Investigation of the Relationship between Solvation Structure and

density would bring the benefits of reduced storage space and thus expand the range of ... The solvation state in these liquids are of interest, due t...
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Investigation of the Relationship between Solvation Structure and Battery Performance in Highly-Concentrated Aqueous Nitroxy Radical Catholyte Ruidong Yang, Yong Zhang, Kensuke Takechi, and Edward J. Maginn J. Phys. Chem. C, Just Accepted Manuscript • DOI: 10.1021/acs.jpcc.8b00915 • Publication Date (Web): 21 May 2018 Downloaded from http://pubs.acs.org on May 21, 2018

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Investigation of the Relationship between Solvation Structure and Battery Performance in HighlyConcentrated Aqueous Nitroxy Radical Catholyte Ruidong Yang1,‡, Yong Zhang2,‡, Kensuke Takechi1,*, Edward J. Maginn2,*

1. Materials Research Department, Toyota Research Institute of North America, 1555 Woodridge Ave., Ann Arbor, MI 48105 2. Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, IN 46556 ‡These authors contributed equally

Corresponding Authors: Kensuke Takechi: [email protected]

TEL: +81-561-71-7751

Edward Maginn: [email protected]

TEL: +1- 574-631-5687

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ABSTRACT

A

new

battery

catholyte

material

composed

of

equilmolar

4-methoxy-2,2,6,6-

tetramethylpiperidine 1-oxyl (MT) and lithium bis(trifluoromethanesulfonyl) imide (LT) and its highly concentrated mixtures with water were studied using experiments and molecular dynamics simulations. It was found that the dynamic properties of the mixture are significantly improved by adding even a small amount of water. Detailed analysis on the solvation structure in the mixtures reveals that water molecules can break the strong interaction between MT and LT and thus the ions can move more freely. As a result, the ionic conductivity of the catholyte mixtures increases with increasing water molar ratio in the water concentration range covered in the current work. The performance of the catholyte mixture systems was also tested in battery cells. The best utility efficiency of the capacity was found for the mixture of water:MT:LT ratio at 5.3:1:1. Water molar ratios of 5 to 6 was also found to be the lowest concentration that MT and LT are fully saturated by water. These results provide insightful understanding of the performance of these battery catholytes.

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1. Introduction Redox flow batteries (RFBs) have attracted much attention in the energy storage research field due to the unique feature of using a fluidic material as an energy storage media.1-5 This feature brings multiple merits over traditional secondary batteries, such as the decoupled requirements on electrolyte storage and cell design.2 However, the low energy density of liquids has limited their broad application. Efforts have been made to solve this problem, such as by employing lithium ions (Li+) as charge carriers6-8 to enhance the operational voltage. Improvement of the energy density would bring the benefits of reduced storage space and thus expand the range of applications.

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Figure 1. Derived atomic partial charges for MT and TFSI- using the RESP method at B3LYP/6311++g(d,p) level. C atoms are shown in gray, H in white, O in red, N in blue, S in yellow and F in light blue. Recently,

a

type

of

highly-concentrated

catholyte

using

4-methoxy-2,2,6,6-

tetramethylpiperidine 1-oxyl (MT) as a redox compound has been reported.9 The energy density of the catholyte reaches 200 Wh/L, and is recognized as the highest achieved record for all organic/inorganic electrolytes1. Such a highly-concentrated electrolyte is achieved via a “molten redox” technique, by which the redox active material (MT, see Figure 1) melts with the plasticizing lithium salt (lithium bis(trifluoromethanesulfonyl) imide (LiTFSI or LT)). MT molecules are found to coordinate to Li+ and the catholyte is characterized as a “solvate ionic liquid”. With addition of water, the catholyte exhibits improved properties (e.g. conductivity and viscosity), making the system suitable for practical battery application. Intriguingly, no bulk water behavior (such as icing) are observed in the differential scanning calorimetry (DSC) analysis at low water contents (water molar ratio < 11), implying the resulting aqueous catholytes maintain the nature of “solvate ionic liquid”. The solvation state in these liquids are of interest, due to the fact that both MT and water coordinate the ions. On the other hand, an emerging technology of highlyconcentrated aqueous electrolyte for lithium ion batteries (LIBs) was reported, and shares the same characteristic property like minimal amount of water in a large quantity of lithium salt.10-12 Unique features such as much expanded electrochemical window (ECW) were achieved in these aqueous electrolytes. The strong coordination force of water to Li+ is believed to contribute the extraordinary property. Thus, understanding the solvation structure and dynamics in these highlyconcentrated aqueous systems becomes substantially important.

