Probing Solid Electrolyte Interphase (SEI) Growth and Ion Permeability

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Probing Solid Electrolyte Interphase (SEI) Growth and Ion Permeability at Undriven Electrolyte-Metal Interfaces Using Li NMR 7

Andrew J. Ilott, and Alexej Jerschow J. Phys. Chem. C, Just Accepted Manuscript • Publication Date (Web): 21 May 2018 Downloaded from http://pubs.acs.org on May 21, 2018

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The Journal of Physical Chemistry

Probing Solid Electrolyte Interphase (SEI) Growth and Ion Permeability at Undriven Electrolyte-metal Interfaces Using 7Li NMR Andrew J. Ilott and Alexej Jerschow* Department of Chemistry, New York University, New York, NY 10003.

corresponding author: [email protected]

Abstract We examine here the exchange of Li ions between electrolyte and metallic lithium with 7 Li NMR spectroscopy. The measurements quantify the liquid-solid exchange processes, as well as the growth of a solid electrolyte interphase (SEI) layer. A numerical model including diffusion in the solid phase through atom hopping, radiofrequency penetration considerations through the skin effect, as well as surface exchange explains the experimental trends. Incorporation of the growth of a SEI layer explains the ‘missing’ Li quantities, and as the SEI layer grows, a decreased ion permeability in dependence on the layer thickness is modeled in order to explain the long-term trends. These measurements provide indirect probes for SEI growth and permeabilities, and also provide a means for quantifying Li diffusion in the metal.

Introduction When lithium metal is brought into contact with an electrolyte solution, spontaneous reactions lead to the formation of a layer made from inorganic and organic reaction products.1 The primary function of the layer, termed solid-electrolyte interphase (SEI), is passivation and protection from metal dissolution.2,3 The SEI is the subject of intense research, because it is often central to the successful operation of an electrochemical cell, in particular Li-ion cells.4,5 In addition to protecting the anode, the layer has to allow for efficient ion propagation.6 Furthermore, with Li-metal anodes, in particular, the nature of the SEI layer is thought to be critical to determining the modality of metal deposits on the electrode (e.g. smooth or irregular deposits and dendrite formation).7 At the same time, there is a lot of uncertainty of knowledge about the initiation, composition, and growth of this layer, because (i) it forms rapidly upon electrode contact with the electrolyte, (ii) is generally very thin (tens of nm), and (iii) is affected significantly by the presence of impurities, electrolyte composition, and the electrode surface morphology.2,5

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Its structure is often found to be composed of both organic and inorganic layers with various levels of porosity and ion conductivity.6,8 Li metal is a promising anode material, especially for secondary batteries and is central to emerging cell technology such as Li-Air cells.9 Safety issues associated with Lidendrite growth currently prevent the use of lithium metal as an anode in secondary batteries. Efforts are being taken to engineer SEI layers such that dendrite growth can be minimized.10 The layer is inherently difficult to study due to its small size, but also because in the process of sample preparation (for ex situ studies, for example), the layer may be altered significantly.

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Figure 1. Schematics of the experimental setup: (a) Li-enriched lithium metal immersed in Li (natural abundance) electrolyte inside an NMR tube. (b) Illustration of the exchanging components of the system between the metal (gray, right) and electrolyte (green, left) including Li self-diffusion inside the metal, SEI growth and inter-phase exchange.

Recently, NMR spectroscopy and MRI techniques have been developed to study electrochemical processes in situ, and derive ion mobilities, monitor electrode reactions and observe microstructure formation.11-20 The SEI has also been studied with solid-state NMR in destructive analyses by scraping off the layer from an electrode or grinding up the electrode and performing multinuclear magic-angle spinning experiments.21-24 To the best of our knowledge, this technique, however, has not been used for metallic lithium electrodes. Static spectra of the SEI are relatively featureless, due to the inability to resolve broad spectral features.25 Further challenges in this approach are given by the low sensitivity of the signals obtained from the small amounts of SEI materials. Hyperpolarization techniques could be used to address this problem.24 Here we investigate the Li ion/metal exchange and SEI growth when Li metal is brought into contact with an electrolyte solution without applying any additional potential. The experiments are performed by means of isotopic tracking from an initial point where a Li metal electrode is enriched with 6Li. 7Li NMR experiments performed on a 6Li-enriched lithium metal strip (6Li:7Li = 0.95:0.05) immersed (Fig. 1) in a natural abundance LiPF6 / EC/DMC battery electrolyte (6Li:7Li = 0.074:0.926) show an increase in the 7Li metal and

