Ternary Quantum Dots: Synthesis, Properties, and Applications reviews the latest advances in ternary (I-III-VI) chalcopyrite quantum dots (QDs), along with their synthesis, properties and applications. Sections address the fundamental key concepts of ternary quantum dots, progress in synthesis strategies (i.e., organic and aqueous synthesis), and characterization methods (i.e., transmission electron microscopy, dynamic light scattering, etc.). Properties of ternary quantum dots are comprehensively reviewed, including optical, chemical and physical properties. The factors and mechanisms of the cytotoxicity of ternary quantum dot-based nanomaterials are also described. Since ternary chalcopyrite quantum dots are less toxic and more environmentally benign than conventional binary II-VI chalcogenide quantum dots, they are being investigated to replace conventional quantum dots in a range of applications. Thus, this book reviews QDs in various applications, such as solar cells, photocatalytic, sensors and bio-applications.

Nanomagnetic Materials: Fabrication, Characterization and Application explores recent studies of conventional nanomagnetic materials in spintronics, data storage, magnetic sensors and biomedical applications. In addition, the book also reviews novel magnetic characteristics induced in two-dimensional materials, diamonds, and those induced by the artificial formation of lattice defect and heterojunction as novel nanomagnetic materials. Nanomagnetic materials are usually based on d- and f-electron systems. They are an important solution to the demand for higher density of information storage, arising from the emergence of novel technologies required for non-volatile memory systems. Advances in the understanding of magnetization dynamics and in the characteristics of nanoparticles or surface of nanomagnetic materials is resulting in greater expansion of applications of nanomagnetic materials, including in biotechnology, sensor devices, energy harvesting, and power generating systems. This book provides a cogent overview of the latest research on novel nanomagnetic materials, including spintronic nanomagnets, molecular nanomagnets, self-assembling magnetic nanomaterials, nanoparticles, multifunctional materials, and heterojunction-induced novel magnetism.

The Beginnings of Electron Microscopy - Part 1, Volume 220 in the Advances in Imaging and Electron Physics series highlights new advances in the field, with this new volume presenting interesting chapters on Electron-optical Research at the AEG Forschungs-Institut 1928-1940, On the History of Scanning Electron Microscopy, of the Electron Microprobe, and of Early Contributions to Transmission Electron Microscopy, Random Recollections of the Early Days, Early History of Electron Microscopy in Czechoslovakia, Personal Reminiscences of Early Days in Electron, Megavolt Electron Microscopy, Cryo-Electron Microscopy and Ultramicrotomy: Reminiscences and Reflections, and much more.

Advances in Imaging and Electron Physics, Volume 218 merges two long-running serials, Advances in Electronics and Electron Physics and Advances in Optical and Electron Microscopy. The series features articles on the physics of electron devices (especially semiconductor devices), particle optics at high and low energies, microlithography, image science, digital image processing, electromagnetic wave propagation, electron microscopy and the computing methods used in all these domains. Specific chapters in this release cover Phase retrieval methods applied to coherent imaging, X-ray phase-contrast imaging: a broad overview of some fundamentals, Graphene and borophene as nanoscopic materials for electronics - with review of the physics, and more.

Thermoelectricity and Advanced Thermoelectric Materials reviews emerging thermoelectric materials, including skutterudites, clathrates, and half-Heusler alloys. In addition, the book discusses a number of oxides and silicides that have promising thermoelectric properties. Because 2D materials with high figures of merit have emerged as promising candidates for thermoelectric applications, this book presents an updated introduction to the field of thermoelectric materials, including recent advances in materials synthesis, device modeling, and design. Finally, the book addresses the theoretical difficulties and methodologies of computing the thermoelectric properties of materials that can be used to understand and predict highly efficient thermoelectric materials. This book is a key reference for materials scientists, physicists, and engineers in energy.

