other state-of-the-art methods can help to solve the important problem of fracture from the atomic level. |
| computational materials science impact factor: Multiscale Materials Modeling Siegfried Schmauder, 2016 |
| computational materials science impact factor: Engineered Living Materials Wil V. Srubar III, 2022-02-16 This book will serve as a primer for readers to understand recent advances, applications, and current challenges in the field of Engineered Living Materials. The chapters cover core science and engineering research areas, including (1) advances in synthetic biology and genetic programmability for Engineered Living Materials, (2) functional Engineered Living Material for application in energy, electronics, and construction, and (3) novel manufacturing approaches for Engineered Living Materials at multiple scales. The emerging field of Engineered Living Materials represents a significant paradigm shift in materials design and synthesis, in which living cells are used to impart biologically active functionalities to manmade materials. The result is a genetically programmable augmentation of non-living matter to exhibit unprecedented life-like (i.e., living) capabilities. At the intersection of synthetic biology and materials science, the field of Engineered Living Materials exhibits unprecedented promise and potential to alter the way we synthesize new materials and design medical devices, fabrics, robotics, commodity polymers, and construction materials. Materials with attributes of living systems can be engineered with an ability to respond to their environment and designed to self-repair in response to physical or other stresses or detect the presence of specific stimuli, such as light, heat, pressure, or hazardous chemical compounds. Although nascent, scientists and researchers in the field of Engineered Living Materials have made marked advances in demonstrating a potential to revolutionize a multitude of science and engineering disciplines. This volume will define the current state of the art of Engineered Living Materials, and highlight grand opportunities and challenges that abound at the nexus of synthetic biology and materials science and engineering. |
| computational materials science impact factor: Introduction to Computational Materials Science Richard LeSar, 2013-03-28 Emphasising essential methods and universal principles, this textbook provides everything students need to understand the basics of simulating materials behaviour. All the key topics are covered from electronic structure methods to microstructural evolution, appendices provide crucial background material, and a wealth of practical resources are available online to complete the teaching package. Modelling is examined at a broad range of scales, from the atomic to the mesoscale, providing students with a solid foundation for future study and research. Detailed, accessible explanations of the fundamental equations underpinning materials modelling are presented, including a full chapter summarising essential mathematical background. Extensive appendices, including essential background on classical and quantum mechanics, electrostatics, statistical thermodynamics and linear elasticity, provide the background necessary to fully engage with the fundamentals of computational modelling. Exercises, worked examples, computer codes and discussions of practical implementations methods are all provided online giving students the hands-on experience they need. |
| computational materials science impact factor: Integrated Computational Materials Engineering (ICME) for Metals Mark F. Horstemeyer, 2012-06-07 State-of-the-technology tools for designing, optimizing, and manufacturing new materials Integrated computational materials engineering (ICME) uses computational materials science tools within a holistic system in order to accelerate materials development, improve design optimization, and unify design and manufacturing. Increasingly, ICME is the preferred paradigm for design, development, and manufacturing of structural products. Written by one of the world's leading ICME experts, this text delivers a comprehensive, practical introduction to the field, guiding readers through multiscale materials processing modeling and simulation with easy-to-follow explanations and examples. Following an introductory chapter exploring the core concepts and the various disciplines that have contributed to the development of ICME, the text covers the following important topics with their associated length scale bridging methodologies: Macroscale continuum internal state variable plasticity and damage theory and multistage fatigue Mesoscale analysis: continuum theory methods with discrete features and methods Discrete dislocation dynamics simulations Atomistic modeling methods Electronics structures calculations Next, the author provides three chapters dedicated to detailed case studies, including From Atoms to Autos: A Redesign of a Cadillac Control Arm, that show how the principles and methods of ICME work in practice. The final chapter examines the future of ICME, forecasting the development of new materials and engineering structures with the help of a cyberinfrastructure that has been recently established. Integrated Computational Materials Engineering (ICME) for Metals is recommended for both students and professionals in engineering and materials science, providing them with new state-of-the-technology tools for selecting, designing, optimizing, and manufacturing new materials. Instructors who adopt this text for coursework can take advantage of PowerPoint lecture notes, a questions and solutions manual, and tutorials to guide students through the models and codes discussed in the text. |
| computational materials science impact factor: Computational Materials Science Wofram Hergert, Arthur Ernst, Markus Dane, 2014-01-15 |