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Li electrolyte signals over time, while the 6Li metal and 7Li electrolyte signals decrease. These results, discussed in more detail below, suggest that there is significant lithium exchange between the electrolyte and the lithium metal electrode even in this undriven situation (no potential applied) over long periods of time. A model of the process is established by including diffusion in the solid phase (atom hopping), a liquid-solid exchange rate constant, a Li-metal sink into the SEI layer, and a growing SEI layer leading to decreased permeability. The Li signals obtained from the conductor are further analyzed considering the properties of radiofrequency (rf) penetration into the conductor. While both 6Li and 7Li were measured, the bulk of this work focuses on 7Li due to its higher sensitivity and consequently more reliable results. Experimental NMR experiments and sample preparation NMR experiments were performed on a Bruker Ultrashield 9.4 T Avance I spectrometer operating at 155.51 MHz for 7Li and 58.90 MHz for 6Li. A Bruker Micro2.5 imaging probe was used, with Bruker WB40 25 mm inside diameter 1H/7Li and 1H/6Li coils. The samples were aligned in the coil such that the major surface of the lithium metal was parallel to the direction of the rf field.26 For each nucleus, two experiments were performed, one with the transmitter on resonance with the electrolyte signal at 0 ppm, and one at the metal signal, at approximately 261 ppm, which is the Knight shift of Li metal.27 The probe was tuned to the metal signal for consistency. Single pulse experiments were performed with a /2 excitation pulse, of = 35 μs duration for 6Li and 39 μs for 7Li, which were calibrated on the on-resonance electrolyte signal for each experiment series. The other acquisition parameters were set to yield quantitative signals for each species: 6Li metal (recycle delay, rd = 3 s, spectral width, sw = 16 kHz, number of scans, ns = 1200), 6Li electrolyte (rd = 30 s, sw = 5 kHz, ns = 40), 7Li metal (rd = 0.8 s, sw = 50 kHz, ns = 1500) and 7Li electrolyte (rd = 15 s, sw = 4 kHz, ns = 1500). The sample preparation was performed inside a glove box under Ar atmosphere. To make the 6Li metal sample, a small strip was cut from a 6Li metal chunk (0.95:0.05 6 Li:7Li, Sigma Aldrich) using a razor blade, then pressed inside a polyester bag using a hammer. A rectangular strip was cut from the pressed metal using a razor blade, measured and weighed. The experiments were set up according to the schematic in Fig. 1, with the metal strip placed at the bottom of a 10 mm NMR tube. 3 mm NMR tubes were placed around the metal to insure stable positioning throughout the experiments. The NMR tube was sealed with a cap and parafilm. Initial NMR experiments were performed on the 6Li and 7Li metal signals on this ‘dry’ sample. The sample was then put back into the glove box and a measured weight of standard battery electrolyte added (1M LiPF6 in 1:1 ethylene carbonate and dimethylene carbonate solvent, with natural lithium isotopic abundance, 6Li:7Li = 0.074:0.926). To allow for quantification, the amount of electrolyte added was set so that it occupied a region entirely within the excitation

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profile of the coil (ca. 15 mm). The tube was again sealed and returned quickly for the experiments, with the coil changed between 6Li and 7Li measurements. The experiments were performed on a 14 x 5 x 0.45 mm 6Li metal strip weighing 14.8 mg (the thickness is calculated from the other dimensions and measured mass) that was placed in 0.6989 g e 0⁄ m 0 e 0 m 0 of LiPF6 electrolyte (7Li 7Li = 4.07, where 7Li and 7Li are the total 7 number of moles of Li in the electrolyte and metal at = 0, respectively). The spectra resulting from the NMR measurements were phased and integrated, so that the integrated areas could be compared to the simulated intensities as expressed above. The full set of NMR spectra are shown in Fig. S1. In the metal series, the spectra were automatically phased to minimize the integral of the imaginary component, after which the integral of the real part of the spectrum was compared directly against the calculated value of from Eqs. (9-13) below. A lineshape fit of the imaginary component of the spectrum could be used to extract additional information from the phase of the signal (see Eqs. 9-11) but this approach is complicated by the presence of multiple, overlapping lineshapes in the metal spectra due to the slightly different susceptibility shifts in different parts of the metal strip, and was hence not used. Numerical simulation The model illustrated in Fig. 1b is used for characterizing the measured data. The concentration of 7Li in the metal electrode is governed by the diffusion equation, ,

=!

