Elsevier

Chemical Physics Letters

Volume 485, Issues 4–6, 26 January 2010, Pages 265-274
Chemical Physics Letters

FRONTIERS ARTICLE
Direct in situ measurements of Li transport in Li-ion battery negative electrodes

https://doi.org/10.1016/j.cplett.2009.12.033Get rights and content

Abstract

We describe the first direct in situ measurements of Li transport in an operating cell. Motion of the lithiation front in the graphite electrode suggests that transport could be controlled by liquid-phase diffusion. The electrochemical (current–voltage) data are successfully modeled with a diffusion equation that contains no material or microstructural information. The model is only qualitatively successful in predicting observed Li transport rate data, suggesting that microstructural information is required and that the actual process is more complex than simply diffusion. The technique can provide data for studying Li plating and Li dendrite growth, both of which can cause battery degradation.

Graphical abstract

Color changes in a graphite electrode as a function of lithiation, controlled by the voltage as shown below.

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Introduction

Because of their high energy density and long cycle life, Li-ion batteries are used today in many practical devices including cell phones and laptop computers, and they are now being contemplated for mass-produced hybrid and electric vehicles [1]. A typical Li-ion battery is shown schematically in Fig. 1a and as an SEM in Fig. 1b. As the battery is charged and discharged, Li, originally present in the electrolyte and in the positive electrode∗, chemically reacts with the negative electrode, inserting or intercalating into the bulk material. This lithiation process changes the chemistry of the electrode particles, so the properties of the Li-ion battery depend critically on the chemical nature of the electrode material. Since, by definition, Li is thermodynamically more stable in the positive electrode, a power supply is required to detach Li from the positive electrode (usually a transition metal oxide or phosphate) to form Li+ ions and then to push them into the negative electrode∗ (almost always a form of graphite or carbon) for charging, as illustrated in Fig. 1a. Because lithium reacts with practically everything, the number of potential lithium-ion battery electrode materials—and, therefore, the number of potential lithium-ion battery types—is almost limitless.

Li-ion batteries are generally analyzed using the macro-homogeneous porous electrode model developed by Newman and co-workers [2], [3]. The model consists of equations for: (1) electronic charge balance in the solid phase (Ohm’s law); (2) electrolyte charge and mass balance for Li+ using concentrated electrolyte theory; (3) diffusion of lithium in the electrode particles (Fick’s law); (4) Butler–Volmer∗ charge transfer kinetics at the electrolyte-solid phase boundary; (5) and associated boundary conditions. The model requires as input no microstructural information beyond particle radius, electrode thickness, and electrode porosity. Otherwise, it assumes that the microstructure can be described as an isotropic, homogeneous, 1-dimensional porous material made up from monodisperse non-porous isotropic spherical particles that are small compared to the electrode thickness.

Of course, none of these assumptions and approximations can be truly correct. For example, significant inhomogeneity in the electrodes and in the state of lithiation within an electrode that should be at equilibrium has been observed [4], [5], [6]. The charge transfer step is modeled as a single global chemical reaction in which Li+ ions in the electrolyte solution de-solvate, transport through a ∼1–10 nm thick solid electrolyte interphase (SEI) layer [7], [8], [9], [10], [11], [12] consisting of various degradation products, and react with the electrode material. Remarkably little is known about the detailed chemistry of the Butler–Volmer step [12], [13], [14], even though it is involved in many proposed degradation mechanisms [11], [15], [16]. Diffusion of lithium in the solid phase active particles is treated with a shrinking core diffusion model [17], [18] although its validity is at best uncertain for many commonly used electrodes, and although it has been shown to be invalid for at least one material [19]. Properties of the conductive carbon and binder, while of considerable importance to battery performance, are absorbed into other parameters.

In the years since the model appeared, a number of papers, some from Newman’s group, have examined the effects of relaxing some of the microstructural assumptions of the original model. For example, Darling and Newman [20] analyzed the effects of multiple particle sizes, Yi and Sastry [21] considered particles with ellipsoidal shapes, and Santhanagopalan et al. [22] and Yi et al. [23] looked at extending the model to higher dimensions. These and other efforts notwithstanding, the original macro-homogenous model performs very well and is still widely and successfully used [24] for optimizing electrode parameters such as thickness and porosity. It is, in fact, the basis for COMSOL’s commercial Li-ion battery code.

