Silicon-Based Hybrid Nanoparticles: Fundamentals, Properties, and Applications focuses on the fundamental principles and promising applications of silicon-based hybrid nanoparticles in nanoelectronics, energy storage/conversion, catalysis, sensors, biomedicine, environment and imaging. This book is an important reference source for materials scientists and engineers who are seeking to understand more about the major properties and applications of silicon-based hybrid nanoparticles. As the hybridization of silicon nanoparticles with other semiconductors or metal oxides nanoparticles may exhibit superior features, when compared to lone, individual nanoparticles, this book provides the latest insights.

In addition, the silicon/iron oxide hybrid nanoparticles also possess excellent fluorescence, super-paramagnetism, and biocompatibility that can be effectively used for the diagnostic imaging system in vivo. Similarly, gold-silicon nanohybrids could be used as highly efficient near-infrared hyperthermia agents for cancer cell destruction.

In-depth discussion on the physics, chemistry, and engineering beneath the construction of 1D semiconducting hybrid materials

1D Semiconducting Hybrid Nanostructures: Synthesis and Applications in Gas Sensing and Optoelectronics provides breakthrough research developments and trends in a variety of 1D hybrid nanostructures for chemi-resistive gas sensors and optoelectronics applications, including recent investigations and developments regarding the innovative designing approaches, fabrications, and methods used to characterize these hybrid nanostructures. The text also includes the surface and interface properties of 1D hybrid semiconducting nanostructured materials, as well as their optimization for applications in gas sensing and optoelectronics.

This book further addresses the different issues of sensitivity, selectivity, and operating temperature of gas sensors based on hybrid 1D nanostructures. Moreover, it covers the novel and additional functional optoelectronic properties that originate at the interface of 1D semiconducting nanostructures combined with other low dimensional materials.

Some of the specific sample topics covered in this book include:

Thanks to its comprehensive coverage of the subject from highly qualified authors who have significant experience in the field, 1D Semiconducting Hybrid Nanostructures is a must-have reference for senior undergraduate and graduate students, professionals, researchers, in the field of semiconductor physics, materials science, surface science, and chemical engineering.

In-depth discussion on the physics, chemistry, and engineering beneath the construction of 1D semiconducting hybrid materials

1D Semiconducting Hybrid Nanostructures: Synthesis and Applications in Gas Sensing and Optoelectronics provides breakthrough research developments and trends in a variety of 1D hybrid nanostructures for chemi-resistive gas sensors and optoelectronics applications, including recent investigations and developments regarding the innovative designing approaches, fabrications, and methods used to characterize these hybrid nanostructures. The text also includes the surface and interface properties of 1D hybrid semiconducting nanostructured materials, as well as their optimization for applications in gas sensing and optoelectronics.

This book further addresses the different issues of sensitivity, selectivity, and operating temperature of gas sensors based on hybrid 1D nanostructures. Moreover, it covers the novel and additional functional optoelectronic properties that originate at the interface of 1D semiconducting nanostructures combined with other low dimensional materials.

Some of the specific sample topics covered in this book include:

Thanks to its comprehensive coverage of the subject from highly qualified authors who have significant experience in the field, 1D Semiconducting Hybrid Nanostructures is a must-have reference for senior undergraduate and graduate students, professionals, researchers, in the field of semiconductor physics, materials science, surface science, and chemical engineering.

This book provides a comprehensive overview of the current state-of-art in oxide nanostructures, carbon nanostructures and 2D materials fabrication. It covers mimicking of sensing mechanisms and applications in gas sensors. It focuses on gas sensors based on functional nanostructured materials, especially related to issues of sensitivity, selectivity, and temperature dependency for sensors. It covers synthesis, properties, and current gas sensing tools and discusses the necessity for miniaturized sensors. This book will be of use to senior undergraduate and graduate students, professionals, and researchers in the field of solid-state physics, materials science, surface science and chemical engineering.

This book provides a unique approach to understand the Nuclear Physics, especially from the experimental end. The highlight of this book is that special care has been taken to provide more experimental information, considering real experimental data which has been published in several journals. Special experimental focus is given to methodologies involving: offline gamma counting and online particle detection. The book provides information about recent developments in accelerators, overview of the detectors and concise information of associated electronics, data acquisition systems and computers for data analysis.

This book presents recent advancements of machine learning methods and their applications in material science and nanotechnologies. It provides an introduction to the field and for those who wish to explore machine learning in modeling as well as conduct data analyses of material characteristics. The book discusses ways to enhance the material’s electrical and mechanical properties based on available regression methods for supervised learning and optimization of material attributes. In summary, the growing interest among academics and professionals in the field of machine learning methods in functional nanomaterials such as sensors, solar cells, and photocatalysis is the driving force for behind this book. This is a comprehensive scientific reference book on machine learning for advanced functional materials and provides an in-depth examination of recent achievements in material science by focusing on topical issues using machine learning methods.

