Solid Electrolyte Interphase in Li-ion Batteries: …inside.mines.edu › ~decaluwe › Papers › OwejanEtAl_ChemMat...Solid Electrolyte Interphase in Li-ion Batteries: Evolving Structures

PreprintofarticlepublishedatChemistryofMaterialshttps://doi.org/dx.doi.org/10.1021/cm3006887

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Solid Electrolyte Interphase in Li-ion Batteries: Evolving Structures Measured In Situ by Neutron Reflectometry Jeanette E. Owejan*a, Jon P. Owejana, Steven C. DeCaluweb,c and Joseph A Dura*b, aElectrochemical Energy Research Laboratory, General Motors, Honeoye Falls, NY 14472, USA b NIST Center for Neutron Research, Gaithersburg, MD 20899-6102, USA c Department of Materials Science and Engineering, University of Maryland, College Park, MD

20742, USA

Author Contact Information:

Steven C. DeCaluwe:

NIST Center for Neutron Research 100 Bureau Dr. MS 6102 Bldg. 235 A124 Gaithersburg, MD 20899-6102 Phone: 301-975-8811 Fax: 301-921-9847 email: [email protected] Joseph A. Dura:

NIST Center for Neutron Research 100 Bureau Dr. MS 6102 Bldg. 235 A126 Gaithersburg, MD 20899-6102 Phone: 301-975-6251 Fax: 301-921-9847 email: [email protected]

Jeanette E. Owejan:

Electrochemical Energy Research Laboratory, General Motors 10 Carriage St. Honeoye Falls, NY 14472 Phone: 585-259-2130 Fax: 585-624-6680 email: [email protected]

Jon P. Owejan:

Electrochemical Energy Research Laboratory, General Motors 10 Carriage St. Honeoye Falls, NY 14472 Phone: 585-953-5558 Fax: 585-624-6680 email: [email protected]


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Abstract

Li-ion batteries are made possible by the solid electrolyte interphase, SEI, a self-forming

passivation layer, generated due to electrolyte instability with respect to the anode chemical

potential. Ideally it offers sufficient electronic resistance to limit electrolyte decomposition to

the amount needed for its formation. However, slow continued SEI growth leads to capacity

fade and increased cell resistance. Despite the SEI’s critical significance, currently structural

characterization is incomplete due to the reactive and delicate nature of the SEI and the

electrolyte system in which it’s formed. Here we present, for the first time, in situ neutron

reflectometry measurements of the SEI layer as function of potential in a working lithium half-

cell. The SEI layer after 10 and 20 CV cycles is 4.0 and 4.5 nm, respectively, growing to 8.9 nm

after a series of potentiostatic holds that approximates a charge / discharge cycle. Specified

datasets show uniform mixing of SEI components.

Keywords:

Li ion Battery, Solid Electrolyte Interphase, In-situ Neutron Reflectometry

Synopsis

These first in situ neutron reflectometry measurements of a solid electrolyte interphase, SEI, layer vs. potential in a working Li battery show its structure, including Li incorporation and thickness, from 4.0 nm to 8.9 nm after a charge / discharge cycle. Uniform mixing of SEI components occurs at some potentials.


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Introduction

Ongoing research and development of lithium ion battery materials for automotive

applications is largely focused on the durability of electrodes and their electrolyte interactions.

Due to the instability of the electrolyte with respect to the anode chemical potential1-4, the

electrolyte components decompose to form lithium-containing inorganic and organic compounds

on the electrode surface, thus reducing the amount of active lithium available to the cell.

Beneficially, this layer is passivating in nature, such that ionic conductivity is maintained while

electronic conductivity drastically decreases, preventing further electrolyte decomposition5. Of

the identified causes for capacity fade, continued growth of the solid electrolyte interphase (SEI)

layer, primarily due to fresh electrode exposure induced during lithiation, is therefore considered

a necessary evil.

Numerous previous investigations have sought to understand the SEI layer, primarily by

performing electrochemical tests and subsequently studying the SEI by ex situ spectroscopy or

microscopy techniques. It is of great interest to expand these measurements to study the growth,

composition, thickness, and porosity of the SEI in situ as a function of operating conditions. The

efficacy of SEI forming additives may be directly evaluated if such a method could be

developed, and various hypotheses, such as the preferential decomposition of various electrolyte

components to form SEI and decomposition of metastable lithium alkyl carbonates into more

stable compounds could be directly verified6-18. Additionally, the SEI is understood to evolve

with temperature, potential, and time, though these dependencies have not yet been thoroughly

explored.6,7,9-11,19,20.

