Kinetic Monte Carlo simulations applied to Li-ion and post Li-ion batteries: a key link in the multi-scale chain (original) (raw)
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Unlike modeling at other levels as described in this workshop, the role of modeling at the atomic level has its main usefulness in the selection and design of materials for high performance batteries. We describe recent progress in studies of transport mechanisms of lithium in polymer electrolytes which suggest new approaches to the search for electrolytes with higher conductivity. #
The formation of passivation films by interfacial reactions, though critical for applications ranging from advanced alloys to electrochemical energy storage, is often poorly understood. In this work, we explore the formation of an exemplar passivation film, the solid electrolyte interphase (SEI), which is responsible for stabilizing lithium-ion batteries. Using stochastic simulations based on quantum chemical calculations and data-driven chemical reaction networks, we directly model competition between SEI products at a mechanistic level for the first time. Our results recover the Peled-like separation of the SEI into inorganic and organic domains resulting from rich reactive competition without fitting parameters to experimental inputs. By conducting accelerated simulations at elevated temperature, we track SEI evolution, confirming the postulated reduction of lithium ethylene monocarbonate to dilithium ethylene monocarbonate and H2. These findings furnish fundamental insights into...
Materials for Lithium Ion Batteries: Challenges for Numerical Simulations
Zeitschrift für Physikalische Chemie, 2012
ABSTRACT We present an overview of numerical challenges in simulating electronic and transport properties of battery assemblies. Li diffusion paths within inorganic materials (olivine phosphates) are investigated using a dedicated accelerated molecular dynamics approach. The need of many-body electronic structure calculations is illustrated for the evaluation of intercalation potentials (LDA/GGA+U) and of transport properties (LDA+DMFT). Steps towards the improvement of silicon based anodic materials are shown. All in all, the framework of an ab initio simulation platform for materials for power storage is sketched.
Statistical Physics-Based Model of Solid Electrolyte Interphase Growth in Lithium Ion Batteries
The article presents a statistical physics-based model for the growth of the solid electrolyte interphase (SEI) in the negative electrode of lithium ion batteries. During battery operation, the SEI thickness grows by the reaction between lithium ions, electrons and solvent species on the surface of active particles at the negative electrode. The growth of the SEI layer causes a loss of lithium ions that induces capacity fade. In addition, it increases the ion transport resistance and decreases the total porosity. Our model employs a population balance formalism based on the Fokker-Planck Equation to describe the propagation of the particle density distribution function in the electrode. Structure-transforming processes at the level of individual particles are accounted for by using a set of kinetic and transport equations. These processes alter the particle density distribution function, and cause changes in battery performance. A parametric study of the model singles out the first moment of the initial SEI thickness distribution as the determining factor in predicting the capacity fade. The model-based treatment of experimental data allows analyzing processes that control SEI growth and extracting their controlling parameters. Lithium ion batteries (LIBs) are highly touted energy storage devices for portable electronics and electric vehicles. 1 The LIB system consists of a negative electrode, a positive electrode, a separator, an electrolyte, and two current collectors. The most commonly used elec-trolytes are comprised of lithium salts, such as LiPF 6 in a solution of ethylene carbonate (EC) and dimethyl carbonate (DMC). 1 The electrodes consist of randomly distributed and interconnected particles of active material, which store and release the lithium ions. Aging and degradation of LIBs have become major concerns for the operation of electric vehicles (EVs), which must fulfill exacting requirements in terms of durability, cyclability and overall lifetime. 2 Battery aging is linked to the (electro-)chemical and mechanical degradation of the electrodes and the electrolyte. 2 Three main degradation mechanisms prevail at the particle level during the cycling of LIBs: (1) growth of the solid electrolyte interphase (SEI) at the negative electrode, 2,3 (2) formation of cracks in the SEI layer at the negative electrode, 4 and (3) dissolution and isolation of nanocrystalline particles at the positive electrode. 5 These processes lead to capacity fade and power loss. At the beginning of the battery life, particularly during the first cycle, the electrolyte undergoes reduction at the electrode/electrolyte interface, because the negative electrode operates at potentials that are outside of the electrochemical stability window of electrolyte components. This reduction is accompanied by the irreversible consumption of lithium ions. 6 This process forms a passivating surface layer known as the solid electrolyte interphase. The SEI layer grows further during charging, thereby reducing the amount of active lithium ions. Moreover , this layer penetrates into the electrode pores, reducing the overall porosity and decreasing ion access to the active surface area of the electrode. 