Download Free Modeling Transport Properties And Electrochemical Performance Of Hierarchically Structured Lithium Ion Battery Cathodes Using Resistor Networks And Mathematical Half Cell Models Book in PDF and EPUB Free Download. You can read online Modeling Transport Properties And Electrochemical Performance Of Hierarchically Structured Lithium Ion Battery Cathodes Using Resistor Networks And Mathematical Half Cell Models and write the review.

Hierarchically structured active materials in electrodes of lithium-ion cells are promising candidates for increasing gravimetric energy density and improving rate capability of the system. To investigate the influence of cathode structures on the performance of the whole cell, efficient tools for calculating effective transport properties of granular systems are developed and their influence on the electrochemical performance is investigated in specially adapted cell models.
In this work, the first simulation model of oxygen depolarized cathodes (ODC), which are silver catalyst-based gas diffusion electrodes, is presented that considers the phase equilibrium of the gas-liquid interface and structure-related inhomogeneities in electrolyte distribution. By means of the model it has been identified that mass transport of water and ions in the liquid phase is a crucial factor for electrode performance and how it is influenced by the electrode structure.
During the production of fiber-reinforced thermosets, the resin material undergoes a reaction that can lead to damage. A two-stage polymerization reaction is modeled using molecular dynamics and evaluations of the system including a fiber surface are performed. In addition, a phase-field model for crack propagation in heterogeneous systems is derived. This model is able to predict crack growth where established models fail. Finally, the model is used to predict crack formation during curing.
This work presents a data mining framework applied to industrial heattreatment (bainitization and case hardening) aiming to optimize processes and reduce costs. The framework analyses factors such as material, production line, and quality assessment for preprocessing, feature extraction, and drift corrections. Machine learning is employed to devise robust prediction strategies for hardness. Its implementation in an industry pilot demonstrates the economic benefits of the framework. - This work presents a data mining framework applied to industrial heattreatment (bainitization and case hardening) aiming to optimize processes and reduce costs. The framework analyses factors such as material, production line, and quality assessment for preprocessing, feature extraction, and drift corrections. Machine learning is employed to devise robust prediction strategies for hardness. Its implementation in an industry pilot demonstrates the economic benefits of the framework.
This work aimed at designing, studying and producing the first prototypes of KIDs tailored for fusion plasma polarimetric diagnostics. Diamond was considered for the first time as substrate material for low-temperature superconducting detectors given its unmatched optical, radiation hardness and thermal qualities, properties necessary for working environments potentially saturated with radiation. This work represents a first step toward the optimization and final application of this technology.
This book is unique to be the only one completely dedicated for battery modeling for all components of battery management system (BMS) applications. The contents of this book compliment the multitude of research publications in this domain by providing coherent fundamentals. An explosive market of Li ion batteries has led to aggressive demand for mathematical models for battery management systems (BMS). Researchers from multi-various backgrounds contribute from their respective background, leading to a lateral growth. Risk of this runaway situation is that researchers tend to use an existing method or algorithm without in depth knowledge of the cohesive fundamentals—often misinterpreting the outcome. It is worthy to note that the guiding principles are similar and the lack of clarity impedes a significant advancement. A repeat or even a synopsis of all the applications of battery modeling albeit redundant, would hence be a mammoth task, and cannot be done in a single offering. The authors believe that a pivotal contribution can be made by explaining the fundamentals in a coherent manner. Such an offering would enable researchers from multiple domains appreciate the bedrock principles and forward the frontier. Battery is an electrochemical system, and any level of understanding cannot ellipse this premise. The common thread that needs to run across—from detailed electrochemical models to algorithms used for real time estimation on a microchip—is that it be physics based. Build on this theme, this book has three parts. Each part starts with developing a framework—often invoking basic principles of thermodynamics or transport phenomena—and ends with certain verified real time applications. The first part deals with electrochemical modeling and the second with model order reduction. Objective of a BMS is estimation of state and health, and the third part is dedicated for that. Rules for state observers are derived from a generic Bayesian framework, and health estimation is pursued using machine learning (ML) tools. A distinct component of this book is thorough derivations of the learning rules for the novel ML algorithms. Given the large-scale application of ML in various domains, this segment can be relevant to researchers outside BMS domain as well. The authors hope this offering would satisfy a practicing engineer with a basic perspective, and a budding researcher with essential tools on a comprehensive understanding of BMS models.