A thorough review of SEI characterization to date is summarized by Xu21, and more

recently by Verma et al.22. It is clear that although ex situ spectroscopic surface characterization


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of the SEI gives evidence that the SEI is a layered structure containing inorganic components

closer to the anode surface and organic moieties in proximity to the electrolyte interface7,10,23,24,

the composition of the organic species in situ is under debate25-28. Discrepancies arise not only

due to the possibility of trace impurities including moisture or oxygen, but also because of the ex

situ nature of these experiments. Synthesis of bulk mono- and dialkyl carbonates utilized for

exhaustive characterization efforts has been undertaken by Xu et al.29-31.

Neutron reflectometry, NR, determines the depth profile of the scattering length density,

SLD (which is related to composition), by fitting the intensity of reflected neutrons as a function

of grazing angle from the surface, q, providing sub-Ångström precision of features greater than

~1.5nm in thickness32,33. The technique is mature, having been widely used for studying

magnetic materials34, thin film interfacial structures in polymers35, biological membranes36,37,

and recently for Li intercalation into Si electrodes38. NR is ideal for in situ lithium ion battery

diagnostics as it is sensitive to light elements in SEI compounds. Additionally, isotopic contrast

variation for H and Li allow accurate depth profiles of these elements or isotopic labeling of

sources for these elements. Furthermore, fluid exchange with working fluids of different

scattering length densities allows direct measurement of the porosity depth profile. Unlike

electron spectroscopy techniques, neutrons are highly penetrating and non-perturbing, thus

making possible in situ measurements of unaltered SEI layers.

This study presents the first ever use of in situ NR to measure the structure of an SEI in a

lithium battery. The cells are configured as a lithium half-cell, where the lithium acts as both

counter and reference electrode. Because specular neutron reflectivity averages over in-plane

features, a rough surface such that graphite exhibits would not be applicable to NR

measurements. Copper, deposited onto a Ti adhesion layer on a single-crystal Si substrate, was


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chosen as working electrode as it does not intercalate lithium, and thus all electrochemical

charge is attributed to decomposition of the electrolyte to form the SEI layer. Copper is

frequently used as an ‘ideal’ electrode for SEI studies31, 39-45, and it has been established that

films grown on non-intercalating substrates are similar to those grown on carbon materials at low

potentials in Li salts46,47. Aurbach et al. have also shown that the thermodynamics of reduction

processes of the electrolyte solution species are governed by the cation used43. The electrolyte

consisted of 1mol/L LiPF6 in a 1:2 (v/v) ratio of deuterated ethylene carbonate, EC, and diethyl

carbonate, DEC. The deuteration was chosen for two reasons. It increases the SLD of the

electrolyte to provide greater contrast to the SEI, which is expected to have a relatively low SLD

due to Li incorporation. Additionally, isotopic labeling of the EC allows one to attempt to

identify the possible preferential decomposition of cyclic over acyclic carbonates.

Experimental Methods

Half Cell Fabrication

The native oxide was first removed by HF cleaning from a single crystal silicon wafer

(Institute of Electronic Materials Technologyd) that is 7.6cm in diameter by 0.95 cm thick with

N/P/100 type/dopant/orientation, respectively. Immediately a 7.5 nm titanium adhesion layer

and 40 nm copper layer were deposited via electron beam evaporation, at the Semiconductor and

Microsystems Fabrication Laboratory at Rochester Institute of Technology. Layer composition,

uniformity, and roughness of a sacrificial wafer were verified using X-ray reflectometry. The

lithium foil (Alfa Aesar), 5.72 cm diameter, was polished and pressed onto a copper/titanium dCertaincommercialequipment,instruments,ormaterialsareidentifiedinthispapertofosterunderstanding.SuchidentificationdoesnotimplyrecommendationorendorsementbytheNationalInstituteofStandardsandTechnology,nordoesitimplythatthematerialsorequipmentidentifiedarenecessarilythebestavailableforthepurpose.


