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Due to their small size and their dependence on very fast phenomena, nanomaterials are ideal systems for computational modelling. This book provides an overview of various nanosystems classified by their dimensions: 0D (nanoparticles, QDs, etc.), 1D (nanowires, nanotubes), 2D (thin films, graphene, etc.), 3D (nanostructured bulk materials, devices). Fractal dimensions, such as nanoparticle agglomerates, percolating films and combinations of materials of different dimensionalities are also covered (e.g. epitaxial decoration of nanowires by nanoparticles, i.e. 0D+1D nanomaterials). For each class, the focus will be on growth, structure, and physical/chemical properties. The book presents a broad range of techniques, including density functional theory, molecular dynamics, non-equilibrium molecular dynamics, finite element modelling (FEM), numerical modelling and meso-scale modelling. The focus is on each method's relevance and suitability for the study of materials and phenomena in the nanoscale. This book is an important resource for understanding the mechanisms behind basic properties of nanomaterials, and the major techniques for computational modelling of nanomaterials. - Explores the major modelling techniques used for different classes of nanomaterial - Assesses the best modelling technique to use for each different type of nanomaterials - Discusses the challenges of using certain modelling techniques with specific nanomaterials
Computational Modelling of Nanoparticles highlights recent advances in the power and versatility of computational modelling, experimental techniques, and how new progress has opened the door to a more detailed and comprehensive understanding of the world of nanomaterials. Nanoparticles, having dimensions of 100 nanometers or less, are increasingly being used in applications in medicine, materials and manufacturing, and energy. Spanning the smallest sub-nanometer nanoclusters to nanocrystals with diameters of 10s of nanometers, this book provides a state-of-the-art overview on how computational modelling can provide, often otherwise unobtainable, insights into nanoparticulate structure and properties. This comprehensive, single resource is ideal for researchers who want to start/improve their nanoparticle modelling efforts, learn what can be (and what cannot) achieved with computational modelling, and understand more clearly the value and details of computational modelling efforts in their area of research.
Computational Modelling of Nanoparticles highlights recent advances in the power and versatility of computational modelling, experimental techniques, and how new progress has opened the door to a more detailed and comprehensive understanding of the world of nanomaterials. Nanoparticles, having dimensions of 100 nanometers or less, are increasingly being used in applications in medicine, materials and manufacturing, and energy. Spanning the smallest sub-nanometer nanoclusters to nanocrystals with diameters of 10s of nanometers, this book provides a state-of-the-art overview on how computational modelling can provide, often otherwise unobtainable, insights into nanoparticulate structure and properties. This comprehensive, single resource is ideal for researchers who want to start/improve their nanoparticle modelling efforts, learn what can be (and what cannot) achieved with computational modelling, and understand more clearly the value and details of computational modelling efforts in their area of research. - Explores how computational modelling can be successfully applied at the nanoscale level - Includes techniques for the computation modelling of different types of nanoclusters, including nanoalloy clusters, fullerines and Ligated and/or solvated nanoclusters - Offers complete coverage of the use of computational modelling at the nanoscale, from characterization and processing, to applications
Applications of nanotechnology continue to fuel significant innovations in areas ranging from electronics, microcomputing, and biotechnology to medicine, consumer supplies, aerospace, and energy production. As progress in nanoscale science and engineering leads to the continued development of advanced materials and new devices, improved methods of modeling and simulation are required to achieve a more robust quantitative understanding of matter at the nanoscale. Computational Nanotechnology: Modeling and Applications with MATLAB® provides expert insights into current and emerging methods, opportunities, and challenges associated with the computational techniques involved in nanoscale research. Written by, and for, those working in the interdisciplinary fields that comprise nanotechnology—including engineering, physics, chemistry, biology, and medicine—this book covers a broad spectrum of technical information, research ideas, and practical knowledge. It presents an introduction to computational methods in nanotechnology, including a closer look at the theory and modeling of two important nanoscale systems: molecular magnets and semiconductor quantum dots. Topics covered include: Modeling of nanoparticles and complex nano and MEMS systems Theory associated with micromagnetics Surface modeling of thin films Computational techniques used to validate hypotheses that may not be accessible through traditional experimentation Simulation methods for various nanotubes and modeling of carbon nanotube and silicon nanowire transistors In regard to applications of computational nanotechnology in biology, contributors describe tracking of nanoscale structures in cells, effects of various forces on cellular behavior, and use of protein-coated gold nanoparticles to better understand protein-associated nanomaterials. Emphasizing the importance of MATLAB for biological simulations in nanomedicine, this wide-ranging survey of computational nanotechnology concludes by discussing future directions in the field, highlighting the importance of the algorithms, modeling software, and computational tools in the development of efficient nanoscale systems.
