Mapping Li+ Concentration and Transport via In Situ Confocal Raman

Letter pubs.acs.org/JPCL

Mapping Li+ Concentration and Transport via In Situ Confocal Raman Microscopy Jason D. Forster,† Stephen J. Harris,§ and Jeffrey J. Urban*,† †

Molecular Foundry, Materials Sciences Division and §Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States S Supporting Information *

ABSTRACT: We demonstrate confocal Raman microscopy as a general, nonperturbative tool to measure spatially resolved lithium ion concentrations in liquid electrolytes. By combining this high-spatial-resolution technique with a simple microfluidic device, we are able to measure the diffusion coefficient of lithium ions in dimethyl carbonate in two different concentration regimes. Because lithium ion transport plays a key role in the function of a variety of electrochemical devices, quantifying and visualizing this process is crucial for understanding device performance. This method for detecting lithium ions should be immediately useful in the study of lithium-ion-based devices, ion transport in porous media, and at electrode−electrolyte interfaces, and the analytical framework is useful for any system exhibiting a concentrationdependent Raman spectrum. SECTION: Energy Conversion and Storage; Energy and Charge Transport

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confocal Raman microscopy is promising, but there has yet to be a study that addresses the concentration-dependent transport properties that we examine here. In this Letter, we have used confocal Raman microscopy as an effective tool for quantifying the transport of lithium ions in a system of lithium perchlorate (LiClO4) dissolved in dimethyl carbonate (DMC) in two different concentration regimes. Confocal Raman microscopy is a chemically specific technique that provides lateral spatial resolution better than 1 μm, limited ultimately by the diffraction limit of light, and temporal resolution limited only by the signal-to-noise ratio of the system. The spatial resolution of the system presented here is approximately 0.8 μm in the lateral direction and 8 μm in the axial direction. Measurement of lithium ion concentrations in situ is difficult because Li+ lacks readily accessible optical signatures such as fluorescence or active vibrational modes. Here, we exploit the vibrational signatures of closely associated solvent molecules to determine the local lithium ion concentration. Simulations have predicted the solvation of lithium ions by carbonate-based solvents to be primarily due to interaction with the carbonyl oxygen.17,18 This interaction is responsible for shifts in certain vibrational modes of various solvents and has been reported in experiments with lithium ion electrolytes,19−25 and similar effects have been observed in other mixed solvent26 and solvent/solute systems.27,28 Here, we have used the concen-

he transport of lithium ions is a fundamental process that enables the diverse functionality of many electrochemical devices. In the confined geometries of porous electrodes during rapid charging and discharging, ion concentrations can locally reach extreme values not observable in macroscopic C−V measurements. However, despite its immense importance, there are no demonstrations of spatially resolved lithium ion imaging under complex in situ conditions. This is a clear scientific gap because ion transport plays a significant role in common failure mechanisms and performance issues such as lithium plating,1 dendrite formation,2 and heterogeneous electrode performance.3−6 Beyond understanding failure modes, a more fundamental understanding of ion transport in porous and tortuous geometries is necessary for the design of many classes of advanced devices such as fuel cells and batteries that incorporate hierarchically ordered and porous electrode structures. While no current approach has demonstrated both the spatial and temporal resolution desired for in situ studies of real electrochemical systems, approaches to “seeing” lithium ions exist and include modeling of voltage−relaxation curves in restricted diffusion experiments,7−9 NMR,2,10,11 UV−vis absorption,12 neutron imaging,13 measurement of index of refraction gradients,14 and confocal Raman microscopy.15,16 The most frequently used electrochemical technique, modeling of restricted diffusion experiments, is problematic because of the inherent experimental uncertainties and numerous assumptions required. Specifically, uncertainty in electrode surface area, spurious currents due to side reactions, and the number of free parameters used in the models limit the ultimate generality and utility of this technique. The previous work on © 2014 American Chemical Society