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wafer to form the counter/reference electrode. A 500 µm thick Kalrez® (Dupont) gasket was

adhered to the working electrode, determining a 20.26 cm2active area. Two 25 µm gold foils

(99.98%, Goodfellow) served as current collectors on each side of the half cell. Partially

deuterated electrolyte was made with LiPF6 (Alfa Aesar), deuterated EC (CDN Isotopes), and

DEC (Alfa Aesar) for a final composition of 1 mol/L LiPF6 in 1:2 d-EC:DEC (v/v).

Electrochemical Testing

Electrochemical data was collected on a Gamry Ref 600™ potentiostat. All voltages are

reported vs. Li. Cyclic voltammetry, CV, was carried out to determine peak locations for

potentiostatic hold test points; the voltage window was limited to avoid lithium plating and

copper oxidation. CV conditions are as follows: Einit= OCV, Ef= 0.05 V, scan rate was 10 mV/s,

and subsequent Ef= 3.0 V. A set of 10 CV scans was initiated by scanning in the cathodic

direction. Directly after, a potentiostatic hold at 250 mV was started by ramping the voltage

down at 10mV/s. The hold lasted until NR data collection was complete, typically around 8

hours and a current of 10E-9 A was reached. NR data was taken as a series of short scans, which

were compared to confirm that the sample structure was invariant to within statistics. Scans that

did not vary from one another were subsequently combined to reduce measurement uncertainty,

as described in the Supporting Information. This procedure was repeated with a hold at 150 mV.

Six additional potentiostatic holds were carried out after 10 mV/s ramps to the new potential, but

without preceding CV cycles. Integrated charge for all eight holds was calculated.

Neutron Reflectivity Fitting

Specular neutron reflectometry was performed by standard procedures (see Supporting

Information). Because NR measures the reflected intensity rather than the amplitude, the phase


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of the neutron wave is not measured; therefore, single NR spectra cannot be directly inverted to

determine a SLD profile. Refl1D48 was used to model the reflectivity data. The SLD depth

profile is represented as a series of material layers of specified scattering length density (real and

imaginary) and thickness, with Gaussian interfaces between them. Reflectivity is computed

using the Abeles optical matrix method, with interfacial effects computed by the method of

Nevot and Croce or by approximating the interfaces by a series of thin layers. In some cases

refinement of multiple reflectivity data sets with constraints between the models has been

employed. The three instrumental fitting parameters that were allowed to vary were the beam

intensity, the residual background, and the incident angle offset.

Refl1D uses a Bayesian approach to determine the uncertainty in the model parameters.

By representing the problem as the likelihood 𝐿 = 𝑒!!!/! of observing the measured reflectivity

curve given a particular parameter set, Refl1D can use Markov Chain Monte Carlo (MCMC)

methods49 to draw a random collection of parameter sets from the joint parameter probability

distribution. In this study a differential evolution stepper was employed since it samples the

entire range of parameter space more effectively than other approaches. The distribution of

values for a particular parameter from the collection is used as an estimate of the probability

density for that parameter. The parameter values, SLD profile, and model reflectivity curve that

are reported are for the best fit, i.e., the parameter set with the lowest value of χ2. The

uncertainty of a given parameter is expressed as the 68 % confidence interval, the shortest range

of parameter values that includes 68 % of the total probability density. The 68 % confidence

interval would correspond to the ±1σ uncertainty level if the parameter values were normally

distributed.


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To visualize the uncertainty in the best fit reflectivity curve, a selection of 50 parameter

sets is randomly chosen. An envelope that includes the central 68 % of the calculated reflectivity

values for each Q value is plotted as a shaded region. To first approximation, there is a 68 %

probability that a point on the true reflectivity curve would fall within this shaded region.

Similarly, the same 50 parameter sets are used to visualize uncertainty in the SLD depth profile.

While SLD profiles have an arbitrary zero point of depth, because the Ti layer and its associated

interfaces are held fixed for all test points, the SLD profiles are co-aligned at this layer. An

envelope that includes the central 68 % of the model SLD values for each depth z of the profile

is plotted as a shaded region. To first approximation there is a 68 % probability that a point on

the true SLD profile would fall within this shaded region. The 95 % confidence intervals,

displayed with lighter shading, are calculated in the same way from the same selection of

parameter sets.