| computational materials science impact factor: A Survey of Computational Physics Rubin Landau, José Páez, Cristian C. Bordeianu, 2011-10-30 Computational physics is a rapidly growing subfield of computational science, in large part because computers can solve previously intractable problems or simulate natural processes that do not have analytic solutions. The next step beyond Landau's First Course in Scientific Computing and a follow-up to Landau and Páez's Computational Physics, this text presents a broad survey of key topics in computational physics for advanced undergraduates and beginning graduate students, including new discussions of visualization tools, wavelet analysis, molecular dynamics, and computational fluid dynamics. By treating science, applied mathematics, and computer science together, the book reveals how this knowledge base can be applied to a wider range of real-world problems than computational physics texts normally address. Designed for a one- or two-semester course, A Survey of Computational Physics will also interest anyone who wants a reference on or practical experience in the basics of computational physics. Accessible to advanced undergraduates Real-world problem-solving approach Java codes and applets integrated with text Companion Web site includes videos of lectures |
| computational materials science impact factor: Computational Materials Science June Gunn Lee, 2016-11-25 This book covers the essentials of Computational Science and gives tools and techniques to solve materials science problems using molecular dynamics (MD) and first-principles methods. The new edition expands upon the density functional theory (DFT) and how the original DFT has advanced to a more accurate level by GGA+U and hybrid-functional methods. It offers 14 new worked examples in the LAMMPS, Quantum Espresso, VASP and MedeA-VASP programs, including computation of stress-strain behavior of Si-CNT composite, mean-squared displacement (MSD) of ZrO2-Y2O3, band structure and phonon spectra of silicon, and Mo-S battery system. It discusses methods once considered too expensive but that are now cost-effective. New examples also include various post-processed results using VESTA, VMD, VTST, and MedeA. |
| computational materials science impact factor: Proceedings of the 1st World Congress on Integrated Computational Materials Engineering (ICME) The Minerals, Metals & Materials Society (TMS), 2011-06-15 In its most advanced form, Integrated Computational Materials Engineering (ICME) holistically integrates manufacturing simulation, advanced materials models and component performance analysis. This volume contains thirty-five papers presented at the 1st World Congress on Integrated Computational Materials Engineering. Modeling processing-microstructure relationships, modeling microstructure-property relationships, and the role of ICME in graduate and undergraduate education are discussed. Ideal as a primary text for engineering students, this book motivates a wider understanding of the advantages and limitations offered by the various computational (and coordinated experimental) tools of this field. |
| computational materials science impact factor: The Fourth Industrial Revolution Klaus Schwab, 2017-01-03 World-renowned economist Klaus Schwab, Founder and Executive Chairman of the World Economic Forum, explains that we have an opportunity to shape the fourth industrial revolution, which will fundamentally alter how we live and work. Schwab argues that this revolution is different in scale, scope and complexity from any that have come before. Characterized by a range of new technologies that are fusing the physical, digital and biological worlds, the developments are affecting all disciplines, economies, industries and governments, and even challenging ideas about what it means to be human. Artificial intelligence is already all around us, from supercomputers, drones and virtual assistants to 3D printing, DNA sequencing, smart thermostats, wearable sensors and microchips smaller than a grain of sand. But this is just the beginning: nanomaterials 200 times stronger than steel and a million times thinner than a strand of hair and the first transplant of a 3D printed liver are already in development. Imagine “smart factories” in which global systems of manufacturing are coordinated virtually, or implantable mobile phones made of biosynthetic materials. The fourth industrial revolution, says Schwab, is more significant, and its ramifications more profound, than in any prior period of human history. He outlines the key technologies driving this revolution and discusses the major impacts expected on government, business, civil society and individuals. Schwab also offers bold ideas on how to harness these changes and shape a better future—one in which technology empowers people rather than replaces them; progress serves society rather than disrupts it; and in which innovators respect moral and ethical boundaries rather than cross them. We all have the opportunity to contribute to developing new frameworks that advance progress. |
| computational materials science impact factor: Recent Advances in Computational Mechanics Tomasz Lodygowski, Jerzy Rakowski, Przemyslaw Litewka, 2014-02-04 Recent Advances in Computational Mechanics contains selected papers presented at the jubilee 20th Conference on Computer Methods in Mechanics (CMM 2013), which took place from 27 to 31 August 2013 at the Poznan University of Technology. The first Polish Conference on Computer Methods in Mechanics was held in Poznan in 1973. This very successful me |
| computational materials science impact factor: The British Chess Magazine; Volume 16 Anonymous, 2022-10-27 This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant. |