Quantitative Atomic-Resolution Electron Microscopy, Volume 217, the latest release in the Advances in Imaging and Electron Physics series merges two long-running serials, Advances in Electronics and Electron Physics and Advances in Optical and Electron Microscopy. The series features extended articles on the physics of electron devices (especially semiconductor devices), particle optics at high and low energies, microlithography, image science, digital image processing, electromagnetic wave propagation, electron microscopy, and the computing methods. Chapters in this release include Statistical parameter estimation theory, Efficient fitting algorithm, Statistics-based atom counting , Atom column detection, Optimal experiment design for nanoparticle atom-counting from ADF STEM images, and more.

Mathematical Modelling of Swimming Soft Microrobots presents a theoretical framework for modelling of soft microrobotic systems based on resistive-force theory. Microorganisms are highly efficient at swimming regardless of the rheological and physical properties of the background fluids. This efficiency has inspired researchers and Engineers to develop microrobots that resemble the morphology and swimming strategies of microorganisms. The ultimate goal of this book is threefold: first, to relate resistive-force theory to externally and internally actuated microrobotic systems; second, to enable the readers to develop numerical models of a wide range of microrobotic systems; third, to enable the reader to optimize the design of the microrobot to enhance its swimming efficiency.

Mechanics of Smart Magneto-electro-elastic Nanostructures provides mathematical models for buckling and vibration analysis of flexoelectric and magneto-electro-elastic nanostructures under thermal environment effects. Analytical results are presented in each chapter based on changes in different parameters, including various electric and magnetic potential, non-local parameters or different boundary conditions and their effects on vibration and buckling behavior on nanobeams and nanoplates. Key characteristics of smart materials and their response to external factors are presented, including size-dependency of nanostructures, effect of various gradient indexes, thermal environment effects, and effects of elastic foundation.

LASER INTER-SATELLITE LINKS TECHNOLOGY State of the art resource covering key technologies and related theories of inter-satellite links Laser Inter-Satellite Links Technology explores satellite networking as a growing topic in the field of communication technology, introducing the definition, types, and working frequency bands of inter-satellite links, discussing the number of orbital elements of the spacecraft motion state under two-body motion and their conversion relationship, and establishing the basic demand model for inter-satellite link network, chain topology model, and transmission protocol model. The book focuses on the analysis and introduction of the principles and error sources of microwave and laser inter-satellite ranging, including the basic composition, workflow, and constraints of the laser inter-satellite link, and related design principles of the inter-satellite laser transmitter and receivers. Later chapters also discuss theories and methods of acquisition, alignment, and tracking, the impact of alignment errors on performance, and inter-satellite link modulation and its implementation. Specific sample topics covered in Laser Inter-Satellite Links Technology include: Pulse position modulation (PPM), differential pulse position modulation (DPPM), digital pulse interval modulation (DPIM), and double-head pulse interval modulation (DH-PIM) Basic demand model of inter-satellite link network application, including basic configuration of constellations and inter-satellite transmission networks Inter-satellite ranging accuracy, principles of microwave inter-satellite ranging, and analysis of microwave ranging error sources Effect of tracking error on the beam distribution at the receiving end and influence of tracking and pointing error on communication error rate Laser Inter-Satellite Links Technology serves a completely comprehensive resource on the subject and is a must-have reference for experts and scholars in aerospace, along with graduates and senior undergraduates in related programs of study.

Cognitive Computing for Human-Robot Interaction: Principles and Practices explores the efforts that should ultimately enable society to take advantage of the often-heralded potential of robots to provide economical and sustainable computing applications. This book discusses each of these applications, presents working implementations, and combines coherent and original deliberative architecture for human-robot interactions (HRI). Supported by experimental results, it shows how explicit knowledge management promises to be instrumental in building richer and more natural HRI, by pushing for pervasive, human-level semantics within the robot's deliberative system for sustainable computing applications. This book will be of special interest to academics, postgraduate students, and researchers working in the area of artificial intelligence and machine learning. Key features: Introduces several new contributions to the representation and management of humans in autonomous robotic systems; Explores the potential of cognitive computing, robots, and HRI to generate a deeper understanding and to provide a better contribution from robots to society; Engages with the potential repercussions of cognitive computing and HRI in the real world.

