Mechanism behind the Unusually High Conductivities of High

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C: Energy Conversion and Storage; Energy and Charge Transport

Mechanism behind the Unusually High Conductivities of High Concentrated Sodium Ion Glyme-based Electrolytes Susith R Galle Kankanamge, Ke Li, Kristen D. Fulfer, Pu Du, Ryan Jorn, Revati Kumar, and Daniel G Kuroda J. Phys. Chem. C, Just Accepted Manuscript • DOI: 10.1021/acs.jpcc.8b06991 • Publication Date (Web): 18 Oct 2018 Downloaded from http://pubs.acs.org on October 20, 2018

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The Journal of Physical Chemistry

Mechanism behind the Unusually High Conductivities of High Concentrated Sodium Ion Glyme-based Electrolytes Susith R Galle Kankanamge,‡ Ke Li,‡ Kristen D. Fulfer, ‡┴ Pu Du,‡ Ryan Jorn,† Revati Kumar‡ and Daniel G. Kuroda‡* † Department of Chemistry, Villanova University, Villanova, Pennsylvania 19085, United States ‡ Department of Chemistry, Louisiana State University, Baton Rouge, Louisiana 70803, United States

*Address correspondence to [email protected] Present Address ┴ Chemistry Program, Centre College, Danville, Kentucky 40422, United States

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The Journal of Physical Chemistry 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ABSTRACT New highly concentrated electrolytes based on ether solvents were developed for sodium electrochemical cells. The investigated electrolytes use sodium triflate and glycol diethers oligomers of different length to form the electrolyte. These electrolytes present conductivities that increase as a function of concentration even when the electrolyte is composed of a majority of ion pairs and aggregates. Correlation analysis between the electrolyte speciation and conductivity suggests the presence of two distinct mechanisms of charge transport, namely a traditional vehicular mechanism based on the diffusion of free ions and a hopping mechanism involving the making and breaking of ion-pairs and/or aggregates. The former mechanism represents the charge transport of glyme with 3 or 4 units, while the latter is observed in electrolytes composed of short chains; i.e., 1 or 2 units. The proposed mechanism of transport is corroborated via molecular dynamics simulations. In addition, our experiments demonstrate that the high concentration of the sodium salt not only increases the overall conductivity of the electrolyte, but also does not affect its electrochemical window.


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I. INTRODUCTION The increasing world demand for energy has prompted a race to improve the efficient production and use of energy. Among the possible pathways to increase the efficiency of energy generation, attention has been given to stationary energy storage devices for grid applications.1 The primary role of stationary storage is to accumulate the excess energy when the immediate consumption is lower than production. For example, the unused energy production in conventional power plants during the night or in solar plants in the middle of the day.1 While it is possible to envision using existing lithium-ion technologies for large stationary storage plants, the current cost of this technology makes it economically unviable.2-3 Thus, the use of other metal-ion technologies, such as sodium-ion, for large scale stationary energy storage have been proposed.2,4 Sodium and lithium share many chemical properties due to their similar electronic structure, providing incentive to consider sodium for metal-ion systems. For example the standard electrochemical reduction potential for sodium ion is -2.71V, which is only 0.3V lower than that of the lithium ion.2,4-7 However, sodium ion batteries (SIBs) intrinsically suffer from a loss in energy density not only due to the decrease in the electrochemical potential, but also as a result of an increase in the atomic mass of the element.8 These drawbacks are out-weighted by the high abundance and economic viability of sodium salts compared to those of lithium.4,7 Moreover, the global availability of sodium salts make it a suitable material for large enterprises such as those required in grid-scale operations.1-2 Finally, sodium-ion technology is thought to be environmental friendly due to its exceedingly large abundance in easily accessible salt deposits and the possibility of its incorporation with aqueous electrolytes.8 SIBs were first developed in the late 1970s; and since then, many different realizations of this technology have been demonstrated.2,4-5,7 However, the SIB technology is still far behind in its development compared to lithium-ion analogues. Among the different challenges of producing 3 ACS Paragon Plus Environment


operational SIBs, the development of suitable electrode and electrolyte materials are on the top of the list.4,9 While studies focused on finding appropriate electrode materials for SIBs have been numerous, the number of studies dedicated to the electrolyte is very limited in comparison.9 Nonetheless, the well-established lithium-ion storage technology has demonstrated that the selection of the proper electrolyte material is crucial for achieving optimal batteries.9 Some of the reasons for the necessary synergistic approach required to find the compatible cell materials (i.e. the interplay between electrolytes and electrodes) are the multiple roles of the electrolyte. For example, among the various roles, the electrolyte is responsible for charge transport in operando and also for the protection of the electrodes by forming the solid electrolyte interface.9 Battery electrolytes must fulfill a large number of requirements:2,5,9 chemical and electrochemical inertness, thermal stability, and high ionic conductivity. These electrolyte properties are strictly dependent on the chemical nature of their constituent solvents and salts.2,5,9 There has been growing understanding of the importance of various molecular properties of the electrolytes, such as charge transport behavior, decomposition, etc., in directly influencing battery characteristics, such as Coulombic efficient, cycling performance, and energy density of the cell.1012

