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High Accuracy Computational Methods For Lithium Ion Battery Materials
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Book Synopsis High Accuracy Computational Methods for Lithium Ion Battery Materials by : Eric Richard Fadel
Download or read book High Accuracy Computational Methods for Lithium Ion Battery Materials written by Eric Richard Fadel and published by . This book was released on 2020 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ongoing research to improve the performance of Lithium-ion batteries has required the study of increasingly complex physical and chemical phenomena. In this context, the use of computational tools to quantitatively assess these phenomena has proven crucial for advancing the Lithium-ion battery technology. However, recent areas of research, ranging from studying the di↵diffusion of Lithium ions across solid polymer or ionic salt electrolytes, to the calculation of the voltage curve and discharge rate for complex transition metal oxide electrodes, has pushed Lithium-ion battery research beyond the framework of common computational methods, compromising the accuracy of these tools. Thus, there is an increasing need to use more accurate computational tools, or develop new ones, that could still be used in practice to design battery materials. This project presents how more accurate methods can be used to compute voltage curves for Lithium-ion cathode materials, determine the voltage stability of organic electrolyte, or predict the conductivity of di↵different electrolyte materials. The motivation for the use of higher accuracy methods is emphasized for each application by showing the limitations of commonly used methods. In particular, the achieved accuracy enables an enhanced understanding of the specific, complex physical and chemical phenomena at the heart of Lithium-ion battery limitations, which is crucial to the design of better battery materials.
Book Synopsis Computational Design of Battery Materials by : Dorian A. H. Hanaor
Download or read book Computational Design of Battery Materials written by Dorian A. H. Hanaor and published by Springer Nature. This book was released on with total page 589 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Computational Methods to Assist in Material Discovery by : Yushan Zhang
Download or read book Computational Methods to Assist in Material Discovery written by Yushan Zhang and published by . This book was released on 2019 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Computational Design of Battery Materials by : Dorian A. H. Hanaor
Download or read book Computational Design of Battery Materials written by Dorian A. H. Hanaor and published by Springer. This book was released on 2024-03-09 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents an essential survey of the state of the art in the application of diverse computational methods to the interpretation, prediction, and design of high-performance battery materials. Rechargeable batteries have become one of the most important technologies supporting the global transition from fossil fuels to renewable energy sources. Aided by the growth of high-performance computing and machine learning technologies, computational methods are being applied to design the battery materials of the future and pave the way to a more sustainable energy economy. In this contributed collection, leading battery material researchers from across the globe share their methods, insights, and expert knowledge in the application of computational methods for battery material design and interpretation. With chapters featuring an array of computational techniques applied to model the relevant properties of cathodes, anodes, and electrolytes, this book provides the ideal starting point for any researcher looking to integrate computational tools in the development of next-generation battery materials and processes.
Book Synopsis Reactive Molecular Dynamics Simulations of Lithium Secondary Batteries - Interfaces and Electrodes by : Md Mahbubul Islam
Download or read book Reactive Molecular Dynamics Simulations of Lithium Secondary Batteries - Interfaces and Electrodes written by Md Mahbubul Islam and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the last two decades, lithium-based batteries have revolutionized the energy storage technologies. Li-ion batteries have found widespread use in portable electronics and electric vehicle applications. However, a detailed understanding of the battery chemistry, especially the formation of a solid electrolyte interphase (SEI)a thin passivation layer which is generated during the first charge cycle due to the reduction of electrolytesis still elusive. The mass scale commercialization of electric vehicles requires the storage capacity beyond the conventional Li-ion batteries, which spurred research interests towards Li-S technologies. Li-S batteries are attractive for their very high capacity and energy density, but their commercial application has been thwarted due to several critical limitations stemming from electrolyte dissociation chemistry and electrode material properties. To investigate the current issues associated with the Li-ion and Li-S batteries and to find possible countermeasures, we used both a newly developed computational tool eReaxFF and the standard ReaxFF reactive molecular dynamics simulations in the following research areas:1) We developed a computational method, eReaxFF, for simulating explicit electrons