On the other hand, the ability to predict cell degradation remains a challenge because so many unaccounted for and seemingly unrelated micro-scale degradation mechanisms have been identified or postulated [4], [21], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39]. Experimental measurements describing local chemistry, details of the microstructure and transport, and an understanding of how these factors evolve are required in order to sort out the issues involved with degradation. At present, analysis of specific degradation mechanisms can sometimes offer explanations for experimentally observed degradation [22], [29], [40], [41], but without additional experimental data and associated theoretical analysis, cause-and-effect relationships between observation and degradation pathway can be difficult to demonstrate. For example, a widely invoked degradation mechanism is loss of internal ‘electrical connectivity.’ The loss of connectivity has been directly observed by Kostecki and McLarnon [4], and they attributed it to the movement of conductive carbon (‘carbon retreat’), reducing electron transport within the electrode. But loss of internal electrical connectivity has also been attributed to particle fracture [36], [38], [42], to precipitation of thick surface films [30], [35], to gas generation [43], to loss of contact between active material and the current collector [44] or between the current collector and the cell housing [45], and to degradation of the binder [46]. As a result, there has not appeared to be any experimental or modeling strategy that elucidates degradation as a general phenomenon. Because a lower degradation rate translates directly into lower-cost batteries, the ability to predict, mitigate, and deal with degradation by understanding fundamental chemical and material properties is critical if batteries for transportation are to become economically viable.

In an ideal Li-ion battery, the only process that should occur at the mesoscale (smaller than an electrode, larger than a molecule) is transport of lithium ions through the electrolyte and in the active particles, accompanied by reversible reactions of lithium at appropriate locations within the electrodes. All of the seemingly disparate mechanisms of battery degradation lead in some way to inefficiency or irreversibility of these fundamental transport and associated chemical processes. The present work is predicated on the notion that a general study of degradation can begin with measurements of Li transport and insertion into porous electrodes. These measurements could then guide researchers towards other experiments and models that provide fundamental knowledge of degradation. With this goal in mind, we provide here in situ time-dependent Li spatial maps and transport rate measurements at the mesoscale.

Section snippets

Experimental

Charging and discharging experiments were carried out in an optical half-cell∗. Fig. 2 shows the optical half cell as seen from the side (schematic) and from above (photograph). The cell was assembled in a glove box under an Ar atmosphere (<1 ppm oxygen and water), since even N2 reacts with Li. A brushed piece of Li foil acted as the negative electrode, while a porous graphite electrode cut from an LR1865AH 18650∗ laptop battery made by Tianjin Lishen Battery Co. served as the positive

Color of lithiated graphite

Graphite possesses a P63/mmc layered structure [52], where layers of graphene composed of hexagonally arranged sp2 hybridized carbon are weakly bonded to each other by van der Waals forces along the c-axis, resulting in 0.34 nm-wide galleries between the graphene layers. The layer stacking of lithium-free graphite is A–B–A–B, with layers translated but not twisted relative to each other. In order to allow lithium intercalation into a gallery space, the graphene layers slide with respect to each

Model

To model the insertion experiments, it will be assumed that the process of lithium insertion obeys the transient diffusion equationct=Deff2cx2,where c is the (molar) concentration of lithium with respect to a volume element containing both graphite and pore-filling electrolyte, x is the distance from the electrode’s edge at the electrode/separating electrolyte boundary, and t is time. The effective diffusion coefficient Deff is intended to lump together microscopic processes such as

Experimental

Fig. 3a and b show a pair of images taken about 45 min apart during lithiation. The camera angle gives a view of the edge of the electrode. The gold color rises from the current collector (Fig. 3a) toward the top face of the electrode (Fig. 3b), where the quartz window sits. The fact that lithiation occurs first at the current collector and only later at the top of the electrode suggests that the pore space between the top surface of the electrode and the quartz window is not the main transport