Thus, there have been efforts to explore the correct salt-solvent combination for developing

operational SIBs. The first candidates were derived from the prior knowledge of lithium-ion batteries.2,4,6-7 In these SIBs, the electrolytes were based on sodium perchlorate or hexafluorophosphate and an organic solvent composed of organic carbonates and/or esters.5-6,9,1317

Since these first demonstrations, many different combination of carbonates and esters or ethers

have been tested with sodium perchlorate or hexafluorophosphate salts.5-6,9,17 More recently, the suitability of pure-ether based electrolytes was reported.17-19 Interestingly, ether based materials showed compatibility with graphite anodes, a property which was not observed for carbonate- or ester-based electrolytes.18 In addition, very recently, it was demonstrated that ether based sodium4 ACS Paragon Plus Environment

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ion electrolytes can be used in combination with sodium metal anodes.20 Furthermore, it has been shown that high concentration electrolytes help to lower the reactivity of the sodium anode.20-21 Glymes are currently a popular and widely used solvents for sodium electrolytes.9 Glymes are oligomers of glycol diethers with –[OCH2CH2]n– subunits where the smallest oligomer is monoglyme (see Scheme 1). Because of the ether bonds, glymes are usually more chemically inert solvents than organic carbonates.9 Although glymes do not have high dielectric constants, they have a good dissolution power due to the metal coordination ability of its oxygen atoms. In general, glymes tend to coordinate each sodium ion with six oxygen atoms at low salt concentrations, but the coordination number due to the glyme oxygen atoms around the sodium ion is reduced at high salt concentrations.22-25 Moreover, the coordination numbers of glymes appear to be higher than those for carbonate solvents,13,26-27 which emphasizes the importance of the chelation effect, especially in glymes with three or more subunits. In such cases, including triglyme and tetraglyme, the solvent molecule wraps around the sodium ion.22,25,28 Previous work has shown that the chelation effect of glymes to sodium ion plays a key role in the stability of the electrolyte via a significant charge donation to the sodium, which results in an increased stability against oxidative process at high salt concentrations.29 It has also been recently demonstrated that sodium-ions chelated with glymes intercalate in graphite electrodes and the intercalation is strongly dependent on the glyme structure.18,30-31 Surprisingly, the intercalation of the sodium ion is not directly related to the glyme length, or equivalently, a more favorable glyme chelation.18 Finally, it has been postulated that glymes not only improve the capacity retention during charge/discharge process via the co-intercalation of glyme-sodium complexes, but also enhance the kinetics of discharge when compared to carbonate-based electrolytes.32



Scheme 1. Molecular structure of sodium triflate, (a), and the different glymes: (b) monoglyme, (c) diglyme, (d) triglyme, (e) tetraglyme It is now evident that glyme-based electrolytes are natural contenders in the race for developing operational SIBs. Here, we present a new sodium ion electrolyte material based on high concentrated solutions of sodium triflate dissolved in various glymes (Scheme 1). Unlike the previous realizations of high concentrated electrolytes for SIBs,20,33 the electrolytes presented here use the triflate anion, which has shown an improved chemical stability in sodium batteries and fuel cells when compared to sodium hexafluorophosphate.19,34-35 Moreover, one study showed that 1M sodium triflate solutions in monoglyme and diglyme have ionic conductivities of ~10-3S.cm-1, sodium transport numbers of 0.5, and electrochemical windows of 0 to 4V.19 Our studies provide a detail examination on the conductivity and chemical stability as a function of both the concentration and the chemical nature of the solvent. In addition, the molecular mechanism behind the observed conductivities is deduced from infrared spectroscopy in combination with computational studies. Interestingly, our studies uncover and support a molecular mechanism of charge transport based on a hopping when the length of the glyme molecules is short and on a traditional diffusion process for glymes with long chains. II. EXPERIMENTAL AND THEORETICAL METHODS Sample preparation Sodium trifluoromethanesulfonate (CF3SO3Na, >98%), diglyme ((CH3)2[CH2CH2O]2O, >99%, water content 90 ppm) and tetraglyme ((CH3)2[CH2CH2O]4O, >99%, water content 110 ppm) were obtained from Acros Organics, monoglyme, ((CH3)2[CH2CH2O]O, >99%, water content 90 ppm) was obtained from MilliporeSigma and triglyme ((CH3)2[CH2CH2O]3O, >99%, water content 130 ppm) was obtained from Alfa Aesar. All the chemicals were used without further 6 ACS Paragon Plus Environment