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Molecular simulation has been demonstrated to be an effective tool to understand the solvation structure of multiple types of highly-concentrated non-aqueous electrolytes.13,14 The equimolar mixtures of LT and glymes were studied by Tsuzuki and coworkers using molecular dynamics simulations.15 It was found that, in both triglyme (G3) and tetraglyme (G4) mixtures, Li+ prefers to coordinate with oxygen atoms of glyme than the oxygen atoms in TFSI-. The results showed good consistency with the calculated and experimental trend that the Li+ and glymes have nearly identical self-diffusion coefficients. Similar behavior was also observed by Sharma and coworkers,16 who pointed out that the strong coordination between the cation and glymes was due to the localized negative charges in the glyme molecules. Furthermore, Saito and coworkers added hydrofluoroethers (HFE) as the diluent to the Li+/TFSI-/G4 electrolyte systems.17 It was found that the diluent affects the Li+ solvation structure although HFE does not directly coordinate with Li+. These results are consistent with Raman and high-energy X-ray total scattering (HEXTS) experiments.17 In addition, simulation results reveal that the three central oxygen atoms of G4 strongly coordinate with Li+ whereas the coordinating status of the two terminal oxygens can frequently change. In this work, both molecular dynamics simulation and experimental analysis are utilized to investigate the solvation structure in the highly-concentrated MT catholytes. The complex interactions among water, MT, Li+, and TFSI- are systematically studied. Properties of the catholytes are found to be well related with the interactions. The mechanistic understandings of the solvation structure of the catholytes are also correlated with their battery performance. The gained insights will direct future efforts in designing the catholytes. In addition, the knowledge from studying the water structure should be valuable to understand the properties of highlyconcentrated aqueous electrolyte systems from a different perspective.

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2. Experimental and Theoretical Methods 2.1 Simulation Procedure. Classical molecular dynamics (MD) simulations were carried out using the package LAMMPS.18 In such simulations, the accuracy of the results depends on the applied force field. The general Amber force field (GAFF)19 was used to describe the MT and LT molecules in the current study. This force field has been widely used on organic and ionic liquid systems and proved reliable.20 In order to derive atomic charges used with GAFF, electronic structure calculations were carried out on an isolated ion or neutral molecule to optimize the structures at the B3LYP/6-311++g(d,p) level using Gaussian09.21 The atomic charges were then derived based on the optimized structure by fitting the electrostatic potential surface obtained from these calculations using the RESP method.22 Such charges have a total value of ±1 e on the cation and anion, respectively. To approximate the effect of charge transfer and polarizability in the bulk phase, the partial charges were scaled uniformly by 0.8. The 0.8-scaled charges have been found to be reliable for the study of dynamic properties of similar ILs.20 The SPC/FW model23 was used for water molecules. The long range electrostatic interactions were calculated using the particleparticle particle-mesh (PPPM) method24 with real space cutoff of 12 Å. For all simulations, a time step of 1 femtosecond (fs) was used and periodic boundary conditions were applied in all directions. The simulation box was built up by putting molecules randomly in a cubic box using the package Packmol.25,26 The number of molecules in each box are summarized in the Table S1 in the Supporting Information (SI). The systems were then equilibrated for 2ns in the isothermalisobaric (NPT) ensemble followed by 70 ns canonical (NVT) ensemble production runs. The NoseHoover thermostat27 and the extended Lagrangian approach28 were applied to control the temperature and pressure, respectively. Simulations were carried out at elevated temperature of 500 K because the dynamics of the system are far too slow at ambient temperatures to be captured

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with these simulations. The only exception is the density, which was able to be calculated at 300 K so that it can be compared directly to experimental results at room temperature. We expect that trends and liquid structure among the species observed at 500 K will also be observed at lower temperatures.16 More discussion on this is provided in section 3.2.1. The pressure was fixed at one atmosphere in all constant pressure simulations with isotropic volume fluctuations. 2.2 Materials. MT (>98.0%, Tokyo Chemical Industry Co.) and LT (99.80%, Kishida Chemical Co.) were used as purchased without further purification. The preparation of the mixture of the MT and LT was conducted in an ambient atmosphere. An equivalent molar amount of each material was mixed with adding an appropriate amount of deionized water. The mixture was sonicated in Branson B5510 ultrasonic cleaner for about 30 mins to 1 hour to ensure homogeneity. 2.3 Measurement of the Liquid Characteristics. Raman spectroscopy measurements were performed using a Horiba Scientific LabRAM HR800 with a 532-nm laser. The density was measured using a Mettler Toledo Densito 30PX density meter. The conductivity was measured using the AC impedance technique with a BioLogic VMP3 multichannel potentiostat that includes frequency response analyzer modules. The electrochemical cell used for conductivity measurement has Pt disk electrodes (13 mm of diameter) facing each other with a gap of 5 mm to be filled with liquid samples. The cell constant was determined by measuring the standard KCl solution in advance. The viscosity was measured using a Thermo Scientific HAAKE RheoStress 1 rheometer with a cone/ plate geometry in combination with a temperature control unit. 2.4 Battery Tests. The battery test was conducted with a customized cell. A sheet of carbon paper (Toray Industries, TGP-H-060) with a thickness of 190 μm and a diameter of 15 mm was used as a current collector of the cathode. A 30 μL of catholyte was used for all evaluations. Li metal and 1 M LT in propylene carbonate was used as the anode and its electrolyte, respectively.