within the framework of the standard ReaxFF reactive force field method. We treat electrons explicitly in a pseudoclassical manner that enables simulation several orders of magnitude faster than quantum chemistry (QC) methods, while retaining the ReaxFF transferability. We describe in this thesis the fundamental concepts of the eReaxFF method, and the integration of the Atom-condensed Kohn-Sham DFT approximated to second order (ACKS2) charge calculation scheme into the eReaxFF. We trained our force field to capture electron affinities (EA) of various species. As a proof-of-principle, we performed a set of molecular dynamics (MD) simulations with an explicit electron model for representative hydrocarbon radicals. We establish a good qualitative agreement of EAs of various species with experimental data, and MD simulations with eReaxFF agree well with the corresponding Ehrenfest dynamics simulations. The standard ReaxFF parameters available in literature are transferrable to the eReaxFF method. The computationally economic eReaxFF method will be a useful tool for studying large-scale chemical and physical systems with explicit electrons as an alternative to computationally demanding QC methods. 2) A detailed understanding of the mechanism of the formation of SEI is crucial for designing high capacity and longer lifecycle lithium-ion batteries. The anode side SEI is primarily comprised of the reductive dissociation products of the electrolyte molecules. Any accurate computational method to study the reductive decomposition mechanism of electrolyte molecules is required to possess an explicit electronic degree of freedom. In this study, we employed our newly developed eReaxFF method to investigate the major reduction reaction pathways of SEI formation with ethylene carbonate (EC) based electrolytes. In the eReaxFF method, a pseudo-classical treatment of electrons provides the capability to simulate explicit electrons in a complex reactive environment. Our eReaxFF predicted simulation results of the EC decomposition reactions are in good agreement with the quantum chemistry data available in literature. Our MD simulations capture the mechanism of the reduction of the EC molecule due to the electron transfer from lithium, ring opening of the EC to generate EC-/Li+ radicals, and subsequent radical termination reactions. Our results indicate that the eReaxFF method is a useful tool for large-scale simulations to describe redox reactions occurring at electrode-electrolyte interfaces where quantum chemistry based methods are not viable due to their high computational requirement.3) Li-S batteries still suffer several formidable performance degradation issues that impede their commercial applications. The lithium negative electrode yields high anodic capacity, but it causes dendrite formation and raises safety concerns. Furthermore, the high reactivity of lithium is accountable for electrolyte decomposition. To investigate these issues and possible countermeasures, we used ReaxFF reactive molecular dynamics simulations to elucidate anode-electrolyte interfacial chemistry and utilized an ex-situ anode surface treatment with Teflon coating. In this study, we employed Li/SWCNT (single-wall carbon nanotube) composite anode instead of lithium metal and tetra (ethylene glycol) dimethyl ether (TEGDME) as electrolyte. We find that at a lithium rich environment of the anode-electrolyte interface, electrolyte dissociates and generates ethylene gas as a major reaction product, while utilization of Teflon layer suppresses the lithium reactivity and reduces electrolyte decomposition. Lithium discharge from the negative electrode is an exothermic event that creates local hot spots at the interfacial region and expedites electrolyte dissociation reaction kinetics. Usage of Teflon dampens initial heat flow and effectively reduces lithium reactivity with the electrolyte. 4) Sulfur cathodes of Li-S batteries undergo a noticeable volume variation upon cycling, which induces stress. In spite of intensive investigation of the electrochemical behavior of the lithiated sulfur compounds, their mechanical properties are not very well understood. In order to fill this gap, we developed a ReaxFF interatomic potential to describe Li-S interactions and performed MD simulations to study the structural, mechanical, and kinetic behavior of the amorphous lithiated sulfur (a-LixS) compounds. We examined the effect of lithiation on material properties such as ultimate strength, yield strength, and Youngs modulus. Our results suggest that with increasing lithium content, the strength of lithiated sulfur compounds improves, although this increment is not linear with the lithiation. The dependence of the mechanical properties and failure behavior on the loading rate of the amorphous lithiated sulfur compositions was also studied. The diffusion coefficients of both lithium and sulfur were computed for the a-LixS system at various stages of Li-loading. A Grand canonical Monte Carlo (GCMC) scheme was used to calculate the open circuit voltage (OCV) profile during cell discharge. The calculated OCV is consistent with prior experimental results. Our ReaxFF potentials also reproduced experimentally observed volume expansion of a-LixS phases upon lithiation. The Li-S binary phase diagram was constructed using genetic algorithm based tools. These simulation results provide insight into the behavior of sulfur-based cathode materials that are needed for developing high-performance lithium-sulfur batteries.