Received: March 27, 2014 Accepted: May 20, 2014 Published: May 20, 2014 2007

dx.doi.org/10.1021/jz500608e | J. Phys. Chem. Lett. 2014, 5, 2007−2011

The Journal of Physical Chemistry Letters

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variety of research fields, including molecular biology,29,30 physics,31−33 and chemistry.34 Inspired by these studies, we have used a Y-shaped device, shown schematically in Figure 2 and in detail in Supporting Information Figure 1, to create concentration gradients of LiClO4 in DMC. The typical channel dimensions of our devices, 50 × 800 × 30 000 μm3 (depth × width × length), and the flow rates at which we conducted experiments, between 7.6 and 13.4 μL/min, ensured that we were in the laminar flow regime, with Reynolds numbers of approximately 8 and lower for all studies. In this regime of fluid dynamics, transport across streamlines is only possible via diffusion. In addition to the requirement of a low Reynolds number, the analysis that we present here requires a high Péclet number. The Péclet number is a measure of the relative importance of advection versus diffusion and is given by Pe = vd/D, where v is the mean velocity of fluid flow, d is the depth of the channel, and D is the diffusion coefficient. When the Péclet number is much larger than 1 (it is approximately 500 in our experiments), transport in the direction of flow is dominated by advection, and diffusion can be assumed negligible. This allows us to consider the diffusive transport of solute in one dimension, perpendicular to the direction of flow.33 Figure 2 shows representative concentration profiles obtained with this technique. In a given experiment, the concentrations at the inlets and the flow rate of the fluid are held constant. As the two input streams meet and flow down the main channel, Li+ diffuses from the high-concentration stream to the low-concentration stream. Assuming a constant diffusion coefficient, the shape of the concentration profile in the channel can be described by32

tration-dependent sideband intensity of the O−C−O vibrational mode of DMC to quantify the local lithium ion concentration. Figure 1 demonstrates the linear relationship

Figure 1. The Raman peak corresponding to the O−C−O deformation of DMC develops a sideband upon the addition of LiClO4. The symbols are the measured spectra; the curves are fits of the spectra using two Voigt profiles. A Voigt profile is the convolution of a Gaussian profile and a Lorentzian profile; it is commonly used to accurately describe the shapes of Raman peaks because it can account for instrumental broadening. For comparison, each spectrum has been scaled by its total fitted intensity. The molecular drawing above the main peak is of DMC, and the arrow indicates the molecular vibration being monitored. (Inset) The fraction of intensity in the sideband, α, increases linearly with increasing LiClO4 concentration. The black line is a linear fit to the data.

between LiClO4 concentration and the fraction of intensity in the sideband. This linear relationship enables us to quantify the diffusive transport of lithium ions by coupling scanning confocal Raman microscopy with a microfluidic cell (Figure 2). Microfluidic techniques have been used to quantify the diffusive transport of dissolved and intermixing species in a

C(x , y) =

⎛ y − y (x ) ⎞⎤ C0 ⎡ m ⎢1 + erf⎜ ⎟⎥ 2 ⎢⎣ ⎝ 2σ(x) ⎠⎥⎦

(1)

where x is the channel position in the direction of flow, y is the channel position perpendicular to flow, C0 is the difference between the two initial concentrations, erf is the error function, and σ(x) is the width of the profile. Equation 1 is valid only as long as σ is much smaller than the width of the channel, which is the case for all of the profiles reported here. The ym(x) term is necessary to fit our profiles because the two streams occupy different fractions of the channel width. This situation arises because the two streams have different viscosities; however, previous studies32 have shown that this asymmetry does not affect the behavior of σ versus x. The phenomenon that we are concerned with occurs as the flow proceeds down the channel and the two streams have more time to interdiffuse, resulting in an increase in σ. The width of the profile can be written as σ(x) = (Dx/v)1/2, where D is the diffusion coefficient of the relevant species, and v is the mean velocity in the channel. Therefore, by measuring σ(x), we have effectively measured the diffusion coefficient; x and v are experimentally determined. The residence time of the fluid will vary as a function of proximity to the channel walls due to the nature of Poiseuille flow. Depending on the channel aspect ratio and the volumetric flow rates involved, this can affect the apparent diffusion coefficient determined by this technique. In our case, however, measuring the concentration profiles in the midplane, with respect to z (depth of the channel), is a reliable method to measure D.33 To quantify the concentration dependence of the diffusion coefficient, we performed this experiment in two different