This book presents nanomaterials as predicted by computational modelling and numerical simulation tools, and confirmed by modern experimental techniques. It begins by summarizing basic theoretical methods, then giving both a theoretical and experimental treatment of how alkali metal clusters develop into nanostructures, as influenced by the cluster's "magic number" of atoms. The book continues with a discussion of atomic clusters and nanostructures, focusing primarily on boron and carbon, exploring, in detail, the one-, two-, and three-dimensional structures of boron and carbon, and describing their myriad potential applications in nanotechnology, from nanocoating and nanosensing to nanobatteries with high borophene capacity. The broad discussion of computational modelling as well as the specific applications to boron and carbon, make this book an essential reference resource for materials scientists in this field of research.
Offering a detailed summary of available modeling methods, both “top-down” and “bottom-up”, this book offers systematic coverage of the use of modeling in the development and application of inorganic nano-materials in industry including sensors, optics, biotechnology, and solar cells. It provides readers with the necessary information to choose the right models and methods for describing particular physical and chemical properties of inorganic materials at varying length scales. Sections include Structure and Dimensionality; Thermodynamics and Nucleation; Magnetic, Optical, and Electronic and Transport Properties; and Case Studies.
Molecular modeling techniques have been widely used in drug discovery fields for rational drug design and compound screening. Now these techniques are used to model or mimic the behavior of molecules, and help us study formulation at the molecular level. Computational pharmaceutics enables us to understand the mechanism of drug delivery, and to develop new drug delivery systems. The book discusses the modeling of different drug delivery systems, including cyclodextrins, solid dispersions, polymorphism prediction, dendrimer-based delivery systems, surfactant-based micelle, polymeric drug delivery systems, liposome, protein/peptide formulations, non-viral gene delivery systems, drug-protein binding, silica nanoparticles, carbon nanotube-based drug delivery systems, diamond nanoparticles and layered double hydroxides (LDHs) drug delivery systems. Although there are a number of existing books about rational drug design with molecular modeling techniques, these techniques still look mysterious and daunting for pharmaceutical scientists. This book fills the gap between pharmaceutics and molecular modeling, and presents a systematic and overall introduction to computational pharmaceutics. It covers all introductory, advanced and specialist levels. It provides a totally different perspective to pharmaceutical scientists, and will greatly facilitate the development of pharmaceutics. It also helps computational chemists to look for the important questions in the drug delivery field. This book is included in the Advances in Pharmaceutical Technology book series.
Providing a clear description of the theory of polydisperse multiphase flows, with emphasis on the mesoscale modelling approach and its relationship with microscale and macroscale models, this all-inclusive introduction is ideal whether you are working in industry or academia. Theory is linked to practice through discussions of key real-world cases (particle/droplet/bubble coalescence, break-up, nucleation, advection and diffusion and physical- and phase-space), providing valuable experience in simulating systems that can be applied to your own applications. Practical cases of QMOM, DQMOM, CQMOM, EQMOM and ECQMOM are also discussed and compared, as are realizable finite-volume methods. This provides the tools you need to use quadrature-based moment methods, choose from the many available options, and design high-order numerical methods that guarantee realizable moment sets. In addition to the numerous practical examples, MATLAB® scripts for several algorithms are also provided, so you can apply the methods described to practical problems straight away.
The development of computational methods that support human health and environmental risk assessment of engineered nanomaterials (ENMs) has attracted great interest because the application of these methods enables us to fill existing experimental data gaps. However, considering the high degree of complexity and multifunctionality of ENMs, computational methods originally developed for regular chemicals cannot always be applied explicitly in nanotoxicology. This book discusses the current state of the art and future needs in the development of computational modeling techniques for nanotoxicology. It focuses on (i) computational chemistry (quantum mechanics, semi-empirical methods, density functional theory, molecular mechanics, molecular dynamics), (ii) nanochemoinformatic methods (quantitative structure–activity relationship modeling, grouping, read-across), and (iii) nanobioinformatic methods (genomics, transcriptomics, proteomics, metabolomics). It reviews methods of calculating molecular descriptors sufficient to characterize the structure of nanoparticles, specifies recent trends in the validation of computational methods, and discusses ways to cope with the uncertainty of predictions. In addition, it highlights the status quo and further challenges in the application of computational methods in regulation (e.g., REACH, OECD) and in industry for product development and optimization and the future directions for increasing acceptance of computational modeling for nanotoxicology.
Advances in photonics and nanotechnology have the potential to revolutionize humanitys ability to communicate and compute. To pursue these advances, it is mandatory to understand and properly model interactions of light with materials such as silicon and gold at the nanoscale, i.e., the span of a few tens of atoms laid side by side. These interactions are governed by the fundamental Maxwells equations of classical electrodynamics, supplemented by quantum electrodynamics. This book presents the current state-of-the-art in formulating and implementing computational models of these interactions. Maxwells equations are solved using the finite-difference time-domain (FDTD) technique, pioneered by the senior editor, whose prior Artech House books in this area are among the top ten most-cited in the history of engineering. This cutting-edge resource helps readers understand the latest developments in computational modeling of nanoscale optical microscopy and microchip lithography, as well as nanoscale plasmonics and biophotonics.