" , "

(1)

m $, where #$, = %7Li , is a discretized 1D representation of the fraction of 7Li at each depth in the metal, where $ ∈ [0, (] represents the distance from the surface of the metal such that $ = 0 corresponds to the metal surface and $ = ( is some maximum depth from the surface of the metal. For convenience, ( is set to half the overall thickness of the lithium metal. In this way, the model geometry can be readily scaled up to the full volume of the electrode through multiplication by the surface area of the main face of the metal, * ≈ 2,-, ignoring the minor electrode faces that make up a small fraction of the overall surface area, and are also poorly sampled in NMR due to rf field effects.26 Appropriate boundary conditions at $ = 0 allow for exchange between the surface sites in the metal and the electrolyte.

The time derivative in Eq. (1) is integrated numerically using the Python/Scipy interface to the lsoda ODE integrator from the FORTRAN library, odepack. The spatial derivative for the diffusion equation in the metal is estimated using central differences. Neumann boundary conditions are used at each end of the box ($ = 0, (. At $ = (, the boundary condition, #. (, = 0 is used to prevent “leakage” of 7Li from the cell. At $ = 0, the metal region is in contact with the electrolyte and exchange between the metal and electrolyte occurs,

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Li/ electrolyte + 7− ⇌ Limetal

(2)

To preserve electroneutrality, both the forward and reverse reactions occur at the same rate, which can be written in terms of the concentration of Li+ in the electrolyte and the surface area of the lithium metal strip, ; , as = ?=> [Li/ ]; ,

(3)

where the rate coefficient, ?=> is in units of m@A s @B . The lithium concentration is assumed to be uniform throughout the volume of the electrolyte, although it does vary in time as the reaction proceeds. Any imbalance in the exchange is modeled by the Li sink into the SEI as described below. We note that a temperature-dependence of the rate coefficients is expected but not explicitly stated. All experiments were performed at room temperature (293 K). Although the overall Li exchange is considered to be in a steady state, the relative effects for the 6Li and 7Li isotopes will be different and we can separately define the exchange of 7Li between the electrolyte and the metal surface via the exchange rate = 2.0 m@A hr @B. Under these conditions, it is possible to reach simultaneous agreement between simulation and the electrolyte and metal NMR results (for ?F=G = 1.5 m@A hr @B). A simple way to understand this result is that the 7Li metal signal does not increase sufficiently to account for the full amount of 7Li+ that is being removed from the electrolyte and therefore an extra “sink” for 7Li+ is required. The formation of an SEI layer satisfies this need, both in terms of numerical agreement with the model, and chemical understanding of the processes occurring in the system.

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Figure 3: NMR results (points) and simulation results (lines) with fixed molar ratio and exchange coefficient, ?=> = 2.0, with ?F=G taking values the values shown (in units of m@A hr @B ) ) for the signal intensities vs. immersion time. NMR intensity is plotted with respect to the intensity at t=0. Labels for the lines in (b) are omitted for clarity but the overlapping lines correspond to ?F=G = 0,1.5,3.0 as in (a).

There are still several areas where the model and approach seem unsatisfactory. Firstly, at long times, the experimental 7Li metal NMR signal seems to reach a plateau and this is not reflected by any of the models. Secondly, the growth of the SEI layer can be expected to impact the electrolyte-metal exchange rate. For instance, from ?F=G and [Li/ ] the number of moles of Li in the SEI can be calculated from, F=G = g= [Li/ ] 1 − [Li/ ] = g= [Li/ ] 1 − exp −?F=G ; ,

(15)

and the thickness of the SEI layer can be estimated by ZF=G =

h ijkl , mno

(16)

where g= is the volume of the electrolyte (assumed to be constant throughout the experiment), M is the average molar mass of the constituents of the SEI layer per Li ion, p its density, and ; the surface area of the lithium metal as before. For ?F=G = 1.5 m@A hr @B as found from the model fit, and assuming an SEI layer composed mainly of Li2O (q = 29.88 g, p = 2.012 g), the thickness of the SEI layer would grow at a rate of approximately 6 nm hr @B (for two other common SEI ingredients, LiOH and Li2CO3, the values would be 13 and 14 nm hr @B, respectively). These numbers appear to be well in line with literature values. We note that the NMR spectra (Fig. S1) do not show the development of any additional peaks associated with SEI formation, nor would they be expected to do so, given the broad NMR signal associated with this amorphous/crystalline phase, and the small quantity of SEI material overall. The presence and growth of the SEI layer can be expected to slow down ?=> due to reduced ion permeability. Therefore, this effect is also modeled. Simulations with SEI layer impacting `bs