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purification. Solutions having concentration ranging from 0.5M to 2.0M were prepared by mixing the components inside a N2 filled glovebox. The water content in all solutions ranged between 100 ppm and 300 ppm, as determined by Karl Fischer titration. Linear IR spectroscopy Fourier Transform Infrared (FTIR) experiments were performed using a Bruker Tensor 27 spectrometer with 0.5 cm-1 resolution. The samples were held in transmission cell (Harrick Scientific) having a pair of 2 mm calcium fluoride windows without a spacer. All samples cell were assemble inside a N2 filled glovebox. Each FTIR spectrum was recorded as an average of 40 individual scans. The measurements were performed at 25 °C. Since the samples were collected without spacer, all the spectra were normalized using the peak at 1200 cm-1 which does not show any significant changes with the type of the glyme and the concentration of the salt. Electrochemical measurements Ionic conductivity was measured using a YSI 3200 conductivity meter combined with a YSI 3250 cell probe. A modified glass sample holder was used to measure the samples. The temperature of the solutions was recorded using the temperature probe integrated with the cell probe. Cyclic voltammetry experiments were performed using an Autolab PGSTAT 302 potentiostat along with a three electrode system consisting of a glassy carbon working electrode, Ag/AgNO3 nonaqueous reference electrode, and Pt gauze counter electrode. Each cyclic voltammogram was recorded as an average of 3 individual scans and ferrocene was used as an internal reference to obtained the corrected the potentials. All measurement were performed inside a N2 filled glovebox. Rheology measurements



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The viscosity of the solutions was determined using a Brookfield DVI-II+ Pro viscometer having a cone plate with an angle of 0.8º and attached to a thermostatic water circulator. All the measure were performed at 25 °C. Chemometric modeling The Partial Least Squares (PLS) multivariate regression method was used to model the conductivity of the solutions as a function of the different species present in the sample, which in this case were derived from the FTIR spectra of the electrolytes. The PLS methodology has been extensively used in many areas of chemistry, and many literature works describe PLS in detail.3638

In brief, the PLS methodology finds the linear relationship between a variable Y and a set of X

predictors, such that one can express Y as: (1) 𝑌 = 𝑋𝐵 + 𝐸 where B represents a matrix of the regression coefficients and E is a matrix of errors. In general, the PLS model is described as: 𝑋 = 𝑇𝑃𝑇 + 𝐸𝑋

(2)

𝑇

(3)

𝑌 = 𝑈𝑄 + 𝐸𝑌

where T and U are the components matrix of X and Y, respectively, P and Q are the loading matrices, and EX and EY contain the error from the modeling of the predictors X and variables Y.3738

Here, the X predictors are extracted from the FTIR spectrum, while the Y variable represents

the conductivity. Thus, the PLS methodology allow us to find the spectral factors giving rise to the conductivity of the solution. All the PLS calculations were performed using Matlab R2015b software package within the line shape from 1000 cm-1 to 1060 cm-1 in each spectrum. This region of wavenumbers corresponds to the SO3 stretch modes of triflate ion (see text below). In each glyme, intensities of each spectra at different concentrations were used as the variables and the corresponding conductivity values were used as the responses. Hence, the PLS calculations provide a weight 8 ACS Paragon Plus Environment

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distribution which describes the spectral factors (weights), which change the conductivity values of the solution. Note that the PLS calculations do not require solvent background subtraction in their predictors, since the static spectral features of the solvent do not contribute to the change of conductivity of the electrolyte. Therefore, the PLS weights deliver the IR spectral signature of the ionic species directly correlated to the changes in conductivity, which can be modeled in order to calculate the ratios of free ions, ion pairs and aggregates in each glyme system. In addition, those IR solvent bands that change with the amount of salt (e.g., 1020 cm-1) will also be observed in the PLS weights because in the first approximation the charge transport is directly proportional to the concentration of salt. However, these solvent bands will not interfere with the quantification of the free ion, ion pair and aggregate because they are located at different frequencies. Molecular dynamics simulations Simulations were carried out using a PCFF based force-field for the solvent with modified ion-ion and ion-solvent interactions taken from previous work. This force-field was previously shown to reproduce the structural features of sodium triflate based glyme electrolytes.22,25 Using the Avogadro software,39 the starting structures of monoglyme, diglyme, triglyme, tetraglyme, and sodium triflate were built. Using the packmol software,40 cubic simulation boxes were set up with an initial length of 40.0 Å for monoglyme, 38.0 Å for diglyme, 41.0 Å for triglyme, and 45.0 Å for tetraglyme and filled based on a random packing algorithm. For each glyme, four different concentrations were simulated keeping the number of glyme molecules fixed, but varying the number of sodium triflate ion pairs. In the case of monoglyme, the simulation box contained 360 monoglyme molecules with 19 ion pairs for 0.5 M, 38 for 1.0 M, 57 for 1.5 M, and 76 for 2.0 M. For diglyme, the box consisted of 230 diglyme molecules with 17 ion pairs for 0.5 M, 34 for 1.0 M, 51 for 1.5 M, and 68 for 2.0 M. For triglyme, the simulation box consisted of 213 triglyme molecules with 19 sodium triflate pairs for 0.5 M, 39 for 1.0 M, 58 for 1.5 M, and78 for 2.0 M. For tetraglyme, the simulation box contained 213 tetraglyme molecules with 29 ion pairs for 0.5 9 ACS Paragon Plus Environment


