Books in Physical sciences and engineering

Processing of Nanocellulose and Nanocellulose-Based Composites

1st Edition
November 1, 2025
Mohammad Jawaid + 2 more
English

The Handbook of Nanocellulose and Nanocellulose-Based Composites is a three-volume set of titles that provides comprehensive information on the emerging field of nanocellulose and its application in composite materials. The Handbook consolidates current knowledge, spanning the entire spectrum from processing, properties and characterization, right through to modern applications. Each volume is dedicated to a distinct aspect of nanocellulose research, offering in-depth insights, methodologies, and case studies. The Handbook of Nanocellulose and Nanocellulose-Based Composites: Processing (volume 1) focuses on the intricate processes involved in the production, modification, and preparation of nanocellulose and nanocellulose-based composites. It provides a comprehensive overview of techniques such as mechanical disintegration, chemical modification, and various nanocellulose isolation methods from abundant sources like wood, plants, and bacteria. Readers will gain valuable insights into the challenges and advancements in scaling up production, achieving nanocellulose dispersions, and incorporating nanocellulose into different matrix materials. The volume acts as a guide for researchers and practitioners aiming to harness the potential of nanocellulose through effective processing strategies.

Mathematical Modeling for Big Data Analytics

1st Edition
November 1, 2025
Passent El-Kafrawy + 1 more
English
Paperback
9 7 8 0 4 4 3 2 6 7 3 5 2
eBook
9 7 8 0 4 4 3 2 6 7 3 6 9

Mathematical Modelling for Big Data Analytics is a comprehensive guidebook that explores the use of mathematical models and algorithms for analyzing large and complex datasets. The book covers a range of topics, including statistical modeling, machine learning, optimization techniques, and data visualization, and provides practical examples and case studies to demonstrate their applications in real-world scenarios. Users will find a clear and accessible resource to enhance their skills in mathematical modeling and data analysis for big data analytics. Real-world examples and case studies demonstrate how to approach and solve complex data analysis problems using mathematical modeling techniques.This book will help readers understand how to translate mathematical models and algorithms into practical solutions for real-world problems. Coverage of the theoretical foundations of big data analytics, including qualitative and quantitative analytics techniques, digital twins, machine learning, deep learning, optimization, and visualization techniques make this a must have resource.

Applications of Artificial Intelligence in Removal of Emerging Contaminants

1st Edition
November 1, 2025
Mika Sillanpää + 1 more
English
Paperback
9 7 8 0 4 4 3 2 6 7 7 9 6
eBook
9 7 8 0 4 4 3 2 6 7 8 0 2

Applications of Artificial Intelligence in Removal of Emerging Contaminants: Sustainable Approach for Environmental Clean-up and Circular Economy focuses on the exploitation of various Artificial Intelligence (AI) tools to treat emerging contaminants and the restoration of contaminated sites. The book addresses critical environmental issues and challenges faced by society to meet such challenges. It highlights artificial intelligence and machine learning tools in the removal of environmental contaminants, such as industrial effluents, air, and to overcome limitations of conventional methods, predict water quality parameters and decrease the chances of error.Advanced tools, updated information, and future directions for researchers and scientists working in the bioremediation of emerging contaminants, bioenergy and reutilization of waste biomass in the production of value-added products for environmental safety are also thoroughly discussed.

Microfluidics in Chemical Engineering

1st Edition
November 1, 2025
Wei Wang + 3 more
English
Paperback
9 7 8 0 4 4 3 2 7 3 0 6 3
eBook
9 7 8 0 4 4 3 2 7 3 0 7 0

Microfluidics for Chemical Engineering: Flow and Reaction, Microreaction, On-line Detection, and Product Engineering presents the fundamentals of microfluidic flow and dispersion and provides new insights on the use of microfluidics in the field of chemical engineering. The book provides a timely, comprehensive, and detailed overview, demonstrating this state-of-the-art methodology, research advances, and classic instances, and providing insightful, forward-looking perspectives. Content ranges from flow and dispersion in microfluidics, microreaction regulation via the coalesce and transfer of droplets, to product engineering regarding controllable fabrication of microparticles and microfibers with advanced functions.The chapters clearly summarize the design concepts and general strategies involved as well as the involved mechanisms and classic instances. Instructive advice is also featured throughout on rational regulation of multiphase flows and interfaces in microfluidics, thus offering guidance for process intensification of chemical engineering. It is primarily written for advanced graduate/postdoc students and researchers chemical engineering, but with relevance to materials scientists, physical and materials (including polymer) chemists, physicists, biochemists, as well as pharmaceutical and biomedical scientists.

