Elementary Kinetic Modelling in Catalytic Reaction Engineering is a practical focused text that brings together the relevant basics for reaction engineering and shows their applications to a wide variety of examples, whilst looking at the intrinsic kinetics data acquisition, reaction mechanism elucidation, elementary step-based modelling and model-based design and optimization involved.The book aims at spanning the entire process from acquisition of the relevant data in dedicated experimental set-ups, over the proper treatment of the data and the corresponding interpretation up to the quantification of the gained understanding in a model. The latter aspect allows the reader to challenge the interpretation made of the data and design subsequent experiments or improve the interpretation/model formulation. The coverage is not just limited to the generic (theoretical) principles but will also carefully consider and explain their application to a variety of real-life applications including gas- and liquid-phase reactions, heterogeneously catalyzed reactions involving adsorption either in the Henry regime or at full saturation of the catalyst or combined homogeneous-heterogeneous reactions.Elementary Kinetic Modelling in Catalytic Reaction Engineering is written primarily for graduate students and postdoc researchers in chemical engineering or applied industrial chemistry studying chemical reaction engineering and catalysis, as well as physical chemists studying kinetics.
Recent Advances in Hemodynamics and Blood Mimetics is a comprehensive compilation of recent developments in biofluid mechanics and biomimetics, covering topics such as numerical modeling, biomedical applications of microfluidics, biomimetic flows, biomedicine applications, and organ-on-chip technology. The book explores blood hemodynamics at different scales, including application to diseases, the relationship between blood biomechanics and rheology, the mimetization of blood properties at arterial and capillary level, including the study of blood mechanical and flow properties, flow and surface properties of blood cells, and mimetization of these same properties in fluid/particle systems.These concepts are applied to the development of organ-on-chip to improve the replication of biological processes in the human body. The book organizes recent knowledge on hemodynamics and blood mimetics and is representative of the different lines of research in the field, showing an integrated view of blood biomechanics encompassing all scales to create a valuable resource where different research lines can be found and their principles understood.
Modeling and Numerical Simulation of Proton Exchange Membrane Fuel Cells: Concept, Methods, and Challenges provides a concise guide to the modeling of PEM fuel cells. The book offers detailed methodologies, codes, and algorithms on every aspect of PEM fuel cells, from cold start to degradation. Chapters cover the development, basic principles, and components of PEM fuel cells, discuss the transport phenomena and mathematical formulation of macro-scale PEM fuel cell models, single cell and stack-level models, and model validation, and explain multi-phase transport modeling in PEM fuel cells, including different multiphase models like flow in gas flow channels, porous electrodes, and multi-phase model validation.The book also addresses multiphase mixture formulation, finite-volume, direct numerical simulation, Lattice Boltzmann, and pore network models, along with a section on modeling the cold start process of PEM fuel cells, including the non-isothermal transient cold start model, reduced-dimensional transient model, and the impact of different parameters on the cold start performance. Final sections cover the degradation and lifetime modeling of PEM fuel cells, including stress-induced degradation mechanisms, physics-based and data-driven modeling methods, and coupled performance-degradation models. Finally, recent progress on multi-scale and multi-dimensional modeling of PEM fuel cells, including micro and nano-scale modeling and multi-scale coupled models, is covered.
Pulp and Paper Industry: Advanced Technologies in Wastewater Treatment provides detailed discussion on the characteristics, environmental hazards, and human health effects of pulp and paper wastewater. The book discusses their different treatment methods and related challenges. These techniques start from physical methods such as sedimentation and froth flotation, followed by physiochemical treatments including activated carbon filtration, chemical precipitation, as well as biological techniques like aerobic and anaerobic processes. The book also covers application of advanced and novel wastewater treatment techniques in pulp and paper industries, such as ozonation, photocatalysis, advanced oxidation process, electrolysis, microbial fuel cells, etc., as well as challenges of industries, economic assessments, and future perspectives of pulp and paper wastewaters treatments.
Pretreatment of Lignocellulosic Biomass for Bioenergy Production presents the latest developments in the pretreatment of recalcitrant lignocellulosic materials. With an emphasis on commercially ready and near-commercially ready technologies, the book comprehensively analyzes the physical, chemical, and biological methods for biomass pretreatment. Sections cover a systematic review of the anatomy and ultrastructure of plant cell walls, the chemical structure of cellulose, hemicelluloses, lignin, lignin-carbohydrate complexes, and the methods for their analysis. With its extensive coverage of pretreatment techniques, structural analysis, and utilization of by-products, this book serves as a valuable resource for researchers and professionals in the field of biofuel production.Additional sections delve into the various pretreatment technologies, including physical, physical-chemical, chemical, biological, and combined approaches. The advantages and disadvantages are examined, and industrial and pre-industrial applications are presented. Finally, saccharification and fermentation methods, enzyme engineering, and the utilization of by-products generated during the pretreatment and fermentation processes are covered. By-products such as xylan, 5-HMF, furfural, phenolic compounds, organic acids, and lignin are discussed in terms of their further conversion and applications.
Drug Delivery and Biomedical Applications of Porous Silicon-Based Nanocarriers delivers an up-to-date and complete overview of the range of biomedical applications for porous silicon nanomaterials, with a special emphasis on drug delivery. This book introduces the fundamentals and beneficial properties of porous silicon, including thermal properties and stabilization, photochemical and nonthermal chemical modification, protein modification, and biocompatibility. The book then builds on the systematic detailing of each biomedical application using porous silicon, such as vaccine development, drug delivery, and tissue engineering. It also contains new insights on in-vivo assessment of porous silicon, photodynamic and photothermal therapy, micro- and nanoneedles, cancer immunotherapy, and more. Drug Delivery and Biomedical Applications of Porous Silicon-Based Nanocarriers is of interest to researchers in the fields of materials science, nanotechnology, pharmaceutical science, biomedical engineering, and cancer research.
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.
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.Quantitative 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.
Machine Learning for Membrane Separation Applications covers the importance of polymeric membranes in separation processes and explains how machine learning is taking these processes to the next level. As polymeric membranes can be used for both gas and liquid separations, along with several other applications, they provide a bypass route to separation due to several fold benefits over traditional techniques. Sections cover the role of Machine Learning in membranes design and development, fouling mitigation, and filtration systems. Machine Learning in a wide variety of polymeric membranes, such as nanocomposite membranes, MOF based membranes, and disinfecting membranes are also covered.This book will serve as a useful tool for researchers in academia and industry, but will also be an ideal reference for students and teachers in membrane science and technology who are looking for new ways to develop state-of-the-art membranes and membrane technologies for liquid and gas separations, such as wastewater treatment and CO2 mitigation.
Drug Discovery and One Health Approach in Combating Infectious Diseases: A Multi-sectoral Approach to address Infections explores the intersection of drug discovery and the One Health Approach, along with the effectiveness of interdisciplinary approaches to combating infectious diseases. The book covers both holistic and innovative drug discovery methodologies and technologies such as natural compounds, harnessing genomics, proteomics, and nanotechnology. Additionally, the book reviews zoonotic diseases, vaccine development, ethical considerations, and regulatory pathways. Practice case studies demonstrate successful One Health and interdisciplinary initiatives to combating infectious disease.This catalogue of knowledge provides a toolbox of innovative and interdisciplinary solutions of complex issues in drug discovery and infectious disease. It will be a valuable resource to professionals and researchers working in the fields of biomedical sciences, pharmaceutical sciences, infectious disease research, and public health, as well as those engaged in drug discovery, development, and the management of infectious diseases.