Results & Discussion

NR data was taken using AND/R at the NIST Center for Neutron Research50 of the virgin

Cu cathode in the electrolyte-filled cell at open circuit voltage (test point a-OCV). Subsequently

an SEI was produced by running 10 CV, followed by a potentiostatic hold at reducing potential

(250mV vs. Li). NR data was again taken after the current decayed to near zero (test point b-

250mV). These two data sets, shown in Figure 1, show a distinct difference in amplitude and

oscillation peak position as a function of momentum transfer, Q, due to the effects of the SEI

layer on the scattering. These two data sets were simultaneously fit, with common parameters

for the Ti layer, itssurrounding interfaces, and the Cu SLD to provide an accurate structural

determination of the layered sample with and without SEI. All other parameters in the model


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were varied independently for each data set, except the Si substrate SLD which was held fixed at

the value calculated from the known scattering length and the density of crystalline Si. The

resultant parameters and 68% confidence intervals are shown in Table S2 of the Supporting

Information. The reflectivity, R, is plotted vs. momentum transfer, Q=(4p/l)sinq where l is the

wavelength of the neutrons, 0.5001 ± 0.0004 nm. Fitting this data reveals that the Cu SLD is 99%

of the bulk value, and the Ti SLD indicates silicide formation. Furthermore, a copper

carbonate/hydroxide liganding layer was present the initial surface, formed due to the pristine

nature (no surface oxides) of the copper. After the CV scans the liganding layer is removed and

an SEI is deposited that consists of a single 4.0 nm [3.6, 4.2] nm e thick layer with SLD well

below the level of the electrolyte, as seen in the inset to Figure 1. To confirm that this model

which includes an SEI layer is a better fit to the data than one without an SEI, an additional

eNumbersinbracketsarethe68%confidencerangedeterminedbythefittingsoftware.NRerrorbarsareplusorminusonestandarddeviationbaseduponpropagatingcountingstatisticsfromthespecular,backgroundandslitscansusedtoobtainthespecularreflectivity.

Figure 1. a) Neutron reflectivity vs. Q is shown for the sample at OCV and after 10 CV cycles during a hold at 250 mV. The solid lines are the best fit, from a simultaneous fit to the two data sets. b) The SLD profiles for the two best fits. The SLD values of Si, Cu and Ti (calculated from known densities) are indicated, and Electrolyte, SEI, and TiSix layers are identified. For both parts, the darker and lighter shaded regions are the 68 % and 95 % confidence intervals, as discussed in the methods section.


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simultaneous fit excluding the SEI was performed. This fit (not shown) resulted in not only an

increase in χ2 but also an increase in the Bayesian information criterion, thus indicating that the

model with an SEI is statistically more likely than the model excluding it. The next test point (c-

150mV) repeated the cyclic voltammograms, followed by a potentiostatic hold at 150 mV.

Charge data for all test points may be found in the Supporting Information.

The SEI layer at test point c is remarkably similar to the previous test point, b, having

similar SLD and interface widths, but slightly thicker at 4.5 nm [4.0, 4.7] nm due to the lower

reduction potential and/or additional 10 CV cycles. These results also agree with a 3.6 nm [3.2,

4.2] nm thick SEI deposited by a similar procedure in a second cell with a fully protonated

electrolyte (see Supporting Information). Subsequently, six data sets (d-i) were taken at various

potentials by slowly ramping the potential at a rate of 10 mV/s to the next value and holding

during NR data collection, as summarized in Figure 2, which shows representative CV curves

taken throughout the experiments. Note that complex chemistries occur as demonstrated by the

various peaks in the CV curves, the

origins of which have been

discussed in the literature31,43,44,51.

They serve for us as points at

which to execute the potential

holds and NR measurements. The

decrease in the magnitude of the

current density with increased

cycling in Figure 2 demonstrates

the passivating nature of the

Figure 2. Electrochemical measurements including cyclic voltammogram results for selected scans. Test points b-i denote the location of potentiostatic holds for NR testing.


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growing SEI layer, also verified by smaller

reductive currents collected during NR

measurements. Thus, in our study, the most

active test points with respect to SEI growth

were those between b-d, and f, where the

passivation layer was forming, and those

subsequent were much less active.

