Products related to Covalent:
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Covalent Organic Frameworks : Chemistry, Materials and Applications
A comprehensive introduction to a groundbreaking polymer class Covalent Organic Frameworks (COFs) are materials that form two- or three-dimensional porous crystalline structures held together by strong covalent bonds.First described only in 2005, COFs have subsequently exploded as a field of study, with recent progress enormously enhancing scientific and industrial capacity for designing these organic materials by means of one-pot direct polymerization.The flexibility and predictability of these structures is part of what has given them applications in semiconductor construction, catalysis, energy storage, and more.Covalent Organic Frameworks: Chemistry, Materials, and Applications (2V set) provides a unique, comprehensive introduction to COFs and their chemistry, materials, and applications.It outlines the fundamentals of COF design, synthesis, and applications, offering a broad overview of both the origins of this thriving field and its many more recent developments.It equips readers with the tools to tailor COF design and production to a limitless range of potential scientific and industrial needs.Covalent Organic Frameworks readers will also find: Detailed treatment of design, synthesis, and computational approaches for a variety of specific COFsUnique comprehensive approach covers all possible reader needs in two accessible volumesDiscussion of connections between COF polymer chemistry and other fields including organic chemistry, computational chemistry, photochemistry, and more Covalent Organic Frameworks is a useful reference for organic chemists, materials scientists, polymer chemists, structural chemists, and more.
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Non-covalent Interactions in Coordination and Organometallic Chemistry
Non-covalent interactions in coordination and organometallic compounds (hydrogen, halogen, chalcogen, pnictogen, tetrel, and semi-coordination bonds; agosic and anagosic interactions; stacking, anion-/cation-Ï€ interactions; metallophilic interactions, etc.) are topical in modern chemistry, materials science, crystal engineering, and related fields of knowledge. Both experimental and theoretical methods are widely used for investigations of the nature and various properties of such weak contacts in gas, liquid, and solid states. Non-covalent interactions could be the driving force to design smart materials with valuable redox, electronic, mechanical, magnetic, and optical properties, which is promising for the manufacture of LEDs, photovoltaic cells of solar power plants, porous structures, sensors, battery cells, and liquid crystals.This Special Issue highlights and presents an overview of modern trends in non-covalent interactions in coordination and organometallic compounds, and bringing various different types to the attention of the scientific community.
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Data Analytics & Visualization All-in-One For Dummies
Install data analytics into your brain with this comprehensive introduction Data Analytics & Visualization All-in-One For Dummies collects the essential information on mining, organizing, and communicating data, all in one place.Clocking in at around 850 pages, this tome of a reference delivers eight books in one, so you can build a solid foundation of knowledge in data wrangling.Data analytics professionals are highly sought after these days, and this book will put you on the path to becoming one.You’ll learn all about sources of data like data lakes, and you’ll discover how to extract data using tools like Microsoft Power BI, organize the data in Microsoft Excel, and visually present the data in a way that makes sense using a Tableau.You’ll even get an intro to the Python, R, and SQL coding needed to take your data skills to a new level.With this Dummies guide, you’ll be well on your way to becoming a priceless data jockey. Mine data from data sourcesOrganize and analyze data Use data to tell a story with TableauExpand your know-how with Python and R New and novice data analysts will love this All-in-One reference on how to make sense of data.Get ready to watch as your career in data takes off.
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Spatial Analysis with R : Statistics, Visualization, and Computational Methods
In the five years since the publication of the first edition of Spatial Analysis: Statistics, Visualization, and Computational Methods, many new developments have taken shape regarding the implementation of new tools and methods for spatial analysis with R.The use and growth of artificial intelligence, machine learning and deep learning algorithms with a spatial perspective, and the interdisciplinary use of spatial analysis are all covered in this second edition along with traditional statistical methods and algorithms to provide a concept-based problem-solving learning approach to mastering practical spatial analysis.Spatial Analysis with R: Statistics, Visualization, and Computational Methods, Second Edition provides a balance between concepts and practicums of spatial statistics with a comprehensive coverage of the most important approaches to understand spatial data, analyze spatial relationships and patterns, and predict spatial processes.New in the Second Edition: Includes new practical exercises and worked-out examples using R Presents a wide range of hands-on spatial analysis worktables and lab exercises All chapters are revised and include new illustrations of different concepts using data from environmental and social sciences Expanded material on spatiotemporal methods, visual analytics methods, data science, and computational methods Explains big data, data management, and data miningThis second edition of an established textbook, with new datasets, insights, excellent illustrations, and numerous examples with R, is perfect for senior undergraduate and first-year graduate students in geography and the geosciences.
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What is covalent development?
Covalent development is a term used in the context of software development to describe a collaborative approach to building and maintaining software. It involves multiple developers working together on the same codebase, using version control systems to manage changes and updates. Covalent development emphasizes communication, teamwork, and shared responsibility for the code, leading to a more efficient and cohesive development process. This approach allows for greater flexibility and adaptability in responding to changes and challenges in the development process.
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What are covalent bonds?
Covalent bonds are a type of chemical bond formed between two atoms when they share one or more pairs of electrons. This sharing of electrons allows both atoms to achieve a more stable electron configuration, typically by filling their outermost energy levels. Covalent bonds are typically found in molecules and are responsible for holding the atoms together to form the structure of the molecule. These bonds can be either polar, where the shared electrons are not equally distributed between the atoms, or nonpolar, where the shared electrons are equally distributed.