2 Understanding the mechanism of SEI thickness growth and the resulting composition of the layer is a vital topic of LIB research, because of its great practical significance and the intricate interplay of underlying processes. 2,6–14 The growth of the SEI involves a complex reaction network 15,16 that is sensitive to operating conditions as well as the battery cycling protocol. A mechanistic understanding of the processes involved in SEI formation and growth is vital for designing LIB systems with high performance and long cycle life. The topic therefore garners significant interest in the experimental and theoretical research community. Recent efforts in modeling of the electrochemical processes during cycling of LIBs include particle level models 17,18 and porous electrode theory. 16 In 1976, Bennion developed the first model of the SEI for lithium metal electrodes. 19 Peled further derived a parabolic growth law for the SEI considering the electron transfer as the rate-determining step in the growth of the SEI layer. 20 Ploehn et al. developed a model for SEI growth, in which the diffusion of solvent through the SEI is the rate-determining step. 21 Interestingly , this assumption also leads to a parabolic growth law. Newman et al. developed a model to predict the SEI growth based on porous electrode theory, including the detailed chemistry of SEI formation. 16 This model was the first attempt to link chemical reactions leading to SEI formation to irreversible capacity loss. However, it comprises a large number of model parameters. Xie et al. expanded Newman's model to incorporate thermal effects. 22 They found the battery skin temperature to significantly affect the growth of the SEI. Several subsequent works are based on Newman's model. Their common feature is that they couple a one dimensional model of charge and mass transport through the electrode to a one dimensional model of spherical diffusion inside active particles, resulting in a pseudo two-dimensional porous electrode (P2D) model. 23–26 Under low to moderate working conditions, the P2D model can be reduced to a single particle (SP) model. 27,28 In this approach, the electrode is represented by identical spherical particles, whose accumulated surface area is equivalent to the total active area of the solid phase in the porous electrode. This model assumes that the mass and charge transport resistances in solution can be neglected. Moreover, the faradaic current across the porous electrode exhibits a linear profile , which is valid in the limit of small applied currents in thin and highly conductive electrodes. 18 The modeling work presented in this article strives to establish relations among structural properties and electrochemical performance of the battery in order to rationalize the influence of SEI growth upon them. The central component of the statistical physics-based modeling framework is the Fokker-Planck Equation (FPE). The porous battery electrode is treated as a statistical distribution of interconnected particles. The FPE governs the temporal evolution of this distribution. The developed formalism allows leading causes of structural degradation , driven by (electro-)chemical and mechanical stressors, to be incorporated. Capacity and power fade as well as the battery cycle life can be analyzed in dependence of the initial structure, the external conditions and the cycling protocol applied, to predict the propagation of the particle density distribution function due to SEI growth. Eikerling and coworkers introduced a statistical modeling framework to study the degradation of platinum nanoparticles in the) unless CC License in place (see abstract). ecsdl.org/site/terms_use address. Redistribution subject to ECS terms of use (see 134.169.25.245 Downloaded on 2017-12-10 to IP
Phys. Chem. Chem. Phys., 2015
There is an increasing worldwide demand for high energy density batteries. In recent years, rechargeable Li-ion batteries have become important power sources, and their performance gains are driving the adoption of electrical vehicles (EV) as viable alternatives to combustion engines. The exploration of new Li-ion battery materials is an important focus of materials scientists and computational physicists and chemists throughout the world. The practical applications of Li-ion batteries and emerging alternatives may not be limited to portable electronic devices and circumventing hurdles that include range anxiety and safety among others, to their widespread adoption in EV applications in the future requires new electrode materials and a fuller understanding of how the materials and the electrolyte chemistries behave. Since this field is advancing rapidly and attracting an increasing number of researchers, it is crucial to summarise the current progress and the key scientific challenges related to Li-ion batteries from theoretical point of view. Computational prediction of ideal compounds is the focus of several large consortia, and a leading methodology in designing materials and electrolytes optimized for function, including those for Li-ion batteries. In this Perspective, we review the key aspects of Li-ion batteries from theoretical perspectives: the working principles of Li-ion batteries, the cathodes, anodes, and electrolyte solutions that are the current state of the art, and future research directions for advanced Li-ion batteries based on computational materials and electrolyte design.