Book Synopsis Advanced Characterization and Modeling of Next Generation Lithium Ion Electrodes and Interfaces by : Thomas Andrew Wynn
Download or read book Advanced Characterization and Modeling of Next Generation Lithium Ion Electrodes and Interfaces written by Thomas Andrew Wynn and published by . This book was released on 2020 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lithium ion batteries have proven to be a paradigm shifting technology, enabling high energy density storage to power the handheld device and electric automotive revolutions. However relatively slow progress toward increased energy and power density has been made since the inception of the first functional lithium ion battery. Materials under consideration for next generation lithium ion batteries include anionic-redox-active cathodes, solid state electrolytes, and lithium metal anodes. Li-rich cathodes harness anionic redox, showing increased first charge capacity well beyond the redox capacity of traditional transition metal oxides, though suffer from severe capacity and voltage fade after the first cycle. This is in part attributed to oxygen evolution, driving surface reconstruction. Solid-state electrolytes (SSEs) offer the potential for safer devices, serving as physical barriers for dendrite penetration, while hoping to enable the lithium metal anode. The lithium metal naturally exhibits the highest volumetric energy density of all anode materials. Here, we employ simulation and advanced characterization methodologies to understand the fundamental properties of a variety of next generation lithium ion battery materials and devices leading to their successes or failures. Using density functional theory, the effect of cationic substitution on the propensity for oxygen evolution was explored. Improvement in Li-rich cathode performance is predicted and demonstrated through doping of 4d transition metal Mo. Next, lithium phosphorus oxynitride (LiPON), an SSE utilized in thin film batteries, was explored. LiPON has proven stable cycling against lithium metal anodes, though its stability is poorly understood. RF sputtered thin films of LiPON are examined via spectroscopic computational methods and nuclear magnetic resonance to reveal its atomic structure, ultimately responsible for its success as a thin film solid electrolyte. A new perspective on LiPON is presented, emphasizing its glassy nature and lack of long-range connectivity. Progress toward in situ methodologies for solid-state interfaces is described, and a protocol for FIB-produced nanobatteries is developed. Cryogenic methodologies are applied to a PEO/NCA composite electrode. Cryogenic focused ion beam was shown to preserve polymer structure and morphology, enabling accurate morphological quantification and preserving the crystallinity, as observed via TEM. Last, development of in situ solid-state interface characterization is discussed.
Book Synopsis First-principles Simulations of Solid State Battery Materials by : Jason D. Howard
Download or read book First-principles Simulations of Solid State Battery Materials written by Jason D. Howard and published by . This book was released on 2018 with total page 102 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this work materials with possible applications in all solid state Li-ion batteries are explored using computational methods within the framework of density functional theory and kinetic Monte Carlo. The density functional theory simulations use fundamental quantum mechanics along with some approximations to produce accurate models of real materials. A smaller portion of the work uses kinetic Monte Carlo to provide qualitative information about the convergence properties of transport coefficients. The materials Li(subscript 2+x)SnO3 and Li(subscript 2+x)SnS3 are studied in the context of electrodes for Li-ion batteries. Their structures are calculated, conduction pathways for the Li-ions predicted, open cell voltages calculated, and reactivity with lithium at the surface studied. The results for these materials provided insight into existing experimental data from the literature and made predictions for open cell voltages that had not yet been measured. The materials Li4SnS4, Li2OHCl, and Li2OHBr are studied in the context of solid state electrolytes for Li-ion batteries. The structural properties are explored for some materials by calculating Helmholtz free energies to help understand temperature dependent phases. First principles molecular dynamics are performed on some of these materials to gain insight into the mechanisms for Li-ion diffusion, which is related to the Li-ion conductivity. The molecular dynamics simulations of these materials are also used to calculate order parameters, such as time averaged site occupancies, which provide insight into temperature dependent aspects of their structure. The computations using kinetic Monte Carlo are limited to the study of the convergence properties of transport coefficients on a lattice equivalent to the Li lattice of Li2OHCl. These Monte Carlo simulations provide critical insight on the level of statistics needed to converge the transport coefficients related to ionic conductivity. As a whole the simulations in this research provide atomistic level knowledge of real world energy storage materials.