Laser Annealing Processes in Semiconductor Technology: Theory, Modeling and Applications in Nanoelectronics synthesizes the scientific and technological advances of laser annealing processes for current and emerging nanotechnologies. The book provides an overview of the laser-matter interactions of materials and recent advances in modeling of laser-related phenomena, with the bulk of the book focusing on current and emerging (beyond-CMOS) applications. Reviewed applications include laser annealing of CMOS, group IV semiconductors, superconducting materials, photonic materials, 2D materials. This comprehensive book is ideal for post-graduate students, new entrants, and experienced researchers in academia, research and development in materials science, physics and engineering.

Deep Learning for Chest Radiographs enumerates different strategies implemented by the authors for designing an efficient convolution neural network-based computer-aided classification (CAC) system for binary classification of chest radiographs into "Normal" and "Pneumonia." Pneumonia is an infectious disease mostly caused by a bacteria or a virus. The prime targets of this infectious disease are children below the age of 5 and adults above the age of 65, mostly due to their poor immunity and lower rates of recovery. Globally, pneumonia has prevalent footprints and kills more children as compared to any other immunity-based disease, causing up to 15% of child deaths per year, especially in developing countries. Out of all the available imaging modalities, such as computed tomography, radiography or X-ray, magnetic resonance imaging, ultrasound, and so on, chest radiographs are most widely used for differential diagnosis between Normal and Pneumonia. In the CAC system designs implemented in this book, a total of 200 chest radiograph images consisting of 100 Normal images and 100 Pneumonia images have been used. These chest radiographs are augmented using geometric transformations, such as rotation, translation, and flipping, to increase the size of the dataset for efficient training of the Convolutional Neural Networks (CNNs). A total of 12 experiments were conducted for the binary classification of chest radiographs into Normal and Pneumonia. It also includes in-depth implementation strategies of exhaustive experimentation carried out using transfer learning-based approaches with decision fusion, deep feature extraction, feature selection, feature dimensionality reduction, and machine learning-based classifiers for implementation of end-to-end CNN-based CAC system designs, lightweight CNN-based CAC system designs, and hybrid CAC system designs for chest radiographs. This book is a valuable resource for academicians, researchers, clinicians, postgraduate and graduate students in medical imaging, CAC, computer-aided diagnosis, computer science and engineering, electrical and electronics engineering, biomedical engineering, bioinformatics, bioengineering, and professionals from the IT industry.

Functional Tactile Sensors: Materials, Devices and Integrations focuses on the subject of novel materials design and device integration of tactile sensors for functional applications. The book addresses the design, materials characteristics, device operation principles, specialized device application and mechanisms of the latest reported tactile sensors. The emphasis of the book lies in the materials science aspects of tactile sensors-understanding the relationship between material properties and device performance. It will be an ideal resource for researchers working in materials science, engineering and physics.

Optical Materials, Second Edition, presents, in a unified form, the underlying physical and structural processes that determine the optical behavior of materials. It does this by combining elements from physics, optics, and materials science in a seamless manner, and introducing quantum mechanics when needed. The book groups the characteristics of optical materials into classes with similar behavior. In treating each type of material, the text pays particular attention to atomic composition and chemical makeup, electronic states and band structure, and physical microstructure so that the reader will gain insight into the kinds of materials engineering and processing conditions that are required to produce a material exhibiting a desired optical property. The physical principles are presented on many levels, including a physical explanation, followed by formal mathematical support and examples and methods of measurement. The reader may overlook the equations with no loss of comprehension, or may use the text to find appropriate equations for calculations of optical properties.