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Li-ion conducting glass ceramics (Ohara) with a 0.15 mm thickness were used as the separators and were located between the cathode and anode compartments. All the battery characteristic tests at 25 °C were determined using a Bitrode battery testing system (model: MCV). 3. Results and Discussion 3.1 Viscosity and Self-Diffusion Coefficients. MT was mixed with LT at 1:1 molar ratio, and water was added at varied molar ratios (x) that are 1, 2, 4, 5, 6, 7, 11, 18, 26. Homogenous liquids of orange color were formed at all compositions. The fluidity of the liquid was found to be improved with higher water amount.

Figure 2. Viscosities measured at 298 K of the samples MT:LT:water=1:1: x (molar ratio) as a function of water molar ratio. Viscosity of the catholytes at different water molar ratios (2.1, 4, 5.3, 10.7 and 21.4) were experimentally measured at 25 ºC. The results are shown in Figure 2. Lower viscosity was found with increased amount of water. The effect of water addition was found to be more dramatic when the water ratio was low. To further study the dynamic properties of the catholytes, the self-diffusion coefficients were calculated based on MD simulations. Before calculating the self-diffusion coefficients, the

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densities of the MT:LT:water = 1:1:x (molar ratio) mixtures were calculated at 300 K as a validation of the force fields. The calculated densities are compared with the experimental data (298 K) in Figure 3. As shown in the figure, in spite of small deviations, the overall trends are the same in the calculated and experimental densities. The largest deviation was observed at high water concentrations and was found to be as small as 2%. Therefore, the applied force fields are judged to be capable of capturing the experimental density reasonably well.

Figure 3. Comparison of calculated density (300 K) and experimental density (298 K) for catholytes mixtures of various water molar ratio. Based on the NVT ensemble simulations, the self-diffusion coefficients were computed from the mean-square displacements (MSDs) using the Einstein relation: 𝐷𝐷𝑠𝑠 =

1 𝑑𝑑 lim 〈(𝑟𝑟𝑖𝑖 (𝑡𝑡) − 𝑟𝑟𝑖𝑖 (0))2 〉 6 𝑡𝑡→∞ 𝑑𝑑𝑑𝑑

where ri(t) is the center of mass (COM) position of ion or molecule i at time t. The COM selfdiffusion coefficient of each species as a function of water molar ratio at 500 K calculated from the normal diffusion region of the MSD curves are shown in Figure 4.

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Figure 4. Calculated center of mass (COM) self-diffusion coefficients of each species in MT/LT/water mixtures at 500 K based on 70 ns NVT ensemble trajectories. Lines are added to guide the eye. Results are split into two plots due to the different scales. As shown in Figure 4, the self-diffusion coefficients of water are significantly higher than other species in all solutions. MT molecules were found to diffuse faster than Li+ ions and TFSI- were the slowest diffusion species. It is worth mentioning that Li+ moves faster than TFSI- in these mixtures whereas they usually follow the opposite trend.29 For all species, the self-diffusion coefficients increase as the water molar ratio in the mixtures increases. This is consistent with the trend in the experimentally measured viscosities. The increases in the calculated self-diffusion coefficients are roughly linear for Li+, TFSI- and water. For MT, however, the increase clearly

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deviates from linear behavior, as the increase is faster at low water molar ratio and slows down after the water molar ratio is higher than 5-6. For the dry MT/LT system (without water), the dynamics were slow even at the elevated temperature of 500 K, and a 70 ns trajectory was not enough to derive reliable self-diffusion coefficients. Based on the mean-squared displacements, the dynamics in this system was estimated to be at least one order of magnitude slower than that in the x=2 mixture. In above discussion, the calculated MSD and self-diffusion coefficients present the average distance that a species moves within a time t. The heterogeneity in dynamics of each species was also studied. The results are provided in the SI. 3.2 Liquid Phase Structure. In order to understand the behavior observed in the transport and dynamic properties, the liquid phase structure of the mixtures was studied in detail using both MD simulation and Raman spectroscopy. 3.2.1 Liquid Phase Structure from MD Simulation. Based on the NVT ensemble MD simulations, the liquid structure of the mixtures was studied in terms of radial distribution functions (RDFs), coordination numbers (CNs) and spatial distribution functions (SDFs). Several selected COM pair-wise RDFs are shown in Figure 5. It is interesting to note that the first Li+-water RDF peaks are at an even shorter distance than those of Li+-TFSI-, indicating the close packing between Li+ ions and water molecules, which is at least partially due to the relatively small size of water molecules compared to TFSI- ions. The other observation worth mentioning is the significant reduction in peak height of the primary peak in Li+-MT RDF when water is introduced into the system (even with as few as two water molecules per MT/LT). These results suggest that a small amount of water is able to break up Li+-MT association, which would play a role in changing the liquid dynamics.