Book Synopsis High-throughput Data Mined Prediction of Inorganic Compounds and Computational Discovery of New Lithium-ion Battery Cathode Materials by : Geoffroy T. F. Hautier
Download or read book High-throughput Data Mined Prediction of Inorganic Compounds and Computational Discovery of New Lithium-ion Battery Cathode Materials written by Geoffroy T. F. Hautier and published by . This book was released on 2011 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ability to computationally predict the properties of new materials, even prior to their synthesis, has been made possible due to the current accuracy of modern ab initio techniques. In some cases, high-throughput computations can be used to create large data sets of potential compounds and their computed properties. However, regardless of the field of application, such a computational high-throughput approach faces a major problem: to be relevant, the properties need to be computed on compounds (i.e., stoichiometries and crystal structures) that will be stable enough to be synthesized. In this thesis, we address this compound prediction problem through a combination of data mining and high-throughput Density Functional Theory. We first describe a method based on correlations between crystal structure prototypes that can be used with a limited computational budget to search for new ternary oxides. In addition, for the treatment of sparser data regions such as quaternaries, a new algorithm based on the data mining of ionic substitutions is proposed and analyzed. The second part of this thesis demonstrates the application of this highthroughput ab initio computing technique to the lithium-ion battery field. Here, we describe a large-scale computational search for novel cathode materials with specific battery properties, which enables experimentalists to focus on only the most promising chemistries. Finally, to illustrate the potential of new compound computational discovery using this approach, a novel chemical class of cathode materials, the carbonophosphates, is presented along with synthesis and electrochemical results.
Book Synopsis Multi-scale Computation Methods: Their Applications in Lithium-ion Battery Research and Development*Project Supported by the National Natural Science Foundation of China (Grant Nos. 51372228 and 11234013), the National High Technology Research and Development Program of China (Grant No. 2015AA034201), and Shanghai Pujiang Program, China (Grant No. 14PJ1403900). by :
Download or read book Multi-scale Computation Methods: Their Applications in Lithium-ion Battery Research and Development*Project Supported by the National Natural Science Foundation of China (Grant Nos. 51372228 and 11234013), the National High Technology Research and Development Program of China (Grant No. 2015AA034201), and Shanghai Pujiang Program, China (Grant No. 14PJ1403900). written by and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Based upon advances in theoretical algorithms, modeling and simulations, and computer technologies, the rational design of materials, cells, devices, and packs in the field of lithium-ion batteries is being realized incrementally and will at some point trigger a paradigm revolution by combining calculations and experiments linked by a big shared database, enabling accelerated development of the whole industrial chain. Theory and multi-scale modeling and simulation, as supplements to experimental efforts, can help greatly to close some of the current experimental and technological gaps, as well as predict path-independent properties and help to fundamentally understand path-independent performance in multiple spatial and temporal scales.
Book Synopsis Computational Approaches to Energy Materials by : Richard Catlow
Download or read book Computational Approaches to Energy Materials written by Richard Catlow and published by John Wiley & Sons. This book was released on 2013-04-03 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of materials for clean and efficient energy generation and storage is one of the most rapidly developing, multi-disciplinary areas of contemporary science, driven primarily by concerns over global warming, diminishing fossil-fuel reserves, the need for energy security, and increasing consumer demand for portable electronics. Computational methods are now an integral and indispensable part of the materials characterisation and development process. Computational Approaches to Energy Materials presents a detailed survey of current computational techniques for the development and optimization of energy materials, outlining their strengths, limitations, and future applications. The review of techniques includes current methodologies based on electronic structure, interatomic potential and hybrid methods. The methodological components are integrated into a comprehensive survey of applications, addressing the major themes in energy research. Topics covered include: • Introduction to computational methods and approaches • Modelling materials for energy generation applications: solar energy and nuclear energy • Modelling materials for storage applications: batteries and hydrogen • Modelling materials for energy conversion applications: fuel cells, heterogeneous catalysis and solid-state lighting • Nanostructures for energy applications This full colour text is an accessible introduction for newcomers to the field, and a valuable reference source for experienced researchers working on computational techniques and their application to energy materials.