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The SEI layer is an ionic conductor (hence why batteries will still cycle even after the SEI layer has formed), but its presence restricts the availability of Li+ at the surface of the metal to some extent. The growth of the SEI may also “freeze in” the isotopic ratio of the exchange pool of lithium to the SEI layers that form in the initial stages of the experiment. In practice, it will be difficult to distinguish between models associated with these phenomena. Instead, we implement a simplified model whereby the exchange rate depends on the SEI thickness, according to = ?=> [Li/ ]; exp −?t ZF=G ,

(17)

where ?H is an additional rate constant with dimensions of m@B. While several models would be consistent with reasonable assumptions, an exponentially decaying permeation rate would be consistent with a gradual decrease of ion conductivity of the SEI layer (e.g. also decrease of porosity). Other models, for example, with d-1 and d-2 behavior have been considered, which could be rationalized by electrophoretic and diffusion transport, respectively. These models, however, were found to be incompatible with the results, probably because the flow cannot be characterized by these regimes alone.

Figure 4: NMR results (points) and simulation results (lines) with fixed molar ratio, exchange coefficient, ?=> = 3.0, ?F=G = 2.0, and ?t taking the values shown (in units of nm@B ) ) for the signal intensities vs. immersion time. NMR intensity is plotted with respect to the intensity at t = 0.

The simulation results for the model including the SEI-limited exchange rate are shown in Fig. 4, where the values of ?=> and ?F=G were fixed at 3.0 and 2.0 m-2 hr-1. The nature of the SEI composition affects the fitted rate constant, ?t , as the molar volume of the SEI material impacts the simulated SEI thickness, ZF=G , grown at any point in time. The numbers reported here are based on Li2O as the major component. Other Li-based components could be used as discussed above and would lead to slightly different layer growth rates. Variation in ?t leads to minor differences in the electrolyte profile, but major changes in both the magnitude and overall shape of the metal profile. In every case there is an initial increase in the 7Li metal intensities as the exchange proceeds

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between the 7Li in the electrolyte and the 6Li at the surface of the metal. However, when ?t is high (5 nm@B ) the exchange rapidly slows and only small amounts of 7Li are added into the metal, while the existing 7Li diffuses away from the surface leading to an overall decrease in the NMR signal due to the skin effect. For smaller values of ?t , there is a more balanced effect and the 7Li metal signal reaches a plateau as the exchange slows. The reproduction of the plateau feature in the metal signal intensities in the range ?t = 1.0~1.5 nm@B marks a significant improvement over the previous models, which did not show this effect. As shown here, it is only observed when the exchange rate between the electrolyte and the metal slows with time. Overall, it is seen that the SEI permeability to ion motion slows with time, but significant growth is observed over long periods of time. The model presented and tested here therefore provides a good means of studying SEI formation dynamics, and could be employed further to determine the influence of electrolyte additives of surface modification.

Conclusions We have provided here results on Li exchange between bulk Li metal and an electrolyte solution by tracking isotope fractions over time with 7Li and 6Li NMR. 7Li data were most useful due to the better signal-to-noise ratios, especially in the signals from the metal region. Theoretical models, based on diffusion in the metal, exchange between the two phases, SEI growth and associated changes in surface permeability were found to fit the experimental data well. These findings allow for an indirect characterization of the origination and growth of an SEI layer. The use of isotopic labeling of the metal, in this case, allows determining slow exchange processes and changes over many hours. These findings and techniques could be important for screening the behavior of SEI growth and Li ion permeability with different electrolytes, additives, and surface modifications.

Acknowledgement Funding is acknowledged from the US National Science Foundation under Award CHE1412064. Supporting Information Paragraph Full time series of 7Li and 6Li NMR spectra. Additional simulations of isotope exchange across the interface. Additional analysis and discussion of 6Li NMR data.