| computational materials science impact factor: Mathematics and Computation Avi Wigderson, 2019-10-29 From the winner of the Turing Award and the Abel Prize, an introduction to computational complexity theory, its connections and interactions with mathematics, and its central role in the natural and social sciences, technology, and philosophy Mathematics and Computation provides a broad, conceptual overview of computational complexity theory—the mathematical study of efficient computation. With important practical applications to computer science and industry, computational complexity theory has evolved into a highly interdisciplinary field, with strong links to most mathematical areas and to a growing number of scientific endeavors. Avi Wigderson takes a sweeping survey of complexity theory, emphasizing the field’s insights and challenges. He explains the ideas and motivations leading to key models, notions, and results. In particular, he looks at algorithms and complexity, computations and proofs, randomness and interaction, quantum and arithmetic computation, and cryptography and learning, all as parts of a cohesive whole with numerous cross-influences. Wigderson illustrates the immense breadth of the field, its beauty and richness, and its diverse and growing interactions with other areas of mathematics. He ends with a comprehensive look at the theory of computation, its methodology and aspirations, and the unique and fundamental ways in which it has shaped and will further shape science, technology, and society. For further reading, an extensive bibliography is provided for all topics covered. Mathematics and Computation is useful for undergraduate and graduate students in mathematics, computer science, and related fields, as well as researchers and teachers in these fields. Many parts require little background, and serve as an invitation to newcomers seeking an introduction to the theory of computation. Comprehensive coverage of computational complexity theory, and beyond High-level, intuitive exposition, which brings conceptual clarity to this central and dynamic scientific discipline Historical accounts of the evolution and motivations of central concepts and models A broad view of the theory of computation's influence on science, technology, and society Extensive bibliography |
| computational materials science impact factor: Computational, Education, and Materials Science Aspects Ponnadurai Ramasami, 2022-10-03 Chapters collected from “The Virtual Conference on Chemistry and its Applications (VCCA-2021) – Research and Innovations in Chemical Sciences: Paving the Way Forward”. This conference was held in August 2021 and organized by the Computational Chemistry Group of the University of Mauritius. These peer-reviewed chapters offer insights into research on fundamental and applied chemistry with interdisciplinary subject matter. |
| computational materials science impact factor: Materials Discovery and Design Turab Lookman, Stephan Eidenbenz, Frank Alexander, Cris Barnes, 2018-09-22 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. |
| computational materials science impact factor: Computational Materials Science Feng Xiong, 2011-07-04 Selected, peer reviewed papers from the 2011 International Conference on Computational Materials Science (CMS 2011) in April 17-18, Guangzhou, China |
| computational materials science impact factor: Hands-On Mathematics for Deep Learning Jay Dawani, 2020-06-12 A comprehensive guide to getting well-versed with the mathematical techniques for building modern deep learning architectures Key FeaturesUnderstand linear algebra, calculus, gradient algorithms, and other concepts essential for training deep neural networksLearn the mathematical concepts needed to understand how deep learning models functionUse deep learning for solving problems related to vision, image, text, and sequence applicationsBook Description Most programmers and data scientists struggle with mathematics, having either overlooked or forgotten core mathematical concepts. This book uses Python libraries to help you understand the math required to build deep learning (DL) models. You'll begin by learning about core mathematical and modern computational techniques used to design and implement DL algorithms. This book will cover essential topics, such as linear algebra, eigenvalues and eigenvectors, the singular value decomposition concept, and gradient algorithms, to help you understand how to train deep neural networks. Later chapters focus on important neural networks, such as the linear neural network and multilayer perceptrons, with a primary focus on helping you learn how each model works. As you advance, you will delve into the math used for regularization, multi-layered DL, forward propagation, optimization, and backpropagation techniques to understand what it takes to build full-fledged DL models. Finally, you’ll explore CNN, recurrent neural network (RNN), and GAN models and their application. By the end of this book, you'll have built a strong foundation in neural networks and DL mathematical concepts, which will help you to confidently research and build custom models in DL. What you will learnUnderstand the key mathematical concepts for building neural network modelsDiscover core multivariable calculus conceptsImprove the performance of deep learning models using optimization techniquesCover optimization algorithms, from basic stochastic gradient descent (SGD) to the advanced Adam optimizerUnderstand computational graphs and their importance in DLExplore the backpropagation algorithm to reduce output errorCover DL algorithms such as convolutional neural networks (CNNs), sequence models, and generative adversarial networks (GANs)Who this book is for This book is for data scientists, machine learning developers, aspiring deep learning developers, or anyone who wants to understand the foundation of deep learning by learning the math behind it. Working knowledge of the Python programming language and machine learning basics is required. |
