Jashanpreet Singh – författare

Zirconia: Properties, Synthesis, and Applications is a comprehensive and up-to-date overview of the research in the field of zirconia-based materials. As Zirconia displays a unique combination of mechanical, thermal, electrical, and optical properties, this book focuses on the growing number of applications of zirconia-based materials, including their usage in biomedical, energy, and environmental applications. In addition to zirconia’s properties, synthesis, and applications, a brief historical introduction is provided, along with future guidance. This book will be of interest to a broad audience, including students, academics, and industrial researchers working in materials science, chemistry, and physics.Covers a wide range of applications of zirconia-based materials, including catalysis, photocatalysis, energy production and storage, sensors, biomedical applications, and radioprotection, among othersProvides the fundamentals of zirconia-based materials and cover synthesis methods, crystal structure, phase transitions, materials properties, surface chemistry, and toxicologyIncludes nanostructured zirconia-based materials and a discussion of future prospects

This book details the emerging area of the induction of expert systems in thermal spray technology, replacing traditional parametric optimization methods like numerical modeling and simulation. It promotes, enlightens, and hastens the digital transformation of the surface engineering industry by discussing the contribution of expert systems like Machine Learning (ML) and Artificial Intelligence (AI) toward achieving durable Thermal Spray (TS) coatings.Artificial Intelligence and Machine Learning in the Thermal Spray Industry: Practices, Implementation, and Challenges highlights how AI and ML techniques are used in the TS industry. It sheds light on AI’s versatility, revealing its applicability in solving problems related to conventional simulation and numeric modeling techniques. This book combines automated technologies with expert machines to show several advantages, including decreased error and greater accuracy in judgment, and prediction, enhanced efficiency, reduced time consumption, and lower costs. Specific barriers preventing AI’s successful implementation in the TS industry are also discussed. This book also looks at how training and validating more models with microstructural features of deposited coating will be the center point to grooming this technology in the future. Lastly, this book thoroughly analyzes the digital technologies available for modeling and achieving high-performance coatings, including giving AI-related models like Artificial Neural Networks (ANN) and Convolutional Neural Networks (CNN) more attention.This reference book is directed toward professors, students, practitioners, and researchers of higher education institutions working in the fields that deal with the application of AI and ML technology.

This book details the emerging area of the induction of expert systems in thermal spray technology, replacing traditional parametric optimization methods like numerical modeling and simulation. It promotes, enlightens, and hastens the digital transformation of the surface engineering industry by discussing the contribution of expert systems like Machine Learning (ML) and Artificial Intelligence (AI) toward achieving durable Thermal Spray (TS) coatings.Artificial Intelligence and Machine Learning in the Thermal Spray Industry: Practices, Implementation, and Challenges highlights how AI and ML techniques are used in the TS industry. It sheds light on AI’s versatility, revealing its applicability in solving problems related to conventional simulation and numeric modeling techniques. This book combines automated technologies with expert machines to show several advantages, including decreased error and greater accuracy in judgment, and prediction, enhanced efficiency, reduced time consumption, and lower costs. Specific barriers preventing AI’s successful implementation in the TS industry are also discussed. This book also looks at how training and validating more models with microstructural features of deposited coating will be the center point to grooming this technology in the future. Lastly, this book thoroughly analyzes the digital technologies available for modeling and achieving high-performance coatings, including giving AI-related models like Artificial Neural Networks (ANN) and Convolutional Neural Networks (CNN) more attention.This reference book is directed toward professors, students, practitioners, and researchers of higher education institutions working in the fields that deal with the application of AI and ML technology.

As healthcare challenges such as human aging and traffic accidents continue to increase exponentially, the biomedical sector faces a significant obstacle in arranging patient-specific biomedical products. Over the past two decades, additive manufacturing’s printing quality and ease of production have gained global attention, particularly in the development of scaffolds and implants.This book explores additive manufacturing technologies and their categorization, materials, processing factors, output responses, advantages, challenges, and biomedical applications. It provides a critical analysis of past biomedical applications of additive manufacturing technology, explores recent advancements, and examines the design, applications, and characterizations of biomedical components using additive manufacturing techniques. Moreover, it discusses notable applications of additive fabrication in aerospace, education, and medicine, as it showcases the medical applications of rapid prototyping, addressing computational and experimental aspects of 3D-printed biomedical devices. Also, it provides future human implications and developments.Advanced Manufacturing Technologies in Biomedical Science: Practical Applications, Case Studies, and Future Trends offers a unique framework for understanding and evaluating the latest advancements in biomedical additive manufacturing. This book targets individuals interested in conducting research, providing valuable insights, and can serve as an authoritative source of information for manufacturers and academic researchers in the business sector.

Sustainability and technological advancements are rapidly gaining traction on a global scale and are becoming increasingly prominent across a wide range of industries, as evidenced by current market trends. Companies are making significant investments in the research and development of smart materials that can adapt to their surroundings in real time, thereby improving their performance and productivity. The heightened interest in environmentally friendly and intelligent materials can be attributed to the recent surge in research, conferences, and patent applications in this field, highlighting the need for a comprehensive resource that can provide a thorough explanation of these developments.Green Technology and Smart Materials for Engineering Applications provides a thorough examination of smart materials, including their unique properties and applications in sustainable construction. It explores the versatile uses of green materials in different industries, emphasizing sustainable manufacturing practices and resource-efficient materials. The integration of eco-design and innovation is looked at for the creation of sustainable materials, highlighting the importance of green and smart materials in optimizing energy consumption. Additionally, the book offers insights into reuse and recycling techniques that promote circular economy principles and sustainable business models related to green and smart materials. Real-world examples and success stories are used to illustrate the environmental and economic impacts of implementing smart and green materials in various industries.This book is intended to serve as a comprehensive reference guide for academics, researchers, scholars, and professionals working in the fields of manufacturing processing, material science, and environmental engineering. The primary objective of this book is to showcase sustainability by emphasizing the diverse array of green and smart materials utilized in various engineering applications. Through this publication, readers will gain valuable insights into the importance of incorporating environmentally friendly materials into their work, ultimately contributing to a more sustainable future.