Book Synopsis Multiscale Modeling, Reformulation, and Efficient Simulation of Lithium-ion Batteries by : Paul Wesley Clairday Northrop
Download or read book Multiscale Modeling, Reformulation, and Efficient Simulation of Lithium-ion Batteries written by Paul Wesley Clairday Northrop and published by . This book was released on 2014 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lithium-ion batteries are ubiquitous in modern society, ranging from relatively low-power applications, such as cell phones, to very high demand applications such as electric vehicles and grid storage. The higher power and energy density of lithium-ion batteries compared to other forms of electrochemical energy storage makes them very popular in such a wide range of applications. In order to engineer improved battery design and develop better control schemes, it is important to understand internal and external battery behavior under a variety of possible operating conditions. This can be achieved using physical experiments, but those can be costly and time consuming, especially for life-studies which can take years to perform. Here using mathematical models based on porous electrode theory to study the internal behavior of lithium-ion batteries is examined. As the physical phenomena which govern battery performance are described using several nonlinear partial differential equations, simulating battery models can quickly become computationally expensive. Thus, much of this work focuses on reformulating the battery model to improve simulation efficiency, allowing for use to solve problems which require many iterations to converge (e.g. optimization), or in applications which have limited computational resources (e.g. control). Computational time is improved while maintaining accuracy by using a coordinate transformation and orthogonal collocation to reduce the number of equations which must be solved using the method of lines. Orthogonal collocation is a spectral method which approximates all dependent variables as a series solution of trial functions. This approach discretizes the spatial derivatives with higher order accuracy than standard finite difference approach. The coefficients are determined by requiring the governing equation be satisfied at specified collocation points, resulting in a system of differential algebraic equations (DAEs) which must be solved with time as the only differential variable. The system of DAEs can be solved using standard time-adaptive integrating solvers. The error and simulation time of the battery model of orthogonal collocation is analyzed. The improved computational efficiency allows for more physical phenomena to be considered in the reformulated model. Lithium-ion batteries exposed to high temperatures can lead to internal damage and capacity fade. In extreme cases this can lead to thermal runaway, a dangerous scenario in which energy is rapidly released. In the other end of the temperature spectrum, low temperatures can significantly impede performance by increasing diffusion resistance. Although accounting for thermal effects increases the computational cost, the model reformulation allows for these important phenomena to be considered in single cell as well as 2D and multicell stack battery models. The growth of the solid electrolyte interface (SEI) layer contributes to capacity fade by means of a side reaction which removes lithium from the system irreversibly as well as increasing the resistance of the transfer lithium-ion from the electrolyte to the active material. As the reaction kinetics are not well understood, several proposed mechanisms are considered and implemented into the continuum reformulated model. The effects of SEI layer growth on a lithium-ion cell over 10,000 cycles is simulated and analyzed. Furthermore, a kinetic Monte Carlo model is developed and implemented to study the heterogeneous growth of the solid electrolyte layer. This is a stochastic approach which considers lithium-ion diffusion, intercalation, and side reactions. As millions of individual time steps may be performed for a single cycle, it is very computationally expensive, but allows for simulation of surface phenomena which are ignored in continuum models.