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TFSI- is known to be hydrophobic. MT is a relatively large molecule (see Figure 1) with multiple potential interaction sites with water. Therefore, it is not a surprise that the TFSI-water, MT-water and TFSI-MT RDFs do not show well organized structure as in Li+ related RDFs.

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Figure 5. Calculated COM RDFs for selected systems at 500 K based on 70 ns NVT trajectories. Note the different scales on both X-axis and Y-axis.

Figure 6. Calculated center of mass coordination numbers (CNs) in the first solvation shell. The first solvation shell was defined as the minimum between the first and second maxima in the

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corresponding RDF. In each plot, the legend label “A-B” indicates the coordination number of B surrounding a central A.

Figure 7. Calculated partial radial distribution functions (PRDFs) between the sites Li+, O of TFSI, O of water and O of N-O group in MT based on 70 ns NVT trajectories at 500 K. Only one of four equivalent O atoms of TFSI- was considered in the calculation. Note the different scales on both X-axis and Y-axis.

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Figure 8. Calculated coordination numbers (CNs) in the first solvation shell based on partial RDFs shown in Figure 7. The first solvation shell was defined as the minimum between the first and second maxima in the corresponding RDF. In each plot, the legend label “A-B” indicates the coordination number of B surrounding a central A. Note that only one of four equivalent O atoms of TFSI- was considered in the calculation.

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Figure 9. a) Spatial distribution functions (SDFs) of species surrounding MT molecules (two side views for each case). b) SDFs of species surrounding TFSI- ions. The color coding of atoms in the central molecules follows the same definition as in Figure 1. The maximum probability relative to the bulk density, similar to the peak heights in RDFs, in each system are provided in the box for

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each system. The maximum densities normalized to the Li+ bulk density in dry MT/LT system are also provided in parenthesis. Using the calculated center of mass RDFs, the coordination numbers in the first solvation shell were calculated for each solution. The first solvation shell was defined as the minimum between the first and second maxima in the corresponding RDF. The results are shown in Figure 6. When water is introduced to the mixture, the Li+-MT coordination numbers drop sharply from ~0.7 to less than 0.2, consistent with the RDFs: a small amount of water breaks up the association between Li+ and MT. Similar behavior was observed for the coordination number between TFSI- and MT, which drops from ~2.4 to 1.0 with the addition of a small amount of water. This means that small amounts of water weaken the TFSI- and MT association. When additional water is added, however, the coordination numbers between Li+-MT and TFSI--MT drop only slightly. On the other hand, the coordination numbers between Li+ and TFSI- also decrease but in a continuous and gradual way from over 2.6 in pure MT/LT to ~2.3 in the most diluted solution studied in the current work. As expected, the number of water molecules surrounding Li+, TFSI- or MT keeps increasing as the concentration of water increases. It is interesting to note that the number of water molecules associating with MT increases sharply when the water concentration is relatively low in the mixture, reaches a maximum for x=4, decreases slightly and increases again almost linearly up to ~6.5 waters per MT at x= 22. Similar behavior was observed for the water molecule numbers coordinating to TFSI-. The slight decrease in CNs was found to be caused by the slight variation in the distance that defines the first solvation shell. The RDF integration curves used to calculate the CNs are provided in Figure S1 in SI. It can be seen from the figure that the integration curves always follow the order in water fraction. On the other hand, the fact that the small variation in the cutoff distance and CNs can change the relative trend in the CNs around x=6 suggests that the CNs