Organometallic Luminescence: A Case Study of Alq3, an OLED Reference Material contains many discoveries on Alq3, an important organometallic material to the optoelectronics community that includes insights that can be applied to other organic compounds. The book contains groundbreaking research from the author's own investigation into the Alq3 material that is based on years of experiments, the results of which initially escaped any logical explanation. The book describes a simple method based on photoluminescence to observe optical properties in Alq3, also covering the optical properties of absorption and long decay from theoretical and experimental perspectives.

Artificial Intelligence for Future Generation Robotics offers a vision for potential future robotics applications for AI technologies. Each chapter includes theory and mathematics to stimulate novel research directions based on the state-of-the-art in AI and smart robotics. Organized by application into ten chapters, this book offers a practical tool for researchers and engineers looking for new avenues and use-cases that combine AI with smart robotics. As we witness exponential growth in automation and the rapid advancement of underpinning technologies, such as ubiquitous computing, sensing, intelligent data processing, mobile computing and context aware applications, this book is an ideal resource for future innovation.

NONLINEAR FILTERS Discover the utility of using deep learning and (deep) reinforcement learning in deriving filtering algorithms with this insightful and powerful new resource Nonlinear Filters: Theory and Applications delivers an insightful view on state and parameter estimation by merging ideas from control theory, statistical signal processing, and machine learning. Taking an algorithmic approach, the book covers both classic and machine learning-based filtering algorithms. Readers of Nonlinear Filters will greatly benefit from the wide spectrum of presented topics including stability, robustness, computability, and algorithmic sufficiency. Readers will also enjoy: Organization that allows the book to act as a stand-alone, self-contained reference A thorough exploration of the notion of observability, nonlinear observers, and the theory of optimal nonlinear filtering that bridges the gap between different science and engineering disciplines A profound account of Bayesian filters including Kalman filter and its variants as well as particle filter A rigorous derivation of the smooth variable structure filter as a predictor-corrector estimator formulated based on a stability theorem, used to confine the estimated states within a neighborhood of their true values A concise tutorial on deep learning and reinforcement learning A detailed presentation of the expectation maximization algorithm and its machine learning-based variants, used for joint state and parameter estimation Guidelines for constructing nonparametric Bayesian models from parametric ones Perfect for researchers, professors, and graduate students in engineering, computer science, applied mathematics, and artificial intelligence, Nonlinear Filters: Theory and Applications will also earn a place in the libraries of those studying or practicing in fields involving pandemic diseases, cybersecurity, information fusion, augmented reality, autonomous driving, urban traffic network, navigation and tracking, robotics, power systems, hybrid technologies, and finance.

The need to more efficiently harvest energy for electronics has spurred investigation into materials that can harvest energy from locally abundant sources. Ferroelectric Materials for Energy Harvesting and Storage is the first book to bring together fundamental mechanisms for harvesting various abundant energy sources using ferroelectric and piezoelectric materials. The authors discuss strategies of designing materials for efficiently harvesting energy sources like solar, wind, wave, temperature fluctuations, mechanical vibrations, biomechanical motion, and stray magnetic fields. In addition, concepts of the high density energy storage using ferroelectric materials is explored. Ferroelectric Materials for Energy Harvesting and Storage is appropriate for those working in materials science and engineering, physics, chemistry and electrical engineering disciplines.

Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications illustrates recent advances in the field of mem-elements (memristor, memcapacitor, meminductor) and their applications in nonlinear dynamical systems, computer science, analog and digital systems, and in neuromorphic circuits and artificial intelligence. The book is mainly devoted to recent results, critical aspects and perspectives of ongoing research on relevant topics, all involving networks of mem-elements devices in diverse applications. Sections contribute to the discussion of memristive materials and transport mechanisms, presenting various types of physical structures that can be fabricated to realize mem-elements in integrated circuits and device modeling. As the last decade has seen an increasing interest in recent advances in mem-elements and their applications in neuromorphic circuits and artificial intelligence, this book will attract researchers in various fields.