The associated NR data sets for test

points c through i are shown in Figure 3.

Each had excellent individual fits to a

model that held all parameters the same as

determined from the simultaneous fit (Fig1)

except the Cu and SEI thickness, the SEI

SLD, both interface widths surrounding the

SEI, and three instrumental parameters

which varied insignificantly. The resulting

SLD profiles from these fits (along with test

point b) are shown in Figure 4, and the

fitted parameter values and 68% confidence

intervals are shown in Table S3 of the

Supporting Information. Key fit parameters

are summarized in Figure 5. It was found

that the apparent thickness of the Cu layer

Figure 3. Neutron reflectivity (expressed as RxQ^4) vs. Q is shown for the sample measured during holds at the potentials indicated. The solid lines are the best individual fit, with several parameters kept constant at values determined from the simultaneous fit of the OCV and 250 mV data (see text for details). The darker and lighter shaded regions are the 68 % and 95 % confidence intervals, as discussed in the methods section.


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Figure 4. The SLD as a function of depth for the SEI deposited on Cu, showing the evolution of the thickness, SLD and interface roughness with hold potential, as indicated. The lines for b-i, are best individual fits, with several parameters kept constant constant at values determined from the simultaneous fit of the OCV and 250 mV data (see text for details). The inset shows the full SLD profile, with the fits co-aligned on the Ti layer.

increased from a starting thickness of 41.51 nm [41.39, 41.57] nm in test point b to a thickness of

41.81nm [41.76, 41.88] nm and 42.17 nm [42.10, 42.23] nm for test points e and f, respectively,

due to the addition of a few monolayers of material, presumably Cu2O (which has a high SLD

sufficiently close to that of Cu). This layer is too thin to be accurately modeled as a separate

layer32,33, and is subsequently removed during cathodic potential holds in test points g-i, where

the Cu layer thickness decreases to a final value of 41.43 nm [41.40, 41.49] nm, which is the

same as the initial value to within uncertainty. Sufficient published electrochemical data of

copper in non-aqueous systems identifies Cu+1 oxidation occurring near 2.0 V vs. Li and Cu+2

oxidation occurring at 3.5V vs. Li.51 . These increases in apparent copper thickness originate

from the demand of current-generating chemical reactions to sustain the potential holds. Thus,


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even at test point g (1.5V) where one would expect all oxide to be reduced, we observe a larger

than initial copper thickness since we remained at a slightly oxidative potential (test point f) for

an extended amount of time and have not fully removed the Cu+1 oxide during the hold at g. In

general, it is important to note that the species formed during these extended potential holds will

not correspond directly with those formed at similar potentials during the CV scans in Figure 2.

These fits and associated uncertainties clearly show that the SEI present on the copper

surface changes in both composition and thickness as a function of potentiostatic holds. SEI

measured thickness grows steadily from b to d, from 3.96 nm to 4.75 nm. At these test points,

the SLD of the layer also increases from 1.90 to 2.24 (x10-4 nm-2), demonstrating that a layer

with molecules originally rich in lithium incorporates molecules that contain relatively less

lithium (i.e., LiOH, SLD= 0.0602 x 10-4 nm-2 vs. (pronated) lithium alkyl carbonates, SLD =

2.22 x 10-4 nm-2). While lithium underpotential deposition and stripping may occur during these

test points, it would add at most one monolayer, which can also be consistent with the results of

the thickness and SLD values measured. The layer shrinks slightly at e (2.3 V), presumably due

to the oxidation current and/or due to solubility of several molecules. Moving from e (2.3 V), a

stable region for carbonate-based electrolytes, to f (1.5 V), we observe a doubling in thickness

accompanied by an increase in SLD, with little change when the potential is decreased to 800mV

at test point g.