The formation of passivation films by interfacial reactions, though critical for applications ranging from advanced alloys to electrochemical energy storage, is often poorly understood. In this work, we explore the formation of an exemplar passivation film, the solid−electrolyte interphase (SEI), which is responsible for stabilizing lithium-ion batteries. Using stochastic simulations based on quantum chemical calculations and data-driven chemical reaction networks, we directly model competition between SEI products at a mechanistic level for the first time. Our results recover the Peled-like separation of the SEI into inorganic and organic domains resulting from rich reactive competition without fitting parameters to experimental inputs. By conducting accelerated simulations at elevated temperature, we track SEI evolution, confirming the postulated reduction of lithium ethylene monocarbonate to dilithium ethylene monocarbonate and H 2. These findings furnish fundamental insights into the dynamics of SEI formation and illustrate a path forward toward a predictive understanding of electrochemical passivation.
Kinetic Monte Carlo applied to the electrochemical study of the Li-ion graphite system
Electrochimica Acta, 2020
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Multiscale modeling and characterization for performance and safety of lithium-ion batteries
Journal of Applied Physics, 2015
Lithium-ion batteries are highly complex electrochemical systems whose performance and safety are governed by coupled nonlinear electrochemical-electrical-thermal-mechanical processes over a range of spatiotemporal scales. Gaining an understanding of the role of these processes as well as development of predictive capabilities for design of better performing batteries requires synergy between theory, modeling, and simulation, and fundamental experimental work to support the models. This paper presents the overview of the work performed by the authors aligned with both experimental and computational efforts. In this paper, we describe a new, open source computational environment for battery simulations with an initial focus on lithium-ion systems but designed to support a variety of model types and formulations. This system has been used to create a three-dimensional cell and battery pack models that explicitly simulate all the battery components (current collectors, electrodes, and ...
Electrochimica Acta, 2019
In this paper we report a comprehensive analysis and tracking of the variabilities associated to multiscale simulations coupling a Coarse Gained Molecular Dynamics (CGMD) model of Lithium Ion Battery electrodes fabrication with a 3D-resolved performance model at the cell scale. We quantify the impact on the final electrode structure of the initial conditions in the CGMD simulations in terms of initial random distribution in the slurry of the active material and carbon binder domain particles (CBD). This study is carried out with a batch of simulations at different slurry active material/CBD compositions. Results show that for each electrode composition there is a statistical dispersion in the predicted cell performance curves, in agreement with in house experimental results. Furthermore, in house experiments revealed a different correlation regime depending on the Crate at which the cathode is operating. The proposed methodology and findings allows us to pave the way towards the design of reliable approaches to control the variables correlations in the multiscale modeling of electrodes fabrication and its impact on LIB performance.
Modeling lithium-ion solid-state electrolytes with a pinball model
Physical Review Materials
We introduce a simple and efficient model to describe the potential energy surface of lithium diffusing in a solid-state ionic conductor. First, we assume that the Li atoms are fully ionized and we neglect the weak dependence of the electronic valence charge density on the instantaneous position of the Li ions. Second, we freeze the atoms of the host lattice in their equilibrium positions; consequently, also the valence charge density is frozen. We thus obtain a computational setup (the "pinball model") for which extremely inexpensive molecular dynamics simulation can be performed. To assess the accuracy of the model, we contrast it with full first-principles molecular dynamics simulations performed either with a free or frozen host lattice; in this latter case, the charge density still readjusts itself self-consistently to the actual positions of the diffusing Li ions. We show that the pinball model is able to reproduce accurately the static and dynamic properties of the diffusing Li ions-including forces, power spectra, and diffusion coefficients-when compared to the selfconsistent frozen-host lattice simulations. The frozen-lattice approximation itself is often accurate enough, and certainly a good proxy in most materials. These observations unlock efficient ways to simulating the diffusion of lithium in the solid state, and provide additional physical insight into the respective roles of charge-density rearrangements or lattice vibrations in affecting lithium diffusion.