M, 58 for 1.0 M, 87 for 1.5 M, and 116 for 2.0 M. Each box was equilibrated in the NVT ensemble for 1 ns at a temperature of 300 K, followed by 3ns simulation in the NPT (temperature of 300 K and pressure of 1 atm) ensemble using the Nose-Hoover thermostat and barostat. Following this equilibration, 30 ns production runs were carried out in the NVE ensemble and were used in the subsequent analysis of solvation structure and ion exchange hopping calculations (see supplementary information). All simulations were carried out under periodic boundary conditions with a time step of 1 fs using the LAMMPS suite of programs.41 The long range electrostatics were accounted for using the PPPM Ewald method. III. RESULTS AND DISCUSSION The conductivity of each glyme-sodium triflate electrolyte as a function of the salt concentration is shown in Figure 1. Notably, the conductivity of the diglyme electrolyte is always greater than that of triglyme and tetraglyme electrolytes in the 0.5m to 2.0m concentration range, or equivalently, from molar ratios of triflate to glyme of ~1/10 to ~1/3 (see supplementary information). In addition, while monoglyme electrolytes show similar conductivity to the electrolytes made of triglyme and tetraglyme, both monoglyme and diglyme electrolytes display a monotonic increase in their conductivities as a function of the salt concentration. In contrast, the triglyme and tetraglyme solutions show a maximum at ~1.5m and subsequent decrease in their conductivity curves. The trend observed for triglyme and tetraglyme electrolytes is the same as many other salts in organic solvents and it has been previously attributed to an increase in the overall viscosity of the solution and/or increased ion association between the metal cation and the salt anion to form ion pairs.9,15,42 The monotonic increase in the conductivity displayed by monoglyme and diglyme electrolytes is unexpected and, to the best of our knowledge, novel for sodium electrolytes in organic solvents. The lack of a maximum in the conductivity as function of concentration could arise from a lack of change in the solution viscosity. However, rheology experiments of the different electrolytes as function of the salt concentration demonstrate that 10 ACS Paragon Plus Environment

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glyme-based electrolytes do indeed follow the expected increase in the viscosity when salt is added (Figure 1 and supporting information for the individual plots).

Figure 1. Conductivity (a), viscosity (b), and Walden product (c) as a function of the molality for sodium triflate in different glymes: monoglyme (black), diglyme (red), triglyme (green), and tetraglyme (blue). The viscosity effect is “removed” from the overall ionic conductivity by computing the product of the molal conductivity and viscosity for each solution. Traditionally, at low concentrations the product of the concentration weighted conductivity and viscosity of a solution is used to define the Walden product. 43 Mathematically, it is expressed as: Λ∞ 𝑚η0 = C

(4)

where Λ∞ 𝑚 is the limiting molar conductivity and η0 is the viscosity of the pure solvent, and C is a constant. For electrolytes where the ions do not present ionic association (i.e., they are well coordinated by the solvent) the conductivity is solely govern by ion migration, i.e. vehicular 11 ACS Paragon Plus Environment