Silicon-Based Hybrid Nanoparticles: Fundamentals, Properties, and Applications focuses on the fundamental principles and promising applications of silicon-based hybrid nanoparticles in nanoelectronics, energy storage/conversion, catalysis, sensors, biomedicine, environment and imaging. This book is an important reference source for materials scientists and engineers who are seeking to understand more about the major properties and applications of silicon-based hybrid nanoparticles. As the hybridization of silicon nanoparticles with other semiconductors or metal oxides nanoparticles may exhibit superior features, when compared to lone, individual nanoparticles, this book provides the latest insights.

In addition, the silicon/iron oxide hybrid nanoparticles also possess excellent fluorescence, super-paramagnetism, and biocompatibility that can be effectively used for the diagnostic imaging system in vivo. Similarly, gold-silicon nanohybrids could be used as highly efficient near-infrared hyperthermia agents for cancer cell destruction.

In-depth discussion on the physics, chemistry, and engineering beneath the construction of 1D semiconducting hybrid materials

1D Semiconducting Hybrid Nanostructures: Synthesis and Applications in Gas Sensing and Optoelectronics provides breakthrough research developments and trends in a variety of 1D hybrid nanostructures for chemi-resistive gas sensors and optoelectronics applications, including recent investigations and developments regarding the innovative designing approaches, fabrications, and methods used to characterize these hybrid nanostructures. The text also includes the surface and interface properties of 1D hybrid semiconducting nanostructured materials, as well as their optimization for applications in gas sensing and optoelectronics.

This book further addresses the different issues of sensitivity, selectivity, and operating temperature of gas sensors based on hybrid 1D nanostructures. Moreover, it covers the novel and additional functional optoelectronic properties that originate at the interface of 1D semiconducting nanostructures combined with other low dimensional materials.

Some of the specific sample topics covered in this book include:

Thanks to its comprehensive coverage of the subject from highly qualified authors who have significant experience in the field, 1D Semiconducting Hybrid Nanostructures is a must-have reference for senior undergraduate and graduate students, professionals, researchers, in the field of semiconductor physics, materials science, surface science, and chemical engineering.

In-depth discussion on the physics, chemistry, and engineering beneath the construction of 1D semiconducting hybrid materials

1D Semiconducting Hybrid Nanostructures: Synthesis and Applications in Gas Sensing and Optoelectronics provides breakthrough research developments and trends in a variety of 1D hybrid nanostructures for chemi-resistive gas sensors and optoelectronics applications, including recent investigations and developments regarding the innovative designing approaches, fabrications, and methods used to characterize these hybrid nanostructures. The text also includes the surface and interface properties of 1D hybrid semiconducting nanostructured materials, as well as their optimization for applications in gas sensing and optoelectronics.

This book further addresses the different issues of sensitivity, selectivity, and operating temperature of gas sensors based on hybrid 1D nanostructures. Moreover, it covers the novel and additional functional optoelectronic properties that originate at the interface of 1D semiconducting nanostructures combined with other low dimensional materials.

Some of the specific sample topics covered in this book include:

Thanks to its comprehensive coverage of the subject from highly qualified authors who have significant experience in the field, 1D Semiconducting Hybrid Nanostructures is a must-have reference for senior undergraduate and graduate students, professionals, researchers, in the field of semiconductor physics, materials science, surface science, and chemical engineering.

This book provides a comprehensive overview of the current state-of-art in oxide nanostructures, carbon nanostructures and 2D materials fabrication. It covers mimicking of sensing mechanisms and applications in gas sensors. It focuses on gas sensors based on functional nanostructured materials, especially related to issues of sensitivity, selectivity, and temperature dependency for sensors. It covers synthesis, properties, and current gas sensing tools and discusses the necessity for miniaturized sensors. This book will be of use to senior undergraduate and graduate students, professionals, and researchers in the field of solid-state physics, materials science, surface science and chemical engineering.

This book provides a unique approach to understand the Nuclear Physics, especially from the experimental end. The highlight of this book is that special care has been taken to provide more experimental information, considering real experimental data which has been published in several journals. Special experimental focus is given to methodologies involving: offline gamma counting and online particle detection. The book provides information about recent developments in accelerators, overview of the detectors and concise information of associated electronics, data acquisition systems and computers for data analysis.

This book presents recent advancements of machine learning methods and their applications in material science and nanotechnologies. It provides an introduction to the field and for those who wish to explore machine learning in modeling as well as conduct data analyses of material characteristics. The book discusses ways to enhance the material’s electrical and mechanical properties based on available regression methods for supervised learning and optimization of material attributes. In summary, the growing interest among academics and professionals in the field of machine learning methods in functional nanomaterials such as sensors, solar cells, and photocatalysis is the driving force for behind this book. This is a comprehensive scientific reference book on machine learning for advanced functional materials and provides an in-depth examination of recent achievements in material science by focusing on topical issues using machine learning methods.