The next two test points, h and i, demonstrate increasing reduction of the SLD as the

potential is lowered, indicating a net gain of lithium-containing or low density molecules. The

large SLD gradients seen at the SEI/electrolyte interface in these last two test points can be

interpreted in two ways. The one-layer model shows the layer thickness roughly constant or

slightly decreasing as the SLD decreases (in going from test point g through i), which can be


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interpreted as the SEI layer as a whole is substituting high SLD material (Li poor or dense) with

lower SLD material (Li rich or less dense). Alternatively, examination of the SLD profile

indicates a layer that increases in thickness from g to h and less so to i, while the low SLD

material is added near the Cu interface. This composition gradient interpretation would indicate

that Li-rich material is added near the Cu interface while the already deposited material remains

adjacent to the electrolyte and is roughened. This is supported by the net charge accumulation

during these potential holds, indicating net molecules were added to the SEI. Future

measurements employing Li isotopic substitution will be able to distinguish between these two

possibilities.

While for some test points (b-e, h, and i) large composition gradients are evident in the

SLD profiles, for select test points, f and g, the uniformly flat SLD profiles show complete

mixture of components within the observed SEI. Such observations contradict the segregation

between inorganic and organic species suggested by previous studies 2, 52-54. Such a segregation

would be very evident in our SLD profiles, as the inorganic molecule Li2O has a very low SLD

(0.8126 x10-4 nm-2), and segregation of this molecule to near the copper surface would result in a

dip in the SLD profile well below the SEI SLD of roughly 2.5 x10-4 nm-2 seen in Figure 4.

Similarly, we also do not observe a segregated lithium-containing organic phase closest to the

electrolyte. These materials would cause a peak in the SLD profile at the electrolyte/SEI

interface because the SLD values of deuterated lithium alkyl carbonates (SLD = 8.65 x10-4 nm-2)

and dicarbonates (SLD = 6.45 x10-4 nm-2) are greater than that of our electrolyte.

To further investigate the possible composition of the SEI layer as a function of potential

holds, a model that estimates the amount of various SEI compounds was created. The partial

thicknesses of each compound and SLD of the total were calculated and matched to the NR


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fitting results. X-ray Photoelectron Spectroscopy, XPS, data (contained in Supporting

Information) indicates the presence of LiF, LiOH, lithium alkyl carbonates, and non-lithium

containing polyethylene oxide (SLD = 3.86 x10-4 nm-2), PEO. The fractional amount of lithium

was assigned to each molecule according to the peak areas in the deconvoluted XPS data. The

relative amount of PEO was determined from the C1s and O1s peaks in the XPS data. Porosity

of the SEI is handled by adding electrolyte to the composition, which affects both SLD and

overall thickness. The thickness is determined from the number of molecules in the model and

the molecular volume. The amounts of each component were adjusted within the variability

range observed in the post mortem XPS measurements, and guided by known chemical reactions

producing SEI components21, until the model thickness and composition (red and blue dashed

lines, respectively) matched the thickness and SLD measured by NR (red squares and blue

circles respectively) as seen in Figure 5. The results of this model are shown in Figure 6, where

the modeled partial thickness are summed and compared to the NR measurement.

The changes of the SEI

composition when moving to

successively more reducing

potential include the increase in

concentration of LiOH and LiF

molecules, and the decrease of

lithium alkyl carbonates. The

porosities determined in these

models (9-10%) are similar to the

11.0% [10.6%, 15.9%] porosity

Figure 5. Selected fitting parameters as a function of test point. For reference, the hold potential vs. Li is also shown. The red and blue dashed lines are the total thickness and SLD from the composition modeling, as described in the text, and match well with values measured by NR. Cu thickness is plotted relative to the thickness measured in test point a – OCV.


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Figure 6. SEI thickness and composition modeled by use of XPS, electrochemical, and NR measured parameters compared to the thickness measured by NR. Each segment in the bar represents the partial thickness (not gradient) that each molecule contributes to the SEI thickness. The hold potential and charge ratio (measured during the holds / modeled) are also shown.

determined by another cell that utilized contrast variation via fluid exchange (see Supporting

Information). The quantity of LiOH and LiF grows during test duration, while the lithium alkyl

carbonate concentration fluctuates during testing. The molecules identified above are consistent

with previous ex situ studies, however the lack of segregation of certain molecules shows that

our in situ evaluation of the SEI structure and composition sheds significant light on how the SEI

initiates and grows. Furthermore, others have modeled that ageing of the SEI over time will

reduce hydroxides and lithium alkyl and dicarbonates to the more stable Li2O, LiF, and Li2CO3

components55. However, this combined electrochemical/reflectivity test was run over a period of


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approximately 3 days, and was not examined ex situ by XPS until approximately 60 days later,

when the cell was released from radiation screening. After this duration, we did not see evidence

of the oxide or carbonate in our ex situ data.