Metal-Oxide-Based Nanomaterials and their Advanced Environmental Applications

1st Edition
November 1, 2025
Lucas Meili + 4 more
English
Paperback
9 7 8 0 4 4 3 2 7 3 0 8 7
eBook
9 7 8 0 4 4 3 2 7 3 0 9 4

Metal-Oxide-Based Nanomaterials and their Advanced Environmental Applications addresses the application of metal-oxide-based materials in soil, water, and wastewater treatment remediation technologies. These materials are particularly promising for applications as adsorbents, catalysts, and sensors, among others. The book provides researchers, students, professors, and industry experts with fundamental and advanced information in the field of metal oxide materials for environmental applications.Metal oxides and their physical, magnetic, optical, and chemical characteristics are of increasing interest to researchers addressing soil, wastewater, groundwater, and surface water contamination. Novel materials based on metal oxides show remarkable sensitivity to alterations in their composition and structure, and lend themselves especially well to cutting-edge procedures or processes for environmental remediation.

Computational Methods for the Multiscale Modelling of Soft Matter

1st Edition
November 1, 2025
Paola Carbone + 1 more
English

Due to the hierarchical organization of morphology in soft materials and their slow dynamics, a single modelling technique does not suffice to simulate them. The wide range of modelling approaches available span many time and length scales, making it challenging for newcomers to the field to know how to critically assess the tools and to determine which is most appropriate for any given problem. This book provides a concise and clear description of a variety of simulation methods to model these ubiquitous materials. The list of techniques includes numerical and molecular modelling ones and covers several time and length scales.Along with the fundamental concepts of the theory behind the methods, a comprehensive set of examples taken from the broad pool of soft materials is included. These exemplify how, thanks to the increased computational resources nowadays available to almost any research group, computational methods have become a powerful tool to sit alongside other experimental characterizations and show their increasing relevance for the manufacturing sector. Chapters illustrate how modelling techniques can be used to aid interpretation of experimental data, and how experiments can be used to parameterise models. In addition to enabling informed decisions to be made about the modelling tools to adopt for a given problem, the book will enable those who might already be experts in one technique to transition to other tools more easily. This will become increasingly important as multiscale tools become increasingly sophisticated and sufficiently well developed to be used by more casual users of simulation tools.Bringing together all these modelling approaches and applications into one coherent volume, Computational Methods for the Multiscale Modelling of Soft Matter provides a one-stop resource that is written primarily for postgraduate students and researchers in materials science, computational physics and chemists and chemical engineering interested in learning about simulation methods for soft materials as polymers, surfactants, and colloids.

Robust Theoretical Models in Medicinal Chemistry

1st Edition
November 1, 2025
Luciana Scotti + 1 more
English
Paperback
9 7 8 0 4 4 3 2 7 4 2 0 6
eBook
9 7 8 0 4 4 3 2 7 4 2 1 3

Robust Theoretical Models in Medicinal Chemistry: QSAR, Artificial Intelligence, Machine Learning, and Deep Learning serves as a valuable resource chock full of applications extending into multiple knowledge domains. The meticulous construction of a robust model holds significance, not only in drug discovery but also in engineering, chemistry, pharmaceutical, and food-related research, illustrating the broad spectrum of fields where QSAR methodologies can be instrumental. The activities considered in QSAR span chemical measurements and biological assays, making this approach a versatile tool applicable across various scientific domains. Currently, QSAR finds extensive use in diverse disciplines, prominently in drug design and environmental risk assessment.Quantitat... Structure-Activity Relationships (QSAR) represent a concerted effort to establish correlations between structural or property descriptors of compounds and their respective activities. These physicochemical descriptors encompass a wide array of parameters, accounting for hydrophobicity, topology, electronic properties, and steric effects, and can be determined empirically or, more recently, through advanced computational methods.