transport. In this particular case, the Walden product can be expressed analytically in terms of the ionic radius of the ions and the solvent friction, directly related to the viscosity of the solution through the Stokes’ law.44 In contrast, the conductivity of concentrated solutions is usually smaller than that computed from the infinite dilution conductivities due to an increase in the interionic interactions, which in turn reduces the mobility of the ions and increases the overall viscosity of the solution.45 This behavior is opposite to that exhibited by sodium triflate in mono- and diglyme where the conductivity increases with concentration even though there is a sharp increase in the viscosity when the salt concentration is increased. The Walden product, simply defined as the product of the molal conductivity and viscosity, is used as a metric of the ideality of the ionic transport in the solution. For electrolytes exhibiting low interionic interactions and diffusive transport of the ionic species, the Walden product is constant with respect to changes in salt concentration, even when the viscosity increases.45-47 In contrast, solutions with strong interionic interactions show a decrease in the Walden product. Note that the molal conductivities (m) are used in here because they do not have a strong dependence on the temperature of the solution as compared to the molar conductivities, but they show the same characteristics.48 The Walden product reveals the following trend: tetraglyme ≈ triglyme > diglyme > monoglyme, for electrolyte with low salt concentrations, i.e. 0.5 molal or below. The observed order of the weighted conductivity is expected given the coordination ability of the solvent and its direct relation to the number of free ions, or equivalent, charge carriers.25 However, at high concentrations (~2.0 m) all the glymes solutions, with the exception of monoglyme, show similar values in the viscosity-conductivity product. The observed products (~15 cP.mS.kg.cm-1.mol-1) are in all cases larger than the values at 0.5 molal concentrations. The behavior shown by the Walden product indicates that the charge transport at high salt concentrations might not be dominated by the typical diffusion transport, since one would expect a reduction in the conductivity when strong 12 ACS Paragon Plus Environment

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interionic interactions start to take place, such as in the case of high concentrated sodium triflate solutions, or a constant if the inter-ionic interactions are weak. In either case, the transport by diffusion does not predict growth of the viscosity-conductivity product with concentration. To understand the role of the ionic association of the sodium triflate in the conductivity of the sodium-glyme solutions, their solvation structures were characterized via FTIR spectroscopy. Given that the SO3 symmetric stretch is a good reporter of the ionic speciation of the triflate ions,4951

IR spectra in the SO3 symmetric stretching region as function of the concentration of sodium

triflate and the glyme length were considered (see Figure 2). The IR spectra reveal that triglyme and tetraglyme electrolytes have very similar spectral features irrespective of concentration. In contrast, the IR spectra of monoglyme and diglyme present different spectral features, as discussed previously in relationship to solvation structure.22,25 Using the previous SO3 symmetric stretching assignments for the different types of triflate ions in solution,22,49-51 it was determined that all electrolytes have a significant population of ion pairs/aggregates and that the concentration of free ions follows the trend reported previously of triglyme ~ tetraglyme > diglyme > monoglyme. This is notable since the Raman spectra shows that all solutions, even those with ~2m concentrations, have free solvent molecules (see supporting information). In addition, it is found that only monoglyme electrolyte exhibits substantial amounts of higher order aggregates as seen by the presence of the band at 1050 cm-1. All these results are in agreement with previous studies.22,25 Interestingly, the FTIR data also shows that the changes to the spectra for each glyme solution with increasing salt concentration can be described as the rise of a single component. Thus, from the previous analysis of the triflate ion speciation, one would expect that triglyme and tetraglyme electrolytes should have the highest conductivities compared to similar solutions of monoglyme and diglyme, because triglyme and tetraglyme salt solutions have a higher percentage of free triflate ions. Although the Walden product suggest that the conductivity mechanism is not 13 ACS Paragon Plus Environment


based on the traditional diffusion of ions, it is apparent that glyme-based electrolytes have a conductivity mechanism relying on free triflate ions since the Walden product is always higher for triglyme and tetraglyme which have the largest amount of free triflates in solution.25 However, one would also expect from a diffusion like mechanism of charge transport a decrease in the Walden product for mono- and diglyme electrolytes due to the large amount of interionic interactions as seen by the large amount of aggregates in their solutions. In contrast, diglyme electrolytes with high salt concentrations (Figure 1) exhibit very similar values of Walden products at high concentrations. The observation is in line with a charge transport mechanism not being dominated by the typical vehicular mechanism of charge transport. In particular, this hypothesis explains the similarity of viscosity-conductivity product of diglyme electrolyte compared to triglyme and tetraglyme electrolytes at high salt concentrations, even when the percentage of free ions in the diglyme electrolyte is clearly lower that in the other two electrolytes at the same conditions.