It is important to note here that the total accumulated charge measured during the NR

experiments is similar to additional experiments performed on button cells. Much less charge

was required for the composition models than the measured charge, indicating that a significant

portion of the decomposition components were not retained within the SEI layer. The ratio of

the measured charge to the modeled charge is shown in Figure 6 and increases from 1.85 at test

point b to 5.39 at test point i. This is most likely due to the solubility of several SEI components.

Several factors add slightly to the possible systematic error in the SLD values used to

determine these compositions, including sample warp and lateral inhomogeneities observed in

XPS; see the Supporting Informationsection for additional detail. Additionally, these models do

not have a unique solution; less probable combinations of molecules may also simultaneously fit

the data. Finally there is a possibility that a second layer with SLD similar to the electrolyte (and

thus invisible to NR) exists in this sample. This, however, is unlikely in that if this second layer

grows in proportion to the excess measured charge its increased thickness would make it easier

to detect, and it is likely that its SLD would evolve with changing potential, like that of the

observed SEI layer. The SLD of this layer would then differ from the electrolyte SLD by a

significant amount at some potentials and would be measurable via NR for those cases.

Conclusions

It is demonstrated that neutron reflectivity is a highly effective tool for investigating in

situ growth and evolution of the SEI. A well-functioning electrochemical cell and electrode


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materials compatible with NR measurements have been developed which are highly suited for

this application, and the SEI has been measured for a range of potentiostatic holds. Results in

this paper represent the first direct measurements of critical SEI properties – such as thickness,

porosity, layered structures and gradients, and chemical composition – on an operating Li cell,

without confounding experimental artifacts associated with ex situ techniques. These results

include an SEI thickness of 4.0 nm to 4.5 nm for 10 CV cycles growing to 8.9 nm after a series

of potentiostatic holds that approximates a charge / discharge cycle. The SLD profile of several

test points indicates a lack of significant gradients, contrary to proposed structures in the

literature. The SEI thickness grew most rapidly directly after test point e, an oxidative hold,

where electrolyte components are stable, to point f (1.5 V), which lies in the region of electrolyte

instability. Due to its passivating nature, growth of the SEI thickness slowed subsequent to this,

even at the lowest potentials examined. However, lower SLD, Li-rich molecules were

substituted into the SEI at lower potentials, as demonstrated in the progressive change in SLD

when moving from test points g through i. Roughly 0.6 nm of a high SLD material, for example,

Cu2O was deposited under the SEI adjacent to the Cu anode between 2300 mV and 1500 mV vs.

Li, and then removed completely upon electrochemical reducing potentials.

Future implications of this study include the capability to directly and quantitatively

study SEI properties as a function of electrolyte composition (including additives), temperature,

voltage, current, and cycling/time, etc. In addition, the direct measurement of critical SEI

parameters, both presented herein and in the future under a variety of conditions, will lead to

marked improvements in the accuracy of numerical simulations of processes in Li batteries

involving the formation of and ion transport within the SEI17,56-60. Taken together, such NR


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investigations will enable future systematic improvements for commercial device performance,

affordability, and sustainability.

Acknowledgements

The authors gratefully acknowledge funding for this work through NIST ARRA Award Number: 60NANB10D027, part of the American Recovery and Reinvestment Act of 2009, as well as the National Research Council for funding through the NRC Research Associateship Program. Nicholas P. Irish of GM Global R&D is acknowledged for XPS data collection and peak deconvolution and Paul A. Kienzle, NCNR, for useful discussions of NR fitting.

Supporting Information

Additional Figures in the form of charge accumulation, XPS overlay plots, reflectivity plot for the fluid exchange cell, and scattering length density profile as a function of test point for the fluid exchange cell. Tabular data for atomic % composition by XPS for the non fluid exchange cell, description of ex situ sample preparation, cell build and test for the fluid exchange cell. Neutron Reflectivity data collection and analysis details, results of data from fluid exchange cell. This material is available free of charge via the Internet at http://pubs.acs.org.


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