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are very close to each other in the mixtures with x=3-6, which can be seen in Figures 6b and 6d. This is consistent with the observation that small amount of water change the LT/MT liquid structure significantly but such change slows down when more water is added to the mixtures. As mentioned earlier, center of mass RDFs sometimes are not the best way to present the solvation structure of molecules like TFSI- and MT. Selected partial RDFs between the sites of O(TFSI), O(N-O in MT) and Li+ and O(water) were calculated. The results are shown in Figure 7 and the corresponding CNs are shown in Figure 8. There are four equivalent O atoms in TFSI-, but only one is considered in the calculation. As shown in Figure 7, all the RDFs show a first peak at a shorter distance than in the corresponding center of mass RDFs. For Li-O(TFSI), the peak position is similar to that of Li-water (Figure 5e). The calculated CNs follow similar trends seen in the center of mass CNs although absolute values are different for most cases. It is interesting to note that the Li-O(TFSI) CN is around 1.2-1.3 for each O in TFSI-, which suggests a total CN of ~5 for all four O atoms. As shown in Figure 6a, the total CN between Li+ and TFSI- center of masses was found to be ~ 2.5. These results suggest that the coordination of most TFSI- are bidentate in these interactions. To study the effect of temperature on the observed trend in liquid structure, the center of mass RDFs and coordination numbers were also calculated at 300 K and compared to those obtained at 500 K. The results are shown in Figure S3-S6 in SI. The peak heights show variation at different temperatures, but the shapes are more or less the same. In addition, as shown in Figure S7 in SI, the trends in the coordination numbers at 300 K as a function of water fraction agree very well with those obtained at 500 K, which confirms that the results obtained at elevated temperature in the current work can provide meaningful insight of the studied systems.

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The calculated spatial distribution functions (SDFs) for species surrounding MT and TFSImolecules are provided in Figures 9a and 9b, respectively. In the dry MT/LT mixture, Li+ are adjacent to the MT ring and TFSI- ions are located under the MT molecule surrounding the N-O group. The maximum probability of finding Li+ and TFSI- molecules in these locations are 1.7 and 11.6 times of their bulk densities, respectively. Such a distribution is dictated by the partial charges of the MT molecules as shown in Figure 1. It can be seen from the figure that ions are attracted to sites with localized opposite charges. For TFSI-, on the other hand, Li+ were found to be close to terminal CF3 groups whereas MT locates in two “slabs” surrounding the middle of TFSI-. The maximum probability of Li+ and MT in these areas are 2.0 and 8.7 times the bulk densities, respectively. The partial charges of TFSI- used in the current study are shown in Figure 1. Compared to the dry MT/LT mixtures, when two water molecules per MT/LT were added to the mixture (x=2), the liquid packing structure changed dramatically. For MT, water was found to locate in the direction of the N-O group, in the middle of the TFSI- distribution. The maximum probability of water is 2.3 times the bulk density. With the water molecules added to the mixture, the probability of finding TFSI- in the same area decreased significantly to 3.6 times the bulk density. When normalized to the bulk density of Li+ in the dry MT/LT system, so the values in different mixtures can be compared relative to the same reference state, this probability is even lower (3.2 times) due to the diluting effect of the addition of water molecules. The maximum Li+ probability was found to be close to the bulk density (1.1 times) and does not have a well-defined preferred location. It is worth mentioning that if normalized to the same standard (Li+ bulk density in dry MT/LT), the water concentration (4.1) surrounding MT is higher than both Li+ (1.0) and TFSI- (3.2), indicating the stronger interaction between MT and water than the interactions

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between MT and Li+/TFSI-. These results are consistent with the observations that a small amount of water breaks up MT-TFSI- and MT-Li+ associations. A similar change in local packing structure was also found for species surrounding TFSI- ions. Water molecules were found to prefer the area around TFSI- oxygen atoms and the MT distribution was squeezed to the area close to the nitrogen atom. Li+ ions are still in the same area as in the dry MT/LT liquid, but the maximum probability decreased from 2.0 times bulk density to 1.4 times bulk density (or 1.2 if normalized to dry MT/LT liquid). The maximum water density was found to be 1.9 times bulk density and the normalized density (3.3) is getting close to that of MT (4.4). These results are consistent with the CNs calculated from RDFs in which the CN of water coordinating to MT increased more significantly than those to Li+ or TFSI- ions. These results suggest the strong interaction and solvation effect of water on MT, even for relatively low water concentrations. It is clear from the above discussion that the addition of water to the MT/LT mixture, even in a small amount, breaks the close interaction among Li+, TFSI- and MT molecules, which is responsible for the decrease in the liquid viscosity (Figure 2) and the increase in self-diffusion coefficients (Figure 4). When more water is added to the mixture with x=6, the liquid structures are similar to that of x=2 except that the normalized water density surrounding MT and TFSI- molecules keeps increasing whereas the density of other surrounding species keeps decreasing slowly. Accordingly, as shown in Figure 4, the MT self-diffusion coefficients increase almost linearly in this water concentration range. With even more water, the solvation structures surrounding MT and TFSI- do not change much, but the extra water starts to form clusters and aggregates. As a result, the increase in the calculated self-diffusion coefficients slows down.