Electron backscatter diffraction is a very powerful and relatively new materials characterization technique aimed at the determination of crystallographic texture, grain boundary character distributions, lattice strain, phase identification, and much more. The purpose of this book is to provide the fundamental basis for electron backscatter diffraction in materials science, the current state of both hardware and software, and illustrative examples of the applications of electron backscatter diffraction to a wide-range of materials including undeformed and deformed metals and alloys, ceramics, and superconductors. The text has been substantially revised from the first edition, and the authors have kept the format as close as possible to the first edition text. The new developments covered in this book include a more comphrensive coverage of the fundamentals not covered in the first edition or other books in the field, the advances in hardware and software since the first edition was published, and current examples of application of electron backscatter diffraction to solve challenging problems in materials science and condensed-matter physics.
The Essential Reference for the Field, Featuring Protocols, Analysis, Fundamentals, and the Latest Advances Impedance Spectroscopy: Theory, Experiment, and Applications provides a comprehensive reference for graduate students, researchers, and engineers working in electrochemistry, physical chemistry, and physics. Covering both fundamentals concepts and practical applications, this unique reference provides a level of understanding that allows immediate use of impedance spectroscopy methods. Step-by-step experiment protocols with analysis guidance lend immediate relevance to general principles, while extensive figures and equations aid in the understanding of complex concepts. Detailed discussion includes the best measurement methods and identifying sources of error, and theoretical considerations for modeling, equivalent circuits, and equations in the complex domain are provided for most subjects under investigation. Written by a team of expert contributors, this book provides a clear understanding of impedance spectroscopy in general as well as the essential skills needed to use it in specific applications. Extensively updated to reflect the field’s latest advances, this new Third Edition: Incorporates the latest research, and provides coverage of new areas in which impedance spectroscopy is gaining importance Discusses the application of impedance spectroscopy to viscoelastic rubbery materials and biological systems Explores impedance spectroscopy applications in electrochemistry, semiconductors, solid electrolytes, corrosion, solid state devices, and electrochemical power sources Examines both the theoretical and practical aspects, and discusses when impedance spectroscopy is and is not the appropriate solution to an analysis problem Researchers and engineers will find value in the immediate practicality, while students will appreciate the hands-on approach to impedance spectroscopy methods. Retaining the reputation it has gained over years as a primary reference, Impedance Spectroscopy: Theory, Experiment, and Applications once again present a comprehensive reference reflecting the current state of the field.
This invaluable book focuses on the mechanisms of formation of a solid-electrolyte interphase (SEI) on the electrode surfaces of lithium-ion batteries. The SEI film is due to electromechanical reduction of species present in the electrolyte. It is widely recognized that the presence of the film plays an essential role in the battery performance, and its very nature can determine an extended (or shorter) life for the battery. In spite of the numerous related research efforts, details on the stability of the SEI composition and its influence on the battery capacity are still controversial. This book carefully analyzes and discusses the most recent findings and advances on this topic.
This is the first machine-generated scientific book in chemistry published by Springer Nature. Serving as an innovative prototype defining the current status of the technology, it also provides an overview about the latest trends of lithium-ion batteries research. This book explores future ways of informing researchers and professionals. State-of-the-art computer algorithms were applied to: select relevant sources from Springer Nature publications, arrange these in a topical order, and provide succinct summaries of these articles. The result is a cross-corpora auto-summarization of current texts, organized by means of a similarity-based clustering routine in coherent chapters and sections. This book summarizes more than 150 research articles published from 2016 to 2018 and provides an informative and concise overview of recent research into anode and cathode materials as well as further aspects such as separators, polymer electrolytes, thermal behavior and modelling. With this prototype, Springer Nature has begun an innovative journey to explore the field of machine-generated content and to find answers to the manifold questions on this fascinating topic. Therefore it was intentionally decided not to manually polish or copy-edit any of the texts so as to highlight the current status and remaining boundaries of machine-generated content. Our goal is to initiate a broad discussion, together with the research community and domain experts, about the future opportunities, challenges and limitations of this technology.