Natalia Rylko – författare

2D and Quasi-2D Composite and Nanocomposite Materials: Theory, Properties and Photonic Applications covers the theory, characterization and computational modeling of 2D composite materials and shows how they are used for the creation of materials for 3D structures

The book covers three major themes:

Properties of 2D and quasi-2D composites are discussed in the context of homogenization theory. Homogenization results are discussed for spatiotemporal material composites assembled from materials which are distributed on a micro-scale in space and in time. New types of transport phenomena and localization in random media are addressed, with particular attention to the non-reciprocity of transport coefficients. Plasmonics and magneto-optics are also of particular interest. Magneto-transport and sub-wavelength resolution in electromagnetic and acoustic imaging are further considered.

This book is an important resource for materials scientists and engineers working on nanomaterials, photonic composites, and materials theory, modeling and simulations.

Outlines major modelling techniques of 2D nanocomposites for photonic applications Explores how the properties of 2D nanocomposites make them suitable for use for building 3D structures Assesses the challenges of using 2D nanocomposites for designing new devices on a mass scale

2D and Quasi-2D Composite and Nanocomposite Materials: Theory, Properties and Photonic Applications covers the theory, characterization and computational modeling of 2D composite materials and shows how they are used for the creation of materials for 3D structuresThe book covers three major themes:- Properties of 2D and quasi-2D composites are discussed in the context of homogenization theory. Homogenization results are discussed for spatiotemporal material composites assembled from materials which are distributed on a micro-scale in space and in time.- New types of transport phenomena and localization in random media are addressed, with particular attention to the non-reciprocity of transport coefficients.- Plasmonics and magneto-optics are also of particular interest. Magneto-transport and sub-wavelength resolution in electromagnetic and acoustic imaging are further considered. This book is an important resource for materials scientists and engineers working on nanomaterials, photonic composites, and materials theory, modeling and simulations.- Outlines major modelling techniques of 2D nanocomposites for photonic applications- Explores how the properties of 2D nanocomposites make them suitable for use for building 3D structures- Assesses the challenges of using 2D nanocomposites for designing new devices on a mass scale

Anisotropy of Metamaterials: Beyond Conventional Paradigms provides a comprehensive introduction to the mathematical modeling of metamaterials based on the macroscopic complex-valued permittivity tensor of dispersed random composites. Key topics include physical and mathematical theory, computer simulations, constructive homogenization, classification of dispersed random composites and their applications in cancer recognition. Image processing and machine learning algorithms are used. The book also discusses the precision of various effective medium approximations, including Bruggeman and Maxwell-Garnett formulas. New analytical, approximate and exact formulas and bounds for the macroscopic permittivity and piezoelectric constants of composites are derived. This book is a valuable tool for academics and professionals in photonics, presenting sustainable materials for sensing, health diagnostics and cancer detection methodologies.Key features:Offers key insights into the current trends and techniques in the study of the macroscopic properties of metamaterials, aiming at stimulating new avenues of researchPresents examples of image analysis, the primary tool for non-destructive metamaterials analysisDiscusses the applications of Machine Learning to image processing, illustrated using specific code in Python programming language

Anisotropy of Metamaterials: Beyond Conventional Paradigms provides a comprehensive introduction to the mathematical modeling of metamaterials based on the macroscopic complex-valued permittivity tensor of dispersed random composites. Key topics include physical and mathematical theory, computer simulations, constructive homogenization, classification of dispersed random composites and their applications in cancer recognition. Image processing and machine learning algorithms are used. The book also discusses the precision of various effective medium approximations, including Bruggeman and Maxwell-Garnett formulas. New analytical, approximate and exact formulas and bounds for the macroscopic permittivity and piezoelectric constants of composites are derived. This book is a valuable tool for academics and professionals in photonics, presenting sustainable materials for sensing, health diagnostics and cancer detection methodologies.Key features:Offers key insights into the current trends and techniques in the study of the macroscopic properties of metamaterials, aiming at stimulating new avenues of researchPresents examples of image analysis, the primary tool for non-destructive metamaterials analysisDiscusses the applications of Machine Learning to image processing, illustrated using specific code in Python programming language