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3.2.2 Liquid Molecular Interaction Analyzed via Raman Spectroscopy. Raman spectroscopic analysis was employed to study the molecular structure changes at different water molar ratios. Raman bands in the range of 3000-4000 cm-1 corresponds to the O-H stretching modes in water molecules. Intensity of different peaks evidently varies with different water ratios in this broad region (Figure 10a). The peaks are also summarized in Figure S11. Due to varied interactions between neighboring molecules around water, the complex peaks in this broad region can be decomposed into a number of Gaussian-shaped functions.30,31 When water content increases, the bands centered at ~3250 and ~3445 cm-1 become more apparent, implying the formation of a greater number of water clusters (free water). As for the peaks at ~ 3560 cm-1, they are only observed in the MT catholytes but not in pure water. Appearance of these peaks in liquid solutions has been rare, and as suggested in the literature11, they do not occur in common lithium salt aqueous solutions, such as saturated LiNO3 or Li2SO4 solutions. These peaks have been regarded as the characteristic sign of crystalline hydrates, and in the case of highly-concentrated electrolytes, the peaks have been suggested as the interactions of water molecules in the Li+ solvation shell11.

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Figure 10. a) The Raman spectra in the O-H stretching region for the MT/LT/water mixture. The samples are prepared at molar ratio of MT/LT/water=1:1:x with x indicated in the plots. b) Percentage fraction of hydration water to the total area with band peaking at ~3445 cm-1 at different water ratios. The fractions are calculated from the fitted curve shown in Figure S12. c) FWHM results of the peak at ~3445 cm-1 (filled circles) and the peak assigned to hydration to Li+ (open triangles). All above-mentioned three bands are used to decompose the spectra in the O-H stretching region. The fitted curves for the peaks at ~3445 cm-1 are used to represent free water due to the less interference. (The detailed fitting results are provided in Figure S12.) The area percentage of free

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water and solvating water (at ~3560 cm-1) are calculated based on the fitted curves with results shown in Figure 10b. The fraction of solvating water is found to be relatively stable up to a water ratio of x=4, followed by a linear drop as the water concentration increases. The full width at half maximum (FWHM) of both peaks are also analyzed. The results are shown in Figure 10c. The width of the vibrational spectrum reflects molecular collisions at varied concentrations. As for the peaks for free water, a monotonic increase is observed as the amount of water goes up. It suggests the enhanced intermolecular collision among water molecules, and the continuously increased amount of free water. On the other hand, the broadness of solvation peak rises only before water ratio reaches 4, implying no further water participating in solvation. Thus, the solvation shell of water surrounding Li+ should be fully established at water molar ratio of 4, even with the existence of an extra solvating compound (MT) in the electrolytes. Such observation from figures 10b and 10c shows good consistence with the simulation results.

Figure 11. a) Raman spectra in the region of nitroxyl vibration. The samples are prepared at molar ratio of MT/LT/water=1:1:x, with the x indicated in the plots. b) Percentage fraction of bands assigned to different N-O vibrations.

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The spectra in the N-O stretching vibration region are summarized in Figure 11a. The peak at ~1386 cm-1 is attributed to the N-O vibration in pure MT molecule. In the catholyte mixture, the intensity of this peak fades significantly with the emergence of the other two series of peaks at 1405-1408 cm-1 and 1394-1397 cm-1, respectively. The peaks at 1402-1408 cm-1 are attributed to the coupling effect via the interactions between N-O and Li+, which has been carefully discussed in our previous report.9 Interestingly, the peaks at 1394-1397 cm-1 have never been observed in the dry LT/MT mixture. This series of peaks could be assigned to interactions between N-O and water via hydrogen bond, which was observed in the simulation work (see Figure 9a). All three peaks are used to the deconvolute N-O vibration region by Gaussian functions and the details are displayed in Figure 136. The area percentages of the three bands are calculated from the fitted curves and summarized in Figure 11b. When the water molar ratio is below 5, the amount of N-O groups coupling Li+ was found to decrease dramatically, while the percentages of the other two peaks increases. Such results suggest the coupling between MT and LT is reduced by adding water, demonstrating the exact observation from the simulation result (Figures 5-9). The results also show good agreement with the result of increased Li-water interaction observed from spectra in the water O-H stretching region. On the other hand, more MT molecules exist at either isolated state or coupled with water. The isolation effect from water reduces the strong Columbic force of MT-Li+ and is believed to contribute to the diffusivity improvement on MT molecules. The area distribution of the three bands appears to be steady when the water molar ratio is above 5. This result suggests that additional water would play a weaker role in further changing the interaction among water, N-O and Li+. This is consistent with the MD simulation results. The region of TFSI- stretching vibration was also investigated as shown in Figure 12. In pure LT, the peak at ~747 cm-1 is attributed to the S-N-S stretching vibration of TFSI-. The peaks in dry

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LT/MT mixtures have been studied in our previous publication9. At the molar ratio of LT:MT=1:1, the shape of TFSI- stretching is observed to be identical as crystaline LT. When water is added to the mixture, the peak shifts to lower wavenumbers and the shift becomes saturated when water ratio reaches to 5. This shift could be assigned to the effect of solvent-separated ion pairs (SSIPs) comparing with the initially ordered ionic structure (contact ion pair or CIP) in dry MT/LT9. The stabilization of this peak suggests solvation around TFSI- was saturated at water molar ratio of ~5. The result corresponds well with TFSI- solvation studied via the simulation (Figure 9b).