Book Synopsis Towards a Systems-level Understanding of Battery Systems by : Akshay Subramaniam
Download or read book Towards a Systems-level Understanding of Battery Systems written by Akshay Subramaniam and published by . This book was released on 2021 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: Current imperatives of electrification and decarbonization entail significant improvements in energy density, performance, and cost metrics for battery technology. This has motivated active research into new materials, cell designs, and external controls to ensure safe and efficient operation. Modeling and simulation approaches have a powerful complementary function in this regard, most notably exemplified by the models for Lithium-ion batteries by Newman and co-workers. The overarching theme of this dissertation is thus the development and application of electrochemical modeling approaches at multiple scales in problems relevant to the abovementioned contexts. At the systems level, the development of more intelligent and powerful Battery Management Systems is enabled by fast electrochemical models, which must balance competing considerations of accuracy, computational efficiency, and ease of parameterization. To this end, we report a rigorous and generalized methodology for "upscaling" continuum electrochemical models. This approach, based on the visualization of a battery as Tanks-in-Series, has been demonstrated for both Lithium-ion and more complex Lithium-sulfur batteries. With respect to full models, voltage prediction errors below 20 mV are achieved for high-energy cells in most practical cases. 30 mV errors are achieved for aggressive conditions of high-rate operation at sub-zero ambient temperatures, illustrating their practical utility. This approach results in improved computational speed since each conservation law is replaced by a relatively simple volume-averaged differential or algebraic equation. For examples of large-scale problems, this leads to 10x savings in computation time over fast implementations of conventional models, illustrating competitiveness for real-time applications. In the development of next-generation chemistries, continuum models can serve as a framework for the analysis and interpretation of experimental data, while providing design guidance and helping determine desirable operating regimes. Electrochemical phenomena at different length and time scales are manifested during operation through voltage and temperature signatures, cycle life, and coulombic efficiency. Optimization of cell-level metrics is thus predicated on their correlation with the internal electrochemistry. This entails the integration of electrochemical models at different levels of detail in a computationally efficient and robust manner. To this end, the second half of this dissertation describes our efforts to develop a simulation framework for the modeling of Lithium-metal systems. We first describe a robust computational method to simulate Poisson Nernst Planck (PNP) models for Lithium symmetric cells characterized by thin double layers. This can be leveraged in applications where computational efficiency is of salience, such as cycling simulations and parameterization by coupling kinetic models of interest. This is demonstrated by a systems level method, enabling the quick evaluation of candidate mechanisms appropriately expressed as time-varying rate constants, making it useful for understanding the phenomena underpinning voltage transitions in Lithium symmetric cells. This is followed by a description of a preliminary electrochemical-mechanical model for Li metal interfaces, which is expected to serve as basis for more sophisticated electrochemical-mechanical models for Li metal systems operating under external pressure. We expect these approaches to advance fundamental understanding and design of Li-metal batteries, while creating accessible computational tools to complement experimental studies. Taken together, these contributions are envisaged to advance the knowledge base for model-based design as well as Battery Management Systems, particularly in anticipation of the commercialization of emerging battery chemistries.
Book Synopsis Multidimensional Lithium-Ion Battery Status Monitoring by : Shunli Wang
Download or read book Multidimensional Lithium-Ion Battery Status Monitoring written by Shunli Wang and published by CRC Press. This book was released on 2022-12-28 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multidimensional Lithium-Ion Battery Status Monitoring focuses on equivalent circuit modeling, parameter identification, and state estimation in lithium-ion battery power applications. It explores the requirements of high-power lithium-ion batteries for new energy vehicles and systematically describes the key technologies in core state estimation based on battery equivalent modeling and parameter identification methods of lithium-ion batteries, providing a technical reference for the design and application of power lithium-ion battery management systems. Reviews Li-ion battery characteristics and applications. Covers battery equivalent modeling, including electrical circuit modeling and parameter identification theory Discusses battery state estimation methods, including state of charge estimation, state of energy prediction, state of power evaluation, state of health estimation, and cycle life estimation Introduces equivalent modeling and state estimation algorithms that can be applied to new energy measurement and control in large-scale energy storage Includes a large number of examples and case studies This book has been developed as a reference for researchers and advanced students in energy and electrical engineering.
Book Synopsis Better Multivalent Battery Materials Through Diffusion High-throughput Computations by : Ziqin Rong
Download or read book Better Multivalent Battery Materials Through Diffusion High-throughput Computations written by Ziqin Rong and published by . This book was released on 2016 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt: Accelerating the discovery of advanced materials is essential for human beings. However, the traditional trial-and-error way of developing materials is often very empirical and time- consuming. In 2011, the launch of Materials Genome Initiative marked a large-scale collaboration between computer scientists and materials scientists to deploy proven computational methods to predict, screen, and optimize materials at an unparalleled scale and rate. This thesis is based on this idea. Finding a suitable cathode material for Mg batteries has been one of the key challenges to the next-generation multi-valent battery technology. In this thesis, a high-throughput computation system is proposed to solve such problem. I tested the high-throughput structures applying traditional NEB calculations schemes and find out it is very different to scale traditional NEB method to a high-throughput application. Then I proposed a new scheme for estimating migration minimum- energy path (MEP) geometry and energetics (PathFinder and ApproxNEB). By testing our methodology against standard NEB calculations and literature values, we find that the PathFinder algorithm can reliably predict the geometry of cation migration MEP within 0.2 Å at negligible computational cost. Furthermore, we find that the ApproxNEB calculation scheme yields activation barriers for migration within an error bound of 20 meV while using significantly fewer computational resources than NEB. We envision that our methods can be used to accelerate NEB calculations, as well as to provide a robust estimation criterion for migration barriers in ionic materials for highthroughput computational screening of materials. Based upon these two newly developed methods, coupled with EndPointFinder, I developed two functional high-throughput applications (ApproxNEB for estimating migration barriers and PathFinder for calculating migration geometric paths), and have already put PathFinder high-throughput system into production and calculate around 2000 structures.