| computational materials science impact factor: Composite Materials Krishan K. Chawla, 2013-04-17 Focusing on the relationship between structure and properties, this is a well-balanced treatment of the mechanics and the materials science of composites, while not neglecting the importance of processing. This updated second edition contains new chapters on fatigue and creep of composites, and describes in detail how the various reinforcements, the materials in which they are embedded, and of the interfaces between them, control the properties of the composite materials at both the micro- and macro-levels. Extensive use is made of micrographs and line drawings, and examples of practical applications in various fields are given throughout the book, together with extensive references to the literature. Intended for use in graduate and upper-division undergraduate courses, this book will also prove a useful reference for practising engineers and researchers in industry and academia. |
| computational materials science impact factor: Issues in Computation: 2013 Edition , 2013-05-01 Issues in Computation / 2013 Edition is a ScholarlyEditions™ book that delivers timely, authoritative, and comprehensive information about Computing. The editors have built Issues in Computation: 2013 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Computing in this book to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in Computation / 2013 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/. |
| computational materials science impact factor: Advanced Healthcare Materials Ashutosh Tiwari, 2014-05-09 Offers a comprehensive and interdisciplinary view of cutting-edge research on advanced materials for healthcare technology and applications Advanced healthcare materials are attracting strong interest in fundamental as well as applied medical science and technology. This book summarizes the current state of knowledge in the field of advanced materials for functional therapeutics, point-of-care diagnostics, translational materials, and up-and-coming bioengineering devices. Advanced Healthcare Materials highlights the key features that enable the design of stimuli-responsive smart nanoparticles, novel biomaterials, and nano/micro devices for either diagnosis or therapy, or both, called theranostics. It also presents the latest advancements in healthcare materials and medical technology. The senior researchers from global knowledge centers have written topics including: State-of-the-art of biomaterials for human health Micro- and nanoparticles and their application in biosensors The role of immunoassays Stimuli-responsive smart nanoparticles Diagnosis and treatment of cancer Advanced materials for biomedical application and drug delivery Nanoparticles for diagnosis and/or treatment of Alzheimers disease Hierarchical modelling of elastic behavior of human dental tissue Biodegradable porous hydrogels Hydrogels in tissue engineering, drug delivery, and wound care Modified natural zeolites Supramolecular hydrogels based on cyclodextrin poly(pseudo)rotaxane Polyhydroxyalkanoate-based biomaterials Biomimetic molecularly imprinted polymers |
| computational materials science impact factor: Materials Science and Engineering William D. Callister, David G. Rethwisch, 2011 Building on the success of previous editions, this book continues to provide engineers with a strong understanding of the three primary types of materials and composites, as well as the relationships that exist between the structural elements of materials and their properties. The relationships among processing, structure, properties, and performance components for steels, glass-ceramics, polymer fibers, and silicon semiconductors are explored throughout the chapters. The discussion of the construction of crystallographic directions in hexagonal unit cells is expanded. At the end of each chapter, engineers will also find revised summaries and new equation summaries to reexamine key concepts. |
| computational materials science impact factor: Computational Materials Science , 2004-03-19 Computational tools have been permanently deposited into the toolbox of theoretical chemists. The impact of new computational tools can hardly be overestimated, and their presence in research and applications is overwhelming. Theoretical methods such as quantum mechanics, molecular dynamics, and statistical mechanics have been successfully used to characterize chemical systems and to design new materials, drugs, and chemicals. This volume on Computational Material Sciences covers selected examples of notable applications of computational techniques to material science. The chapters contained in this volume include discussions of the phenomenon of chaos in chemistry, reaction network analysis, and mechanisms of formation of clusters. Details of more practical applications are also included in the form of reviews of computational design of new materials and the prediction of properties and structures of well known molecular assemblies. Current developments of effective computational methods, which will help in understanding, predicting, and optimizing periodic systems, nanostructures, clusters and model surfaces are also covered in this volume. - Reviews of current computational methods applied in material science - Reviews of practical applications of modelling of structures and properties of materials - Cluster and periodical approaches |
| computational materials science impact factor: Computational and Experimental Methods in Mechanical Engineering Veeredhi Vasudeva Rao, Adepu Kumaraswamy, Sahil Kalra, Ambuj Saxena, 2021-08-30 This book includes selected peer-reviewed papers presented at third International Conference on Computational and Experimental Methods in Mechanical Engineering held in June 2021 at G.L. Bajaj Institute of Technology and Management, Greater Noida, U.P, India. The book covers broad range of topics in latest research including hydropower, heat transfer, fluid mechanics, advanced manufacturing, recycling and waste disposal, solar energy, thermal power plants, refrigeration and air conditioning, robotics, automation and mechatronics, and advanced designs. The authors are experienced and experts in their field, and all papers are reviewed by expert reviewers in respective field. The book is useful for industry peoples, faculties, and research scholars. |