Recent decades have witnessed significant progress in zirconia‑based materials research. This comprehensive handbook explores the latest advancements and applications of these materials, providing insights into cutting‑edge manufacturing and materials science research while covering diverse industrial uses, properties, and synthesis methods. This handbook is structured into five key sections: I. Fundamentals and Materials Science, II. Industrial and Engineering Applications, III. Energy and Catalytic Applications, IV. Medical and Dental Applications, and V. Emerging Technologies.Handbook of Zirconia‑Based Materials: Manufacturing, Electrochemical, and Biomedical Engineering examines the notable characteristics and wide‑ranging applications of zirconia‑based materials. Zirconia’s distinctive properties like optical transparency, thermal stability, mechanical strength, and electrical conductivity have attracted engineers and researchers across numerous fields, including energy production, biomedical engineering, and environmental remediation. These materials find significant applications in environmental protection, sustainable energy advancement, dental implants, solid oxide fuel cells, and catalytic converters. This handbook thoroughly investigates zirconia’s crystal structure, phase transitions, and surface chemistry while exploring synthesis methodologies for nanostructured materials, from conventional to cutting‑edge approaches. It also highlights the practical industries utilizing zirconia to demonstrate its importance. This resource provides accessible insights suitable for readers with varying levels of expertise, including industrial researchers, students, professionals, and scholars in manufacturing, materials science, chemistry, and physics.

Slurry Erosion: Flow Phenomenon, Complexities, and Protection Methods presents the necessary fundamentals to understand slurry flows and erosion phenomenon. It describes the complexities in the critical assessment on minimizing erosion and the process of selecting an appropriate protection technique.Addressing new technologies for modeling and achieving reduction in slurry erosion with optimized design, the book highlights how CFD simulations and AI techniques are used to predict slurry erosion. It explores the application of slurry erosion in various industries, such as thermal power plants, hydropower plants, mining, chemical and food processing, and offshore structures. The chapters cover various problems in slurry erosion including head loss, erosion-corrosion, erosion-abrasion, leakage flow, puncture point failure, and leaching.This resource is intended to support researchers and graduate students studying slurry erosion, surface engineering, tribology, erosion and corrosion prevention.

The text addresses the importance of additive manufacturing in aerospace applications, high-temperature oxidation-resistant, fatigue-resistant, corrosion-resistant, and wear-resistant materials.Discusses advanced manufacturing techniques, like 3D printing and laser powder bed fusion for aerospace materials.Covers the characterization of the cutting edge, performance, and properties of high-entropy alloys at elevated temperatures.Focuses on the advancement of protecting coatings and claddings in the aerospace industry, including laser cladding, microwave oven claddings, plasma spray, and arc spray.Presents the materials used in the interior of aircraft, and their performance, in case of emergencies, like fire safety and sudden shocks.Illustrates phase field modeling, material design and modeling, and classical approaches used for the development of new aerospace materials.The text is primarily written for senior undergraduates, graduate students, and academic researchers in fields including mechanical engineering, aerospace engineering, industrial and production engineering, manufacturing engineering, and materials science.

Artificial Intelligence in Tribology presents the use of machine learning, AI, neural networks, and optimization algorithms in studying friction, wear, and lubrication. It explores the selection of materials, modeling of the tribo‑system, prediction of tribological behavior, and assessment and optimization of performance across numerous systems.Addressing tribological problems from macroscale to nanoparticles, this book discusses AI‑driven methods to improve productivity, detect disasters, and support sustainable engineering. Case studies from various industries, such as automotive, aerospace, renewable energy, and marine engineering, highlight the transformative impact of AI in real‑world scenarios.This book will interest researchers and graduate students studying AI integration and advances in surface engineering, tribology, and materials science.

The text explains the fundamental mechanisms and complexities involved in two-phase flow systems. It presents the physical and rheological properties of slurries, solid-liquid interactions, and the flow regimes. The book focuses on sector-specific use cases, including energy, mining, and processing systems. It highlights the use of machine learning models for predicting the rate of erosion based on experimental and material data.This book:· Focuses on modelling approaches such as computational fluid dynamics, multiphase flow solvers, and simulation-based predictive tools relevant to both academic and industrial applications. · Examines hydraulic issues associated with slurry transportation, such as pressure decline, loss of corrected energy, and the impacts of vortex production. · Explains the dynamics of slurry erosion, inspecting the mechanisms under the influence of impact forces and wear processes, as well as the behaviour of materials. · Discusses surface modification strategies, including thermal spraying, laser cladding, and surface alloying. · Demonstrates machine learning models used for predicting the rate of erosion based on experimental and material data. It is primarily written for senior undergraduates, graduate students, and academic researchers in mechanical engineering, aerospace engineering, fluid dynamics, heat transfer, manufacturing engineering, production engineering, and materials science.