Multimodal Learning Using Heterogeneous Data

1st Edition
November 1, 2025
Saeid Eslamian + 3 more
English

Multimodal Learning Using Heterogeneous Data is a comprehensive guide to the emerging field of multimodal learning, which focuses on integrating diverse data types such as text, images, and audio within a unified framework. The book delves into the challenges and opportunities presented by multimodal data and offers insights into the foundations, techniques, and applications of this interdisciplinary approach. It is intended for researchers and practitioners interested in learning more about multimodal learning and is a valuable resource for those working on projects involving data analysis from multiple modalities.The book begins with a comprehensive introduction, focusing on multimodal learning's foundational principles and the intricacies of heterogeneous data. It then delves into feature extraction, fusion techniques, and deep learning architectures tailored for multimodal data. It also covers transfer learning, pre-processing challenges, and cross-modal information retrieval. The book highlights the application of multimodal learning in specialized contexts such as sentiment analysis, data generation, medical imaging, and ethical considerations. Real-world case studies are woven into the narrative, illuminating the applications of multimodal learning in diverse domains such as natural language processing, multimedia content analysis, autonomous systems, and cognitive computing. The book concludes with an insightful exploration of multimodal data analytics across social media, surveillance, user behavior, and a forward-looking examination of future trends and practical implementations. As a collective resource, Multimodal Learning Using Heterogeneous Data illuminates the powerful utility of multimodal learning to elevate machine learning tasks while also highlighting the need for innovative solutions and methodologies. The book acknowledges the challenges associated with deep learning and the growing importance of ethical considerations in the collection and analysis of multimodal data.Overall, Multimodal Learning Using Heterogeneous Data provides an expansive panorama of this rapidly evolving field, its potential for future research and application, and its vital role in shaping machine learning's evolution.

AI and Data Science in Medical Research

1st Edition
November 1, 2025
Olfa Boubaker
English

AI and Data Science in Medical Research focuses on the integration of AI and data science into medical research, highlighting their impact on drug discovery, medical imaging, diagnostics, and genomic medicine. It addresses the acceleration of therapeutic compound discovery and optimization of drug development pipelines through AI. The volume also discusses advancements in medical imaging, including early disease detection and neuroimaging. Additionally, it covers the application of AI in genomic medicine, offering insights into personalized treatment strategies. The volume concludes with an examination of AI's role in public health surveillance, particularly in disease detection and epidemiological research.

Theoretical Foundations of Quantum Computing

1st Edition
November 1, 2025
Daowen Qiu
English

Theoretical Foundations of Quantum Computing is the essential textbook designed specifically for introductory courses in this groundbreaking discipline. Quantum computing represents a paradigm shift in how we understand computation itself. This textbook delves deep into the fundamental principles of quantum mechanics that underpin this revolutionary technology, making it an invaluable resource for both undergraduate and graduate students in computer science and related fields. Structured into eight meticulously crafted chapters, this textbook covers everything from the historical context of quantum computing to advanced theories and applications. Each chapter is designed to build upon the last, ensuring that students develop a robust understanding of both foundational concepts and cutting-edge research. Chapter 1 briefly introduces the development history, background, and current status of quantum computing, and points out its advantages and potential applications; Chapter 2 describes the basic concepts related to quantum computing and points out that classical computing is a special case of quantum computing; Chapter 3 provides an overview of linear algebra, systematically summarizing the relevant theorems on operator (matrix) decomposition and hyperoperators; Chapter 4 states the basic quantum cryptography and communication protocols; Chapter 5 elaborates on basic quantum computing models, including quantum finite automata, quantum Turing machines, and quantum circuits; Chapter 6 introduces the core content of quantum computing, including important quantum algorithms It also introduces hidden subgroup algorithms and summarizes the basic tools for designing quantum algorithms, namely quantum phase estimation method and quantum amplitude amplification method; Chapter 7 introduces the basic knowledge and methods of quantum computing complexity; Chapter 8 introduces the basic concepts and methods of quantum error correction codes, as well as their error correction principles. This textbook not only serves as a foundational resource for students but also acts as a comprehensive guide for researchers interested in quantum computing. Its clarity and thoroughness make it an excellent reference for those looking to deepen their understanding or engage in cutting-edge research.

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