Figure 2 FTIR spectra of sodium triflate in four glymes: (a) monoglyme, (b) diglyme, (c) triglyme and (d) tetraglyme, with different concentrations: pure glyme (black), 0.5m (red), 1.0m (green), 1.5m (blue), and 2.0m (cyan). Note that FTIR spectra of sodium triflate in diglyme is presented for comparison purposes only. 14 ACS Paragon Plus Environment

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FTIR spectra as function of concentration provides good insights about the speciation of the solutions, but it does not directly inform us about the effect that the different species have on the conductivity. Therefore, PLS was used to obtain the spectral signatures of the ionic species giving rise to the observed ionic transport. In this case, transport is characterized by the viscosityconductivity product to minimize the solvent friction effect. Since the ionic transport in electrolytes depends on the amount and speciation of the ions present in the solution, i.e. free, ion pairs and aggregate, PLS is applied to the SO3 stretch IR region (Figure 2). PLS analysis shows that a single component is sufficient to explain the 90% variances (see supporting information) in each glyme within an overall error of less than 10% (Table 1). A cross validation of the PLS model is performed by calculating the Pearson correlation coefficient for the computed Walden products of each glyme as a function of the salt concentration (shown in Table 1). The predicted Walden product shows a good correlation coefficient with the experiment for all glymes except for triglyme, which has the most complicated behavior with concentration as seen from the nonlinearity. Note that the PLS model uses a single component to minimize over fitting problems, which also diminishes the predictive ability of the method.52 Table 1. PLS modeling of the conductivities at ~2.0m in each glyme electrolyte and the speciation of the PLS weight. Add PLS model vs experiment. PLS modeling

PLS weight fitting

m (Exp.) (mS.cP.kg.cm-1.mol-1) m (PLS) (mS.cP.kg.cm-1.mol-1) % error R2 Free ion Ion pairs Higher order aggregates

Monoglyme

Diglyme

Triglyme

Tetraglyme

2.2

13.6

15.3

17.8

2.3

12.8

16.8

18.8

2% 0.996 6±1 48 ± 1 46 ± 1

6% 0.963 36 ± 1 41 ± 1 23 ± 1

10 % 0.917 53 ± 1 35 ± 1 13 ± 1

6% 0.973 42 ± 1 52 ± 1 6±1



Figure 3. Calculated weights of the PLS model with one component and its fitting with Voight profiles for each glyme electrolyte, as indicated in the Figure and detailed in the text. Black dashed and purple solid lines correspond to the PLS weight and its fitting with Voight profiles corresponding to free ions (green line), ion-pairs (blue line), and higher order aggregates (red and magenta lines). The spectral components giving rise to the Walden product are derived from the PLS weights of the single component model (Figure 3), by fitting them with three Voigt profiles corresponding to free ions (1033 cm-1), ion pairs (1038 cm-1), and higher order aggregates (1042 cm-1). Note that an additional peak at 1049 cm-1 was needed in the modeling of the monoglyme PLS weights, and it is likely to arise from aggregates with different structure. The percentage ratio of each peak derived from the PLS weight/Voight modeling is tabulated in Table 1. The results show that the contributions from the ion pairs and aggregates are greater than free ion contribution in monoglyme and diglyme solutions, while the free ion contribution is dominant in triglyme and tetraglyme. The trend is the same as that observed directly from the FTIR spectra. Since in this case the PLS found a correlation between conductivity and ion speciation through FTIR, the results suggest the involvement of different conduction mechanisms in different glymes.


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The excess amount of free ions present in all the triglyme and tetraglyme electrolytes and its strong correlation with viscosity-conductivity product strongly suggest a typical diffusion-like mechanism for charge transport. The proposed charge transport mechanism is consistent with the change of conductivity as function of the sodium triflate concentration in triglyme and tetraglyme, where the conductivity increases until the concentration is 1.5m and then starts decreasing. While the drop in the conductivity at high salt concentrations could arise from the formation of ion pairs, the ratio of free to ion pairs is relatively constant, as demonstrated by the FTIR spectra (Figure 2), and indicates that at high salt concentrations viscosity is the dominating effect. Moreover, when the viscosity effect is removed from the conductivity the high concentration electrolytes for triglyme and tetraglyme show very similar values of viscosity-conductivity products, which is in agreement with the similarity of percentage of free ions present in the solutions (Table 1). The conductivity as function of concentration observed for the monoglyme and diglyme electrolytes cannot be simply explained using the traditional conduction mechanism. The conductivities do not show a maximum at 1.5m, but they monotonically increase with the salt concentration, even when, the viscosity of the electrolytes follows the same trend (Figure 1 and supporting information). Moreover, the ionic speciation of triflate ion derived from the PLS weights shows that monoglyme and diglyme electrolytes share a common feature: the presence of large amounts of ion pairs/aggregates relative to free ions. Therefore, the data suggests that the exceptional conductivity is due to a different conduction mechanism in which ion pairs/aggregates are mainly involved in an exchange mechanism in which the exchange facilitates the spatial “diffusion” of ions. This assumption is consistent with the almost linear dependence of the concentration of ion pairs/aggregates with the overall salt concentration of the solution, and with the lack of dependence on the solvent friction shown by the conductivity of these electrolytes. In other words, the formation of isolated ion pairs/aggregates domains retards the direct motion of 17 ACS Paragon Plus Environment