| computational materials science impact factor: Impact of Advances in Computing and Communications Technologies on Chemical Science and Technology National Research Council, Division on Engineering and Physical Sciences, Commission on Physical Sciences, Mathematics, and Applications, Chemical Sciences Roundtable, 1999-08-31 The Chemical Sciences Roundtable provides a forum for discussing chemically related issues affecting government, industry and government. The goal is to strengthen the chemical sciences by foster communication among all the important stakeholders. At a recent Roundtable meeting, information technology was identified as an issue of increasing importance to all sectors of the chemical enterprise. This book is the result of a workshop convened to explore this topic. |
| computational materials science impact factor: Computational Materials Science A.M. Ovrutsky, A. S Prokhoda, M.S. Rasshchupkyna, 2013-11-19 Computational Materials Science provides the theoretical basis necessary for understanding atomic surface phenomena and processes of phase transitions, especially crystallization, is given. The most important information concerning computer simulation by different methods and simulation techniques for modeling of physical systems is also presented. A number of results are discussed regarding modern studies of surface processes during crystallization. There is sufficiently full information on experiments, theory, and simulations concerning the surface roughening transition, kinetic roughening, nucleation kinetics, stability of crystal shapes, thin film formation, imperfect structure of small crystals, size dependent growth velocity, distribution coefficient at growth from alloy melts, superstructure ordering in the intermetallic compound. Computational experiments described in the last chapter allow visualization of the course of many processes and better understanding of many key problems in Materials Science. There is a set of practical steps concerning computational procedures presented. Open access to executable files in the book make it possible for everyone to understand better phenomena and processes described in the book. - Valuable reference book, but also helpful as a supplement to courses - Computer programs available to supplement examples - Presents several new methods of computational materials science and clearly summarizes previous methods and results |
| computational materials science impact factor: Computational Matter Susan Stepney, Steen Rasmussen, Martyn Amos, 2018-07-20 This book is concerned with computing in materio: that is, unconventional computing performed by directly harnessing the physical properties of materials. It offers an overview of the field, covering four main areas of interest: theory, practice, applications and implications. Each chapter synthesizes current understanding by deliberately bringing together researchers across a collection of related research projects. The book is useful for graduate students, researchers in the field, and the general scientific reader who is interested in inherently interdisciplinary research at the intersections of computer science, biology, chemistry, physics, engineering and mathematics. |
| computational materials science impact factor: Nano Mechanics and Materials Wing Kam Liu, Eduard G. Karpov, Harold S. Park, 2006-08-30 Nanotechnology is a progressive research and development topic with large amounts of venture capital and government funding being invested worldwide. Nano mechanics, in particular, is the study and characterization of the mechanical behaviour of individual atoms, systems and structures in response to various types of forces and loading conditions. This text, written by respected researchers in the field, informs researchers and practitioners about the fundamental concepts in nano mechanics and materials, focusing on their modelling via multiple scale methods and techniques. The book systematically covers the theory behind multi-particle and nanoscale systems, introduces multiple scale methods, and finally looks at contemporary applications in nano-structured and bio-inspired materials. |
| computational materials science impact factor: Crystals, Defects and Microstructures Rob Phillips, 2001-02-22 Examines the advances made in the field in recent years and looks at the various methods now used; ideal for graduate students and researchers. |
| computational materials science impact factor: Computational Materials Science Wofram Hergert, Arthur Ernst, Markus Däne, 2004-04-29 Computational Physics is now a discipline in its own right, comparable with theoretical and experimental physics. Computational Materials Science concentrates on the calculation of materials properties starting from microscopic theories. It has become a powerful tool in industrial research for designing new materials, modifying materials properties and optimizing chemical processes. This book focusses on the application of computational methods in new fields of research, such as nanotechnology, spintronics and photonics, which will provide the foundation for important technological advances in the future. Methods such as electronic structure calculations, molecular dynamics simulations and beyond are presented, the discussion extending from the basics to the latest applications. |
| computational materials science impact factor: Research Program Summary, Department of Materials Sciences and Engineering: Ames Laboratory , |
COMPUTATIONAL definition | Cambridge English Dictionary
COMPUTATIONAL meaning: 1. involving the calculation of answers, amounts, results, etc.: 2. using computers to study…. Learn more.