Figure 2. The concentration profile width increases along the direction of flow. (Top) Schematic of the microfluidic channel with colored lines indicating the positions at which line scans were recorded. (Bottom) Normalized concentration profiles from a flow experiment that used 0.8 and 1.0 M LiClO4 in DMC with a flow rate of 10 μL/min. The points correspond to the concentration as determined by fitting the Raman peak described in Figure 1. The lines are fits to the profile shapes using eq 1. The widths of the gray rectangles beneath the curves correspond to the fitted widths (σ) of the profiles. Each rectangle is labeled with the value of σ. 2008



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the slope of σ2 versus τ is the diffusion coefficient of Li+. The best fit of the low-concentration data yields Dlow = (10.6 ± 0.1) × 10−10 m2/s, while the best fit of the high-concentration data yields Dhigh = (4.5 ± 0.3) × 10−10 m2/s. Assuming an exponential dependence of D on the concentration of LiClO4, these results suggest D(c) = 11.9 exp(−1.09c), with D in units of 10−10 m2/s and c in units of mol/L. For comparison, Stewart and Newman12 found D(c) = 25.82 exp(−2.856c) for a system of lithium hexafluorophosphate (LiPF6) dissolved in a mixture of ethylene carbonate and diethyl carbonate (EC/DEC). At concentrations comparable to the ones used in our experiments, their relationship indicates Dlow = 19.41 × 10−10 m2/s and Dhigh = 1.98 × 10−10 m2/s. Apparently, this LiPF6 in EC/ DEC system exhibits an even more dramatic concentration dependence of the diffusion coefficient. We have presented confocal Raman microscopy as a valuable method for directly measuring spatially resolved lithium ion concentrations in a carbonate-based electrolyte. Combining this technique with a microfluidic device, we have measured the diffusion coefficient of lithium ions in DMC in two different concentration regimes. This approach allows for the most direct observation and quantification of lithium ion transport with excellent spatial resolution, free from assumptions about other transport parameters. Moreover, confocal Raman microscopy is not limited to the specific system presented here; any electrolyte system with concentration-dependent spectral features can, in principle, be studied with this technique. The concentration-dependent transport data already obtained with this technique are vital for understanding the function and failure of electrochemical devices.36 Extending this technique to the study of transport in more complicated and interesting geometries should enable the design of optimized electrode and device geometries.

concentration regimes. For a fixed concentration, slow flow yields more diffuse flow profiles relative to faster flow rates. This is because slower flow rates provide more time for the streams to mix and interdiffuse relative to the fast flow case, when measured at the same x position. With this in mind, we can recast the x positions as times by dividing by the mean velocity in the channel. Similarly, for a given flow rate, we observed that profiles from the low-concentration regime relax more than those from the high-concentration regime, as highlighted in Figure 3.

Figure 3. Normalized concentration profiles at x = 12 mm with a flow rate of 10 μL/min. (green squares) Neat DMC versus 0.2 M LiClO4. (purple circles) 0.8 versus 1.0 M LiClO4. The concentration profiles have been shifted to share the same center. The solid lines are fits to the data using eq 1. The shaded rectangles correspond to the fitted widths, σ, of each profile. The profiles and fits for all flow rates and x positions can be seen in Supporting Information Figures 2−5.

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In Figure 4, we plot the squared width of each concentration profile versus a time parameter, τ = x/v. Following this procedure, the squared widths of each concentration profile from each concentration regime collapse onto two separate lines. Assuming a constant viscosity and diffusion coefficient,

EXPERIMENTAL METHODS Electrolyte samples for the concentration calibration series were carefully prepared with volumetric glassware and were loaded into air-free optical cells constructed from glass microscope slides and polymer sealing foil (Meltonix) in an argon glovebox. Electrolyte samples for the microfluidic experiments were loaded into glass syringes (Hamilton Gas Tight), also in an argon glovebox. The syringes were then fitted to the device tubing before bringing the entire device out of the glovebox and attaching it to the microscope translation stage. Confocal Raman microscopy was performed using a WITec alpha300 S confocal microscope coupled to a Raman spectrometer (1800 grooves/mm grating) equipped with a CCD detector (UHTS-300). A fiber-coupled laser operating at 532 nm was used to stimulate Raman scattering. Excitation laser light was focused into the sample with a Nikon E Plan objective lens with 20× magnification and NA = 0.4. Light from the sample was collected using the same lens and passed through a fluorescence filter to remove nonscattered and Rayleigh-scattered laser light and then focused onto a pinhole at the entrance of an optical fiber that leads to the spectrometer. Spectra were collected using a single 5 s integration. Line scans were carried out at designated x positions. Each line scan was performed via the combination of a piezoactuated translation stage for small displacements (100 μm). Using this combination of translation stages, spectra were recorded every 10 μm across the