Figure 12. The region of TFSI- stretching vibration in Raman spectra. The samples are prepared at molar ratio of MT/LT/water=1:1:x, with the x indicated in the plots. The Raman spectra analysis from all three different regions correspond well with the simulation studies and elucidates the molecular structure variations at different water contents. The knowledge on the intermolecular interaction in the aqueous catholytes also provides more insights to interpret their physical properties and battery performance. 3.3 Ionic Conductivity and Ionicity. Both simulations and Raman spectra studies illustrate that there is a significant weakening of the interactions between Li+, TFSI- and MT when water is added. This causes the increase in dynamics of the species and, presumably, of the conductivity.

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The ionic conductivities of the catholytes were measured in experiments at 25 °C and the results are shown in Figure 13a.

Figure 13. (a) Calculated ideal ionic conductivity (σNE), actual ionic conductivity (σE) at 500 K, and experimental ionic conductivity (σExp.) at 298 K; (b) calculated ionicity (defined as σE/σNE) at 500 K. Based on simulation results at 500 K, using the Nernst-Einstein (NE) relation 𝜎𝜎𝑁𝑁𝑁𝑁 =

𝑁𝑁𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝 2 (𝑞𝑞 𝐷𝐷 + 𝑞𝑞−2 𝐷𝐷− ) 𝑉𝑉𝑘𝑘𝐵𝐵 𝑇𝑇 + +

the ideal ionic conductivity of each MT/LT/water mixture system was calculated. In the equation, Npair is the number of ion pairs, V the simulation box volume, kB the Boltzmann constant, and T the temperature, q+ and q- are the total charges of the ions (full charges were used), and D+ and D-

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are the self-diffusion coefficients of the cations and anions, respectively. The results are shown in Figure 13a. As shown in the figure, consistent with the experimental trend, the ideal ionic conductivity keeps increasing with the water concentration in the mixture. The increase is faster at low water concentrations, slower at high water concentrations, and reaches the maximum in the x=22 mixture. As more water is added to the mixture, the ion self-diffusivity increases so that the ideal ionic conductivity increases. At the same time, the ionic conductivity will go down as the concentration of the charge carrying species is reduced. There is a competition between these two effects, which leads to the appearance of the maximum in the ideal ionic conductivity in the x=22 mixture. The ionic conductivity may eventually decrease with higher water concentrations.16 It is thus required to optimize water content for real battery operation. The NE relation assumes no correlation between the ions, which can be a good assumption in diluted solutions. For systems studied in the current work, however, this assumption likely fails and the ideal ionic conductivity overestimates the actual ionic conductivity. Therefore, the actual ionic conductivity of each system was studied using the Einstein relation in which the correlation term ignored by the simple NE model is included. 𝑁𝑁

𝑁𝑁

1 𝑑𝑑 𝜎𝜎𝐸𝐸 = lim 〈� � 𝑞𝑞𝑖𝑖 𝑞𝑞𝑗𝑗 [𝑟𝑟𝑖𝑖 (𝑡𝑡) − 𝑟𝑟𝑖𝑖 (0)] ∙ �𝑟𝑟𝑗𝑗 (𝑡𝑡) − 𝑟𝑟𝑗𝑗 (0)�〉 6𝑘𝑘𝐵𝐵 𝑇𝑇𝑇𝑇 𝑡𝑡→∞ 𝑑𝑑𝑑𝑑 𝑖𝑖=1 𝑗𝑗=1

The results calculated using the Einstein relation are also included in Figure 13a. As shown in the figure, for a given mixture, the actual ionic conductivity is lower than that of the ideal ionic conductivity, consistent with the above discussion. Similar to the NE results, a maximum value was observed for the mixture with x=22. The correlation of the ions can be measured by ionicity, which is the ratio σE/σNE. The ionicity has value between 0 and 1. A larger value means more ions can move freely, thereby transferring charges more effectively and the liquid likely performs better as an electrolyte. The calculated