COMPUTATIONAL Definition & Meaning - Merriam-Webster
The meaning of COMPUTATION is the act or action of computing : calculation. How to use computation in a sentence.
Computation - Wikipedia
Mechanical or electronic devices (or, historically, people) that perform computations are known as computers. Computer science is an academic field that involves the study of computation.
Computational science - Wikipedia
Computational science, also known as scientific computing, technical computing or scientific computation (SC), is a division of science, and more specifically the Computer Sciences, …
Computational - Definition, Meaning & Synonyms
Computational is an adjective referring to a system of calculating or "computing," or, more commonly today, work involving computers. Tasks with a lot of computational steps are best …
COMPUTATIONAL definition in American English - Collins Online …
Computational means using computers. Students may pursue research in any aspect of computational linguistics. Collins COBUILD Advanced Learner’s Dictionary. Copyright © …
Computational - definition of computational by ... - The Free …
Define computational. computational synonyms, computational pronunciation, computational translation, English dictionary definition of computational. n. 1. a. The act or process of …
COMPUTATIONAL - Definition & Translations | Collins English …
Discover everything about the word "COMPUTATIONAL" in English: meanings, translations, synonyms, pronunciations, examples, and grammar insights - all in one comprehensive guide.
What is computational thinking? - Introduction to computational …
Learn about the four cornerstones of computational thinking including decomposition, pattern recognition, abstraction and algorithms.
Computational Definition & Meaning - YourDictionary
Computational definition: Of or relating to
computation.
COMPUTATIONAL definition | Cambridge English Dictionary
COMPUTATIONAL meaning: 1. involving the calculation of answers, amounts, results, etc.: 2. using computers to study…. Learn more.
COMPUTATIONAL Definition & Meaning - Merriam-Webster
The meaning of COMPUTATION is the act or action of computing : calculation. How to use computation in a sentence.
Computation - Wikipedia
Mechanical or electronic devices (or, historically, people) that perform computations are known as computers. Computer science is an academic field that involves the study of computation.
Computational science - Wikipedia
Computational science, also known as scientific computing, technical computing or scientific computation (SC), is a division of science, and more specifically the Computer Sciences, …
Computational - Definition, Meaning & Synonyms - Vocabulary.com
Computational is an adjective referring to a system of calculating or "computing," or, more commonly today, work involving computers. Tasks with a lot of computational steps are best …
COMPUTATIONAL definition in American English - Collins Online …
Computational means using computers. Students may pursue research in any aspect of computational linguistics. Collins COBUILD Advanced Learner’s Dictionary. Copyright © …
Computational - definition of computational by ... - The Free …
Define computational. computational synonyms, computational pronunciation, computational translation, English dictionary definition of computational. n. 1. a. The act or process of …
COMPUTATIONAL - Definition & Translations | Collins English …
Discover everything about the word "COMPUTATIONAL" in English: meanings, translations, synonyms, pronunciations, examples, and grammar insights - all in one comprehensive guide.
What is computational thinking? - Introduction to computational
Learn about the four cornerstones of computational thinking including decomposition, pattern recognition, abstraction and algorithms.
Computational Definition & Meaning - YourDictionary
Computational definition: Of or relating to
computation.