Figure 4. Determining the lithium ion diffusion coefficient from the slope of σ2 versus τ. All data from each concentration range collapse onto a single straight line after recasting the x positions as time. The black square symbols correspond to the low-concentration regime (neat DMC versus 0.2 M LiClO4) and the gray circle symbols to the high-concentration regime (0.8 versus 1.0 M LiClO4). The error bars in σ2 are derived from the uncertainties in fitting the concentration profiles, and the error bars in τ are due to the accuracy limit of the syringe pump, the variability in channel dimensions, and the uncertainty in determining the x position of each measurement. The black lines are fits obtained via a Deming regression, which takes into account the uncertainties in both τ and σ2.35 2009



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(7) Hafezi, H.; Newman, J. Verification and Analysis of Transference Number Measurements by the Galvanostatic Polarization Method. J. Electrochem. Soc. 2000, 147, 3036−3042. (8) Valoen, L. O.; Reimers, J. N. Transport Properties of LiPF6-Based Li-Ion Battery Electrolytes. J. Electrochem. Soc. 2005, 152, A882−A891. (9) Nyman, A.; Behm, M.; Lindbergh, G. Electrochemical Characterisation and Modelling of the Mass Transport Phenomena in LiPF6− EC−EMC Electrolyte. Electrochim. Acta 2008, 53, 6356−6365. (10) Klett, M.; Giesecke, M.; Nyman, A.; Hallberg, F.; Lindström, R. W.; Lindbergh, G.; Furó, I. Quantifying Mass Transport During Polarization in a Li Ion Battery Electrolyte by in Situ 7Li NMR Imaging. J. Am. Chem. Soc. 2012, 134, 14654−14657. (11) Krachovskiy, S. A.; Pauric, A. D.; Halalay, I. C.; Goward, G. R. Slice-Selective NMR Diffusion Measurements: A Robust and Reliable Tool for in situCharacterization of Ion Transport Properties in Lithium Ion Battery Electrolytes. J. Phys. Chem. Lett. 2013, 4, 3940− 3944. (12) Stewart, S. G.; Newman, J. The Use of UV/Vis Absorption to Measure Diffusion Coefficients in LiPF6 Electrolytic Solutions. J. Electrochem. Soc. 2008, 155, F13. (13) Siegel, J. B.; Lin, X.; Stefanopoulou, A. G.; Hussey, D. S.; Jacobson, D. L.; Gorsich, D. Neutron Imaging of Lithium Concentration in LFP Pouch Cell Battery. J. Electrochem. Soc. 2011, 158, A523−A529. (14) Brissot, C.; Rosso, M.; Chazalviel, J. N.; Lascaud, S. Concentration Measurements in Lithium/Polymer−Electrolyte/Lithium Cells during Cycling. J. Power Sources 2001, 94, 212−218. (15) Rey, I.; Bruneel, J.-L.; Grondin, J.; Servant, L.; Lassègues, J.-C. Raman Spectroelectrochemistry of a Lithium/Polymer Electrolyte Symmetric Cell. J. Electrochem. Soc. 1998, 145, 3034−3042. (16) Luo, Y.; Cai, W.-B.; Xing, X.-K.; Scherson, D. A. In Situ, TimeResolved Raman Spectromicrotopography of an Operating LithiumIon Battery. Electrochem. Solid-State Lett. 2004, 7, E1−E5. (17) Borodin, O.; Smith, G. D. LiTFSI Structure and Transport in Ethylene Carbonate From Molecular Dynamics Simulations. J. Phys. Chem. B 2006, 110, 4971−4977. (18) Tenney, C. M.; Cygan, R. T. Analysis of Molecular Clusters in Simulations of Lithium-Ion Battery Electrolytes. J. Phys. Chem. C 2013, 117, 24673−24684. (19) Klassen, B.; Aroca, R.; Nazri, M.; Nazri, G. A. Raman Spectra and Transport Properties of Lithium Perchlorate in Ethylene Carbonate Based Binary Solvent Systems for Lithium Batteries. J. Phys. Chem. B 1998, 102, 4795−4801. (20) Kondo, K.; Sano, M.; Hiwara, A.; Omi, T.; Fujita, M.; Kuwae, A.; Iida, M.; Mogi, K.; Yokoyama, H. Conductivity and Solvation of Li+ Ions of LiPF6 In Propylene Carbonate Solutions. J. Phys. Chem. B 2000, 104, 5040−5044. (21) Alía, J. M.; Edwards, H. G. M. Ion Solvation and Ion Association in Lithium Trifluoromethanesulfonate Solutions in Three Aprotic Solvents. An FT-Raman Spectroscopic Study. Vib. Spectrosc. 2000, 24, 185−200. (22) Xuan, X.; Wang, J.; Tang, J.; Qu, G.; Lu, J. A Vibrational Spectroscopic Study of Ion Solvation in Lithium Perchlorate/ Propylene Carbonate Electrolyte. Phys. Chem. Liq. 2001, 39, 327−342. (23) Alía, J. M.; Edwards, H. G. M.; Lawson, E. E. Preferential Solvation and Ionic Association in Lithium and Silver Trifluomethanesulfonate Solutions in Acrylonitrile/Dimethylsulfoxide Mixed Solvent a Raman Spectroscopic Study. Vib. Spectrosc. 2004, 34, 187−197. (24) Markarian, S. A.; Gabrielian, L. S.; Zatikyan, A. L.; Bonora, S.; Trinchero, A. FT-IR and Raman Study of Lithium Salts Solutions in Diethylsulfoxide. Vib. Spectrosc. 2005, 39, 220−228. (25) Hardwick, L. J.; Holzapfel, M.; Wokaun, A.; Novák, P. Raman Study of Lithium Coordination in EMI-TFSI Additive Systems as Lithium-Ion Battery Ionic Liquid Electrolytes. J. Raman Spectrosc. 2007, 38, 110−112. (26) Giorgini, M. G.; Musso, M.; Torii, H. Concentration-Dependent Frequency Shifts and Raman Spectroscopic Noncoincidence Effect of the CO Stretching Mode in Dipolar Mixtures of Acetone/Dimethyl