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(16) Chang, H. J.; Trease, N. M.; Ilott, A. J.; Zeng, D. L.; Du, L. S.; Jerschow, A.; Grey, C. P. Investigating Li microstructure formation on Li anodes for lithium batteries by in situ Li-6/Li-7 NMR and SEM, J. Phys. Chem. C, 2015, 119, 16443. (17) Ilott, A. J.; Mohammadi, M.; Chang, H. J.; Grey, C. P.; Jerschow, A. Real-time 3D imaging of microstructure growth in battery cells using indirect MRI, Proc Natl Acad Sci U S A, 2016, 113, 10779. (18) Ilott, A. J.; Trease, N. M.; Grey, C. P.; Jerschow, A. Multinuclear in situ magnetic resonance imaging of electrochemical double-layer capacitors, Nat Comm, 2014, 5, 4536. (19) Chandrashekar, S.; Trease, N. M.; Chang, H. J.; Du, L. S.; Grey, C. P.; Jerschow, A. 7Li mri of Li batteries reveals location of microstructural lithium, Nat Mat, 2012, 11, 311. (20) Forse, A. C.; Griffin, J. M.; Merlet, C.; Carretero-Gonzalez, J.; Raji, A.-R. O.; Trease, N. M.; Grey, C. P. Direct observation of ion dynamics in supercapacitor electrodes using in situ diffusion NMR spectroscopy, Nat Energy, 2017, 2, 16216. (21) Wan, C.; Xu, S.; Hu, M. Y.; Cao, R.; Qian, J.; Qin, Z.; Liu, J.; Mueller, K. T.; Zhang, J.-G.; Hu, J. Z. Multinuclear NMR study of the solid electrolyte interface formed in lithium metal batteries, ACS Appl Mat Interf, 2017, 9, 14741. (22) Hall, D. S.; Werner-Zwanziger, U.; Dahn, J. 19F and 31P solid-state NMR characterization of a pyridine pentafluorophosphate-derived solid-electrolyte interphase, J Electrochem Soc, 2017, 164, A2171. (23) Murakami, M.; Yamashige, H.; Arai, H.; Uchimoto, Y.; Ogumi, Z. Direct evidence of LiF formation at electrode/electrolyte interface by 7Li and 19F double-resonance solid-state NMR spectroscopy, Electrochem. Solid-State Lett., 2011, 14, A134. (24) Leskes, M.; Kim, G.; Liu, T.; Michan, A. L.; Aussenac, F.; Dorffer, P.; Paul, S.; Grey, C. P. Surface-sensitive nmr detection of the solid electrolyte interphase layer on reduced graphene oxide, J. Phys. Chem. Lett, 2017, 8, 1078. (25) Wang, Y.; Guo, X.; Greenbaum, S.; Liu, J.; Amine, K. Solid electrolyte interphase formation on lithium-ion electrodes: A 7Li nuclear magnetic resonance study, Electrochem. Solid-State Lett., 2001, 4, A68. (26) Ilott, A. J.; Chandrashekar, S.; Klockner, A.; Chang, H. J.; Trease, N. M.; Grey, C. P.; Greengard, L.; Jerschow, A. Visualizing skin effects in conductors with MRI: (7)Li MRI experiments and calculations, J Magn Reson, 2014, 245, 143. (27) Gutowsky, H. S.; McGarvey, B. R. Nuclear magnetic resonance in metals. I. Broadening of absorption lines by spin‐lattice interactions, J. Chem. Phys., 1952, 20, 1472. (28) Jackson, J. D. Classical electrodynamics john wiley & sons, Inc., New York, 1999. (29) Hoult, D. The principle of reciprocity in signal strength calculations—a mathematical guide, Concepts Magn Reson, Part A, 2000, 12, 173. (30) Mehring, M.; Kotzur, D.; Kanert, O. Influence of the skin effect on the Bloch decay in metals, Physica Status Solidi B, 1972, 53. (31) Ilott, A. J.; Jerschow, A. Super-resolution surface microscopy of conductors using magnetic resonance, Sci Rep, 2017, 7, 10.1038/s41598. (32) Messer, R.; Noack, F. Nuclear magnetic relaxation by self-diffusion in solid lithium: T1-frequency dependence, Appl Phys, 1975, 6, 79.

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(33) Mali, M.; Roos, J.; Sonderegger, M.; Brinkmann, D.; Heitjans, P. 6Li and 7Li diffusion coefficients in solid lithium measured by the nmr pulsed field gradient technique, J. Phys. F., 1988, 18, 403. (34) Mehrer, H. Atomic jump processes in self-diffusion, J Nucl Mat, 1978, 69, 38.

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