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What is a covalent bond?
A covalent bond is a type of chemical bond that involves the sharing of electron pairs between atoms. This sharing of electrons allows each atom to achieve a more stable electron configuration, typically by filling their outermost energy level. Covalent bonds are typically found in molecules and are stronger than other types of chemical bonds, such as ionic bonds. The number of shared electrons can vary, leading to different types of covalent bonds, such as single, double, or triple bonds.
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What is spatial visualization ability?
Spatial visualization ability refers to the capacity to mentally manipulate and comprehend spatial relationships between objects. Individuals with strong spatial visualization skills can easily visualize and understand how objects relate to each other in space, such as rotating or manipulating shapes in their mind. This ability is crucial in various fields such as engineering, architecture, and mathematics, as it allows individuals to solve complex problems and understand spatial concepts more effectively. Improving spatial visualization ability can enhance problem-solving skills and overall cognitive performance.
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Spatial Epidemiological Approaches in Disease Mapping and Analysis
Containing method descriptions and step-by-step procedures, the Spatial Epidemiological Approaches in Disease Mapping and Analysis equips readers with skills to prepare health-related data in the proper format, process these data using relevant functions and software, and display the results as mapped or statistical summaries.Describing the wide range of available methods and key GIS concepts for spatial epidemiology, this book illustrates the utilities of the software using real-world data.Additional topics include geographic data models, address matching, geostatistical analysis, universal kriging, point pattern analysis, kernel density, spatio-temporal display, and disease surveillance.
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Crime Mapping and Spatial Data Analysis using R
Crime mapping and analysis sit at the intersection of geocomputation, data visualisation and cartography, spatial statistics, environmental criminology, and crime analysis.This book brings together relevant knowledge from these fields into a practical, hands-on guide, providing a useful introduction and reference material for topics in crime mapping, the geography of crime, environmental criminology, and crime analysis.It can be used by students, practitioners, and academics alike, whether to develop a university course, to support further training and development, or to hone skills in self-teaching R and crime mapping and spatial data analysis.It is not an advanced statistics textbook, but rather an applied guide and later useful reference books, intended to be read and for readers to practice the learnings from each chapter in sequence.In the first part of this volume we introduce key concepts for geographic analysis and representation and provide the reader with the foundations needed to visualise spatial crime data.We then introduce a series of tools to study spatial homogeneity and dependence.A key focus in this section is how to visualise and detect local clusters of crime and repeat victimisation.The final chapters introduce the use of basic spatial models, which account for the distribution of crime across space.In terms of spatial data analysis the focus of the book is on spatial point pattern analysis and lattice or area data analysis.
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An Introduction to R for Spatial Analysis and Mapping
The ever-expanding availability of spatial data continues to revolutionise research.This book is your go-to guide to getting the most out of handling, mapping and analysing location-based data. Without assuming prior knowledge of GIS, geocomputation or R, this book helps you understand spatial analysis and mapping and develop your programming skills, from learning about scripting and writing functions to point pattern analysis and spatial attribute analysis. The book:Illustrates approaches to analysis on a range of datasets that are new to this edition. Enables you to put your skills into practice with embedded exercises and over 30 self-test questions. Showcases the possibilities of using spatial analysis to explore spatial inequalities. Whether you’re an R novice or experienced user, this book equips upper undergraduates, postgraduates and researchers with the tools needed for spatial data handling and rich analysis.
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Advanced video mapping techniques - Spatial Augmented Reality applied to cultural heritage
Spatial Augmented Reality applied to cultural heritage.
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Can you explain the covalent bond?
A covalent bond is a type of chemical bond that involves the sharing of electron pairs between atoms. This sharing of electrons allows each atom to achieve a full outer electron shell, making the atoms more stable. Covalent bonds are typically formed between nonmetal atoms, and the strength of the bond is determined by the number of shared electrons and the distance between the nuclei of the atoms. Covalent bonds can be either polar or nonpolar, depending on the electronegativity difference between the atoms involved.
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What does "covalent" mean in chemistry?
In chemistry, "covalent" refers to a type of chemical bond that involves the sharing of electron pairs between atoms. This type of bond is formed between nonmetal atoms and is characterized by the atoms sharing electrons in order to achieve a stable electron configuration. Covalent bonds are typically strong and result in the formation of molecules.
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Is covalent bonding a difficult topic?
Covalent bonding can be a challenging topic for some students due to its abstract nature and the need to understand concepts such as electron sharing and molecular geometry. However, with proper explanation and practice, students can grasp the fundamentals of covalent bonding. It is important to break down the concepts into simpler parts and provide real-world examples to help students understand the concept better. With patience and practice, students can overcome the difficulties associated with covalent bonding.
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What is a non-covalent bond?
A non-covalent bond is a type of chemical bond that does not involve the sharing of electrons between atoms. Instead, non-covalent bonds are formed through electrostatic interactions, such as hydrogen bonding, van der Waals forces, and ion-dipole interactions. These bonds are generally weaker than covalent bonds and can be easily broken under certain conditions.
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