Introduction to Mathematical Modeling and Computer Simulations, Second Edition continues to serve as an engaging and accessible textbook for undergraduates studying mathematical modeling and computer simulations. The book is heavily focussed on applications, and so may have a particular appeal to applied mathematicians, engineers, and others working in applied quantitative disciplines. The book may also be useful as a reference text for reference text for early-career stage practitioners. New to this Edition:A new chapter on Machine Learning and Data Analysis in order to account for recent developments in the field.Chapter 9, ‘Asymptotic Methods in Composites’, has been entirely re-written to make it more consistent with industry and scientific standards.Includes an elementary introduction to programming in Python language.The Jupyter notebooks with examples for Chapter 10 and Appendix A are available for a download from www.Routledge.com/9781032661513.

Introduction to Mathematical Modeling and Computer Simulations, Second Edition continues to serve as an engaging and accessible textbook for undergraduates studying mathematical modeling and computer simulations. The book is heavily focussed on applications, and so may have a particular appeal to applied mathematicians, engineers, and others working in applied quantitative disciplines. The book may also be useful as a reference text for reference text for early-career stage practitioners. New to this Edition: A new chapter on Machine Learning and Data Analysis in order to account for recent developments in the field. Chapter 9, 'Asymptotic Methods in Composites', has been entirely re-written to make it more consistent with industry and scientific standards. Includes an elementary introduction to programming in Python language. The Jupyter notebooks with examples for Chapter 10 and Appendix A are available for a download from www.Routledge.com/9781032661513.

Introduction to Mathematical Modeling and Computer Simulations, Second Edition continues to serve as an engaging and accessible textbook for undergraduates studying mathematical modeling and computer simulations. The book is heavily focussed on applications, and so may have a particular appeal to applied mathematicians, engineers, and others working in applied quantitative disciplines. The book may also be useful as a reference text for reference text for early-career stage practitioners. New to this Edition: A new chapter on Machine Learning and Data Analysis in order to account for recent developments in the field. Chapter 9, 'Asymptotic Methods in Composites', has been entirely re-written to make it more consistent with industry and scientific standards. Includes an elementary introduction to programming in Python language. The Jupyter notebooks with examples for Chapter 10 and Appendix A are available for a download from www.Routledge.com/9781032661513.

Anisotropy of Metamaterials: Beyond Conventional Paradigms provides a comprehensive introduction to the mathematical modeling of metamaterials based on the macroscopic complex-valued permittivity tensor of dispersed random composites. Key topics include physical and mathematical theory, computer simulations, constructive homogenization, classification of dispersed random composites and their applications in cancer recognition. Image processing and machine learning algorithms are used. The book also discusses the precision of various effective medium approximations, including Bruggeman and Maxwell-Garnett formulas. New analytical, approximate and exact formulas and bounds for the macroscopic permittivity and piezoelectric constants of composites are derived. This book is a valuable tool for academics and professionals in photonics, presenting sustainable materials for sensing, health diagnostics and cancer detection methodologies.

Key features:

Offers key insights into the current trends and techniques in the study of the macroscopic properties of metamaterials, aiming at stimulating new avenues of research Presents examples of image analysis, the primary tool for non-destructive metamaterials analysis Discusses the applications of Machine Learning to image processing, illustrated using specific code in Python programming language

Anisotropy of Metamaterials: Beyond Conventional Paradigms provides a comprehensive introduction to the mathematical modeling of metamaterials based on the macroscopic complex-valued permittivity tensor of dispersed random composites. Key topics include physical and mathematical theory, computer simulations, constructive homogenization, classification of dispersed random composites and their applications in cancer recognition. Image processing and machine learning algorithms are used. The book also discusses the precision of various effective medium approximations, including Bruggeman and Maxwell-Garnett formulas. New analytical, approximate and exact formulas and bounds for the macroscopic permittivity and piezoelectric constants of composites are derived. This book is a valuable tool for academics and professionals in photonics, presenting sustainable materials for sensing, health diagnostics and cancer detection methodologies.

Key features:

Offers key insights into the current trends and techniques in the study of the macroscopic properties of metamaterials, aiming at stimulating new avenues of research Presents examples of image analysis, the primary tool for non-destructive metamaterials analysis Discusses the applications of Machine Learning to image processing, illustrated using specific code in Python programming language