Disposal and Recycling Strategies for Nano-engineered Materials enables the reader to understand and implement the latest methods for the safe disposal and re-use of nanomaterials found in the environment at end-of-life. Sections introduce nanomaterials, their general classification, properties, and preparation techniques before providing an overview and analysis of common disposal strategies. This is followed by in-depth chapters that focus on important steps and innovative strategies in dealing with waste nanomaterials, including sampling, classification and identification of waste materials, green technologies and biodegradation strategies, physico-chemical disposal, integrated technologies to prevent or control nanomaterial wastes entering the environment, and more. This is a valuable resource for researchers, advanced students, engineers, and scientists, with an interest in nanomaterials, their life cycle, waste, and recycling, water treatment, chemical engineering, environmental science, materials science, chemistry, and sustainability.

3D Printing Technology for Water Treatment Applications provides a state-of-the-art presentation on the application of 3D printing technology in water treatment. The book discusses numerous processes and their scope for improvement through the use of 3D-printing technology, including pollutant separation from water and an overview of the advantages and disadvantages of different 3D printed technology over current technologies. In addition, the future outlook for device development using 3D printing water purification is explored. Finally, sustainability issues relating to 3D printing-based water purification processes are discussed, describing specific technologies such as 3D printed membranes. This book will serve as a vital resource for scientists, engineers and environmental professionals working in water treatment technologies.

Advances in Oil-Water Separation: A Complete Guide for Physical, Chemical, and Biochemical Processes discusses a broad variety of chemical, physical and biochemical processes, including skimming, membrane separation, adsorption, onsite chemical reactions, burning and usage of suitable microbial strains for onsite degradation of oil. It critically reviews all current developments in oil-water separation processes and technologies, identifies gaps and illuminates the scope for future research and development in the field. This book provides researchers, engineers and environmental professionals working in oil recovery and storage with solutions for disposal of waste oil and separation of oil from water in a sustainable, environmentally-friendly way. As the book provides a complete state-of-art overview on oil-water separation technologies, it will also ease literature searches on oil-water separation technologies.

Biocomposites: Design and Mechanical Performance describes recent research on cost-effective ways to improve the mechanical toughness and durability of biocomposites, while also reducing their weight. Beginning with an introduction to commercially competitive natural fiber-based composites, chapters then move on to explore the mechanical properties of a wide range of biocomposite materials, including polylactic, polyethylene, polycarbonate, oil palm, natural fiber epoxy, polyhydroxyalkanoate, polyvinyl acetate, polyurethane, starch, flax, poly (propylene carbonate)-based biocomposites, and biocomposites from biodegradable polymer blends, natural fibers, and green plastics, giving the reader a deep understanding of the potential of these materials.

Provides a comprehensive review on new swarm intelligence Offers practical implementation of PSO with MATLAB code Presents statistical analysis techniques so that researchers can analyze their own experiment design Discusses swarm intelligence algorithms in social sector and oil and gas industries Covers recent findings and the implementation techniques to Machine Learning

Applied Soft Computing and Embedded System Applications in Solar Energy deals with energy systems and soft computing methods from a wide range of approaches and application perspectives. The authors examine how embedded system applications can deal with the smart monitoring and controlling of stand-alone and grid-connected solar photovoltaic (PV) systems for increased efficiency. Growth in the area of artificial intelligence with embedded system applications has led to a new era in computing, impacting almost all fields of science and engineering. Soft computing methods implemented to energy-related problems regularly face data-driven issues such as problems of optimization, classification, clustering, or prediction. The authors offer real-time implementation of soft computing and embedded system in the area of solar energy to address the issues with microgrid and smart grid projects (both renewable and non-renewable generations), energy management, and power regulation. They also discuss and examine alternative solutions for energy capacity assessment, energy efficiency systems design, as well as other specific smart grid energy system applications. The book is intended for students, professionals, and researchers in electrical and computer engineering fields, working on renewable energy resources, microgrids, and smart grid projects. Examines the integration of hardware with stand-alone PV panels and real-time monitoring of factors affecting the efficiency of the PV panels Offers real-time implementation of soft computing and embedded system in the area of solar energy Discusses how soft computing plays a huge role in the prediction of efficiency of stand-alone and grid-connected solar PV systems Discusses how embedded system applications with smart monitoring can control and enhance the efficiency of stand-alone and grid-connected solar PV systems Explores swarm intelligence techniques for solar PV parameter estimation Dr. Rupendra Kumar Pachauri is Assistant Professor - Selection Grade in the Department of Electrical and Electronics Engineering, University of Petroleum and Energy Studies (UPES), Dehradun, India. Dr. Jitendra Kumar Pandey is Professor & Head of R&D in the University of Petroleum and Energy Studies (UPES), Dehradun, India. Mr. Abhishek Sharma is working as a research scientist in the research and development department (UPES, India). Dr. Om Prakash Nautiyal is working as a scientist in Uttarakhand Science Education & Research Centre (USERC), Department of Information and Science Technology, Govt. of Uttarakhand, Dehradun, India. Prof. Mangey Ram is working as a Research Professor at Graphic Era Deemed to be University, Dehradun, India.

Applied Soft Computing and Embedded System Applications in Solar Energy deals with energy systems and soft computing methods from a wide range of approaches and application perspectives. The authors examine how embedded system applications can deal with the smart monitoring and controlling of stand-alone and grid-connected solar photovoltaic (PV) systems for increased efficiency. Growth in the area of artificial intelligence with embedded system applications has led to a new era in computing, impacting almost all fields of science and engineering. Soft computing methods implemented to energy-related problems regularly face data-driven issues such as problems of optimization, classification, clustering, or prediction. The authors offer real-time implementation of soft computing and embedded system in the area of solar energy to address the issues with microgrid and smart grid projects (both renewable and non-renewable generations), energy management, and power regulation. They also discuss and examine alternative solutions for energy capacity assessment, energy efficiency systems design, as well as other specific smart grid energy system applications. The book is intended for students, professionals, and researchers in electrical and computer engineering fields, working on renewable energy resources, microgrids, and smart grid projects. Examines the integration of hardware with stand-alone PV panels and real-time monitoring of factors affecting the efficiency of the PV panels Offers real-time implementation of soft computing and embedded system in the area of solar energy Discusses how soft computing plays a huge role in the prediction of efficiency of stand-alone and grid-connected solar PV systems Discusses how embedded system applications with smart monitoring can control and enhance the efficiency of stand-alone and grid-connected solar PV systems Explores swarm intelligence techniques for solar PV parameter estimation Dr. Rupendra Kumar Pachauri is Assistant Professor – Selection Grade in the Department of Electrical and Electronics Engineering, University of Petroleum and Energy Studies (UPES), Dehradun, India. Dr. Jitendra Kumar Pandey is Professor & Head of R&D in the University of Petroleum and Energy Studies (UPES), Dehradun, India. Mr. Abhishek Sharma is working as a research scientist in the research and development department (UPES, India). Dr. Om Prakash Nautiyal is working as a scientist in Uttarakhand Science Education & Research Centre (USERC), Department of Information and Science Technology, Govt. of Uttarakhand, Dehradun, India. Prof. Mangey Ram is working as a Research Professor at Graphic Era Deemed to be University, Dehradun, India.