Summary and future work

In this work we have presented what we believe are the first direct in situ measurements of Li transport in an operating Li-ion cell. Such transport measurements could be useful for relating the many degradation modes that have been observed or proposed, to material properties and operating conditions, since most such mechanisms involve Li ‘not getting to the right place at the right time.’ We showed that for our conditions the lithium transport rate scales as t0.5. A model developed to

Acknowledgements

Valuable discussions with Prof. Martin Bazant of MIT and Drs. Yue Qi and Mark Verbrugge of GM R&D are gratefully acknowledged. SJH acknowledges support for this work from the Tank Automotive Research, Development and Engineering Center (TARDEC) under Contract N61339-03-D-0300.

Glossary

18650 battery
A standard size cylindrical cell, 18 mm in diameter and 65 mm long.
Butler–Volmer equation
This equation, which describes how the current in an electrochemical cell depends on the electrode potential, models an elementary charge transfer step. It includes Arrhenius dependences for forward and reverse reactions; the activation energies also depend on overpotential.
Half-cell
An electrochemical cell in which one electrode is a reference electrode that is thermodynamically equilibrated and

Stephen J. Harris received his B.S. in Chemistry at the University of California, Los Angeles in 1971 and his Ph.D. in Physical Chemistry at the Harvard University in 1975. He was a Miller Institute Fellow at the University of California, Berkeley from 1975 to 1977. Since then he has spent his career at the General Motors Research Labs (1977–1998), Ford Research Labs (1998–2007), and back at General Motors Research since 2007. He has worked in the areas of laser diagnostics of combustion, soot

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    Stephen J. Harris received his B.S. in Chemistry at the University of California, Los Angeles in 1971 and his Ph.D. in Physical Chemistry at the Harvard University in 1975. He was a Miller Institute Fellow at the University of California, Berkeley from 1975 to 1977. Since then he has spent his career at the General Motors Research Labs (1977–1998), Ford Research Labs (1998–2007), and back at General Motors Research since 2007. He has worked in the areas of laser diagnostics of combustion, soot formation and aerosol dynamics, chemical vapor deposition of diamond and boron carbide, contact mechanics modeling and prediction of fatigue lifetimes, microscopic basis for ductile fracture in cast aluminum, and battery degradation.

    Adam Timmons received a BSc and CAS in Science and Engineering from Acadia University (Canada) in 2001 and a Ph.D. in Physics from Dalhousie University (Canada) in 2007. Adam performed his doctoral work under the supervision of Prof. Jeff Dahn concluding in the dissertation titled ‘Visible Changes in Lithium-Ion Electrodes Upon Lithium Insertion and Removal’. He is the recipient of a Presidents Graduate Teaching Award at Dalhousie University as well as master’s and doctoral level scholarships from the Natural Science and Engineering Research Council of Canada. In 2007, Adam joined General Motors Global Research and Development where he executes a portfolio of research endeavors that pursue an enhanced understanding of the mechanisms and materials of advanced batteries.

    Daniel R. Baker received his Bachelor’s degree in mathematics in 1971 from Brandeis University and his Ph.D. in theoretical mathematics in 1976 from S.U.N.Y. Stony Brook. In 1979 he took his first job in applied mathematics, simulating melt water run-off from a glacier in the Austrian Alps. In 1985 he joined General Motors R&D Center, where he is currently a Staff Research Scientist. For the last twenty years, his work has focused on electrochemical modeling.

    Charles Monroe received a BSE from Princeton University in 1999 in Chemical Engineering, and a Ph.D. in Chemical Engineering from UC Berkeley in 2004. He was a research associate in the Chemistry Department at Imperial College from 2004 to 2007, and he was a post doctoral fellow in the Chemistry Department at Simon Frasier University from 2007 to 2008. He joined the faculty of the Chemical Engineering Department at the University of Michigan in the fall of 2008. His work involves modeling of batteries, fuel cells, and other electrochemical systems; nonequilibrium statistical mechanics; and coupled and multicomponent transport theory.

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