Book Synopsis Computational Investigation of Materials for Energy Storage Applications by : Naman Katyal
Download or read book Computational Investigation of Materials for Energy Storage Applications written by Naman Katyal and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The need for sustainable, economical, and high energy density rechargeable batteries are mandatory to develop next generation consumer electronics, transportation, and stationary energy devices to meet the growing energy demands of the world. In order to meet those challenges, the fundamental understanding of thermodynamics and diffusion processes in battery materials can help achieve the current goals. Atomic-scale simulations using density functional theory coupled with experimental characterization techniques have the capabilities to reveal local atomic environment of battery electrodes and electrolytes which is directly related to the ionic conductivity, stability of electrode-electrolyte interphase, electrode potential, energy density, and rate capabilities. Developing models using atomistic simulations are powerful tools because structural features can be directly compared to experimental characterization results and develop deeper insights into battery processes. In this thesis, a number of atomistic models were developed using computational characterization techniques, which were compared with experiments to develop an accurate understanding of next-generation battery materials for high-energy density applications. These atomistic models were used to compare the catalytic processes in zin-air batteries and the intercalation process in different ion intercalation materials for dual-ion batteries for high energy density and economical application. Furthermore, the computational cost of running electronic structure calculations limits the lengthscale and timescale of simulations to study kinetic processes at experimental timescales, which involve rare events on potential energy surfaces. This work developed a generalized interatomic potential for bulk lithium using a machine learning package PyAMFF to replace density functional theory calculations to study the metal deposition process in batteries
Book Synopsis Fuzzy Filter-Based State of Energy Estimation for Lithium-Ion Batteries by : Shunli Wang
Download or read book Fuzzy Filter-Based State of Energy Estimation for Lithium-Ion Batteries written by Shunli Wang and published by Cambridge Scholars Publishing. This book was released on 2024-03-21 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: Awareness of the safety issues of lithium-ion batteries is crucial in the development of new energy technologies, and real-time and high-precision State of Energy (SOE) estimation is not only a prerequisite for battery safety, but also serves as the basis for predicting the remaining driving range of electric vehicles and aircrafts. In order to achieve real-time and accurate estimation of the energy state of lithium-ion batteries, this book improves the calculation method of the open-circuit voltage in the traditional second-order RC equivalent circuit model. It also combines a fuzzy controller and a dual-weighted multi-innovation algorithm to optimize the traditional Centralized Kalman Filter (CKF) algorithm in terms of the aspects of convergence speed, estimation accuracy, and algorithm robustness. This enables the precise estimation of SOE and the maximum available energy. The content of this book provides theoretical support for the development of new energy initiatives.
Book Synopsis Computational Methods of Multi-Physics Problems by : Timon Rabczuk
Download or read book Computational Methods of Multi-Physics Problems written by Timon Rabczuk and published by MDPI. This book was released on 2019-08-20 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a collection of six papers addressing problems associated with the computational modeling of multi-field problems. Some of the proposed contributions present novel computational techniques, while other topics focus on applying state-of-the-art techniques in order to solve coupled problems in various areas including the prediction of material failure during the lithiation process, which is of major importance in batteries; efficient models for flexoelectricity, which require higher-order continuity; the prediction of composite pipes under thermomechanical conditions; material failure in rock; and computational materials design. The latter exploits nano-scale modeling in order to predict various material properties for two-dimensional materials with applications in, for example, semiconductors. In summary, this book provides a good overview of the computational modeling of different multi-field problems.