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ions at low salt concentrations. However, when the ion pairs/aggregate domains start to spatially overlap the charge transport stops being dominated by simple diffusion processes and starts being controlled by an exchange of anions between domains, which makes it independent of the solution viscosity. Hence, the conductivity of the monoglyme and diglyme solutions can be described by a hopping mechanism of triflate ions between ion pairs and aggregates. The hypothesis of a conduction mechanism based on a hopping mechanism is not new, but quite recent. Okoshi et. al. revealed that for sodium bis(fluorosulfonyl)amide in monoglyme an alternative mechanism pathway not involving diffusion could play a role in the charge carrier mechanism at high salt concentration.53 While Li et al. showed in previous simulation work that the diffusion constant of the sodium and triflate ions decreased as a function of concentration for all the glymes, the possibility of hopping as a non-vehicular mechanism of charge transport was not examined.25 The simulation results in the current work indicate, as expected, that sodium ions remain chelated to the same glyme molecules, but the triflate ion can exchange between different sodium complexes. Table 2. Triflate exchange and hopping rates, along with the fraction of ions that show exchange and hopping respectively, as a function of glyme chain length and salt concentration. Solvent

Conc. (m)

Monoglyme

0.6 1.2 1.8 2.3 0.6 1.1 1.7 2.2 0.5 1.0 1.5 2.1 0.6

Diglyme

Triglyme

Tetraglyme

Exchange Fraction Rate x 10-6 of ions (ns-1Å-3) 0.68 0.66 0.82 0.71 1.00 0.97 0.98 0.93 0.00 0.10 0.10 0.20 0.07

16 28 63 123.5 45 79 88 109 0 2 2 18 1 18

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Hopping Fraction Rate x 10-6 of ions (ns-1Å-3) 0.00 0.00 0.00 0.00 0.90 0.80 0.70 0.60 0.00 0.00 0.00 0.00 0.00

0 0 0 0 21 32 37 30 0 0 0 0 0

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1.2 1.8 2.5

0.14 0.37 0.37

4 23 34

0.0 0.04 0.03

0 2 2

The fraction of triflates that show exchange behavior (see supporting information for exact definition), is shown in Table 2 and the rate of exchange was also calculated for all the four glymes at different concentrations. As shown in Table 2, diglyme has the highest exchange rate, while triglyme has the lowest. Moreover, the exchange rate increases with increasing concentration except for triglyme, where it remains fairly constant till high salt concentrations. While it is observed that exchange occurs in all solutions, it is possible that exchange of triflate ions is only between a small group of ions, essentially a back and forth shuttling, and thereby not contributing to the conductivity seen experimentally. In order to differentiate the exchange and shuttling of triflate ions within an aggregate from productive forward hopping, a new definition of hopping is also considered (see supporting information). Based on this definition, the hopping rate for the different glymes as a function of concentration is derived (Table 2).

Figure 4. Snapshot depicting an aggregate structure wherein the triflate shuttles between different sodium ions in monoglymes (a) and triglymes (b), red corresponds to O atoms, blue to C atoms, yellow to S, pink to F atoms, dark blue to sodium and white to H atoms. The hopping rate shows that monoglyme and triglyme electrolytes exhibit negligible hopping of the triflate ion despite a non-negligible population of the anion engaging in the exchange process. The result is surprising given that the solvation structure of monoglyme derived 19 ACS Paragon Plus Environment


from the FTIR shows significant amount of aggregation with one triflate ion coordinated to multiple sodium ions, while virtually no free triflate ions are present. Thus, one would expect a large contribution of the hopping mechanism to the charge transport. However, our simulations of the monoglyme electrolyte also show that essentially all the triflate anions shuttle between a cluster of coordinating sodium ions (see Figure 4 for a representative structure), but the shuttling does not contribute to productive hopping of the anions beyond this cluster. Similarly, in triglyme most triflate anions did not show hopping, but only shuttling among different coordinated sodium ions (see Figure 4 and Figure 5). The origin of the shuttling versus the exchange mechanism can be attributed to the different solvation environments around the sodium ions in diglyme versus monoglyme and triglyme. In previous work, it was shown that around 0.8 fraction of sodium ions in diglyme have just one contact ion in their solvation shell and the remaining sodium ions have no counterions in the solvation shell.25 Hence, in the case of diglyme the hopping of triflate ions typically results in exchange or vice versa. On the other hand, in monoglyme and triglyme there is significant aggregation (~40% as in Ref. 25), and so shuttling take place for the triflate ions among different coordinating sodium ions of the aggregate (Figure 5). In addition, one expects that at longer time scales the triflate anion will eventually “hop” between different ion pair/aggregate domains, which will explain the conductivity of monoglyme electrolytes. However, this long range hopping is a behavior that cannot be captured by the present simulations due to limitations in both length and time scales.