width of the channel. Care was taken to record spectra in the midplane of the channel by focusing the laser spot on the glass−electrolyte interface at the top of the channel, recording the z position, then focusing the laser spot on the interface at the bottom of the channel, recording the position, and then adjusting the focal plane of the microscope to be halfway between these two positions. Microfluidic devices were constructed by sandwiching a layer of polymer sealing foil between two 25 mm × 75 mm glass microscope slides. Prior to sealing, a y-shaped channel was carefully cut out of the polymer foil. Three holes, two inlets and one outlet, were sandblasted through one of the glass slides. The glass/polymer/glass stack was clamped with binder clips and heated in a vacuum oven at 150 °C for approximately 5 min to seal the device. After sealing, needles were epoxied over the holes to accommodate the tubing used to inject and extract the electrolyte. The final dimensions of the microfluidic channel are determined by optical microscopy after sealing. The width is determined by using the micrometer on the translation stage of the microscope. The height is determined by recording the difference in microscope position when the excitation laser is focused on the top and bottom glass/electrolyte interfaces.

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ASSOCIATED CONTENT

* Supporting Information S

Additional figures, including a photograph of a typical microfluidic device, a to-scale rendering of the channel cross section, and concentration profiles. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS Work at the Molecular Foundry was supported by the Office of Science, Office of Basic Energy Sciences, of the U.S. Department of Energy under Contract No. DE-AC0205CH11231.

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REFERENCES

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Mapping Li+ Concentration and Transport via In Situ Confocal Raman

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