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Figure 5. Cartoon representation of the molecular mechanism of (a) hopping and (b) shuttling. Productive hopping is only observed in electrolytes composed of diglyme and tetraglyme. In the tetraglyme electrolytes, productive hopping takes place, but the percentage of triflate ions that display hopping behavior is small and non-negligible only at high concentrations. In contrast, sodium triflate in diglyme presents a significant portion of ions that are engaged in productive hopping at all concentrations. Moreover, the hopping rate of triflate ions is quite large even in diglyme solutions with low concentrations of ions. In addition, the hopping rate appears to be constant with concentration for concentrations larger than 1m. The observed hopping rate explains not only the quasi-linear behavior of the conductivity of diglyme electrolytes as a function of concentration of the salt, but also the divergence in behavior between triglyme and tetraglyme electrolytes. In the latter, an increase in the viscosity weighted conductivity is observed at very high concentrations of sodium triflate in diglyme (Figure 1), which is likely to occur due to the opening of the hopping mechanism pathways in the charge transport as demonstrated by the simulations. While the MD simulations demonstrate that the molecular diffusion is dominated by hopping of triflate ions in diglyme and by shuttling in monoglyme and triglyme, the molecular 21 ACS Paragon Plus Environment


reasons behind the observed behavior are beyond the scope of this paper and will be address in a subsequent study.

Figure 6. Cyclic voltammetry. Cyclic voltammogram of triglyme (top) and diglyme (bottom) electrolytes with 1 M (red) and 2 M (black) sodium triflate concentrations. The study so far has shown that these electrolytes have favorable properties for using them as electrolytes. Adelhelm et al. have previously demonstrated that sodium triflate electrolytes can be used in rechargeable sodium-ion batteries.15 In order to demonstrate that the high salt concentration do not affect the chemical stability of the glyme based electrolytes, the electrochemical properties of two electrolytes with completely different conduction mechanisms and ionic speciation are compared. For this purpose, the cyclic voltammetry of sodium triflate in diglyme and triglyme at 1M and 2M concentrations were measured. The voltammograms ( Figure 6) demonstrate that the electrochemical window of the electrolytes does not vary significantly when the concentration of the salt is increased from 1M to 2M. In the case of diglyme electrolytes, the voltammograms are almost identical for the two concentrations. In contrast, there is a small decrease of the electrochemical window of the triglyme electrolyte indicating that the presence of high concentration of ion pairs might be detrimental for this particular electrolyte. 22 ACS Paragon Plus Environment

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SUMMARY The conductivities of sodium triflate in glymes of different length show that diglyme presents the largest conductivity among all glyme electrolytes in the concentration range of 0.5-2 M. Moreover, the monoglyme and diglyme electrolytes show a monotonic increased in the conductivity with the salt concentration, which is not observed in the triglyme and tetraglyme. Rheology studies reveal that the observed behavior in the conductivity of the investigated electrolytes cannot be simply explained by viscosity effects. Here, it is shown that conductivity phenomena in these glyme electrolytes arise from different charge transport mechanisms. Long chain glymes appear to favor a vehicular conduction mechanism via free triflate ions in which the anion diffuses through the solution to produce charge transport. In contrast, short chain glymes favor a mechanism in which the charge transport is carried out by the hopping of the triflate between aggregates and/or ion pair domains. The proposed mechanism of charge transport is corroborated via computational studies and provides a molecular picture for the experimental conductivity data. The observed results suggest that changes in chemical composition of the electrolytes (mixed glymes, different counterion ion, etc.) that result in different solvation environments can directly impact charge transport. These studies highlight the importance of design principles derived from atomistic characterization of the electrolyte for finding optimal electrolyte compositions from the wide range of possible combinations. ASSOCIATED CONTENT Supporting Information This Supporting Information is available free of charge on the ACS Publications website at DOI: Conductivities and viscosities for the individual electrolytes, PLS explained variance as a function



of the number of PLS components, PLS predicted Walden product, and the fitting parameters of the PLS weights with Voight profiles. AUTHOR INFORMATION Corresponding Author * E-mail: [email protected]. Tel: (+1) 225-578-1780 ORCID Daniel G. Kuroda: 0000-0002-4752-7024 Revati Kumar: 0000-0002-3272-8720 Ryan Jorn: 0000-0002-0192-9298

Notes The authors declare no competing financial interest. ACKNOWLEDGMENT The current work was supported in part by start-up funds provided to DGK and RK by the LSU Department of Chemistry and computer time allotted by the high performance center at LSU and the Louisiana Optical Network Initiative.


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Mechanism behind the Unusually High Conductivities of High

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