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ionicity of each system is shown in Figure 13b. It was found that the trend in ionicity follows that of actual ionic conductivity closely. With low water fraction, the ionicity was found to be around 0.1, indicating strong correlations between the ions in the mixtures. At the highest water fractions studied in the current work (x=22), the ionicity was found to be around 0.5. This result suggests that, even at this water fraction, there is significant correlations between the cations and anions, consistent with the slow dynamics of the systems. 3.4 Battery Performance. The catholytes with different water content were tested in a static cell design by employing lithium as the anode. All battery test was run at a constant current of 0.2 mA/cm2. All catholytes show complete charge-discharge behaviors, and the charge-discharge curves from the initial cycles are displayed in Figure 14a. The average discharge voltage and the gravimetric capacity of MT from their initial cycles are summarized in Figure 14b. The capacity was found to approach the theoretical value with higher amount of water, and a more pronounced rate is observed with the water ratio up to 5.3. The improvement in ionic conductivity plays a role in the enhancement of the utility efficiency that is defined as the ratio of achievable capacity by the theoretical value. The higher rate with water ratio of 5.3 could be explained by the solvation structure in the catholytes that per MT interacts with 5-6 water molecules. The interactions reduce strong interactions between MT and the ions, resulting in accelerated diffusivity of MT and thus the enhanced achievable capacity. The utility efficiency is above 90% when the water molar ratio is at 5.3. The improvement on MT diffusion and utility efficiency slows down with additional water due to the saturated interaction between MT with water (Figures 6 and 11).

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Figure 14. Battery performance of the catholytes prepared at MT/LT/water=1:1: x (molar ratio). a) The initial charge-discharge curves of varied catholytes with the water molar ratio (x) indicated in the plots. The dashed line indicates the theoretical value of gravimetric capacity based on the weight of MT (143.9 mAh/g). b) Average discharge voltage and capacity of different catholytes as a function of water molar ratio. c) Cycling performance of the catholytes with the x indicated in the plots.

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Higher discharge voltages are also observed with increased water ratio up to 10.7. The improved ionic conductivity should contribute to the enhancement. Besides, the increased mobility of MT also reduces the thickness of diffusion layer on the electrode towards the bulk of solution, and improve the kinetics of redox reactions of MT at the surface of the electrode. This fact should also contribute to the higher discharge voltage. While the water ratio goes higher, lower voltage was observed at water ratio of 21.4. That is because the improvement of ionic conductivity and MT mobility are less dramatic, and the effect of reduced concentration of the active material (MT) lowered the voltage. The discharge voltage reflects the combined effects from the catholyte properties such as the ionic conductivity, diffusivity and concentration of MT. The battery performances are well related to the water ratio and the interactions among MT,water, and ions. The molecular structure studies provide the reliable guidance to understand such relations. The charge-discharge cyclability of the catholytes are also investigated with results shown in Figure 14c. All tests are conducted at the same current density (0.2 mA/cm2) as the initial cycle. Similar trend of cycling stability for 20 cycles is observed for the catholytes at all different water ratios, indicating the amount of water has minimal influence on battery cycling stability. 4. Conclusion A type of highly-concentrated catholyte composed of 4-methoxy-2,2,6,6-tetramethylpiperidine 1-oxyl (MT), lithium bis(trifluoromethanesulfonyl) imide (LT) and water at varied water molar ratios were studied using both experimental techniques and classical molecular dynamics simulations. The experimental measured viscosity and calculated self-diffusion coefficients consistently show that the dynamics in the MT/LT/water catholytes is significantly improved with the addition of even a small amount of water. Detailed analysis on the solvation structures in the mixtures reveals that MT and LT are strongly coordinated in the dry mixture (without water). The

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favorite water coordination with both MT and LT breaks the strong interaction between MT and LT and therefore improve the dynamics significantly. Both simulation and experiments suggest that the coordination of MT and LT by water is saturated at water molar ratio between 4 to 6. The ionic conductivity was also studied. The results from experiments and simulation follow the same trend although the simulated ionic conductivity was underestimated by almost one order of magnitude. In both simulation and experiments, the ionic conductivity was found to increase significantly with increase of water molar ratio in the mixture when the water molar ratio is below 5-6. These results are consistent with the observed solvation structure in the mixtures. When additional water is added to the mixtures, the increase in the ionic conductivity slows down. It is worth mentioning that, even at the highest water concentration studied in the current work, the ionicity is still lower than 0.5, suggesting strong interaction among the ions in these catholyte mixtures. The performance of the catholytes was further tested in battery cells. It was found that the battery performance correlates well with the solvation structures in the mixtures. With the water ratio up to 5.3, the utility efficiency of the capacity is improved dramatically due to the much-accelerated diffusivity of MT. The improvement in discharge voltage was found to be the combined effects of the diffusivity and concentration of MT, besides the ionic conductivity. The study on the solvation structure provides more insights on understanding the properties of the catholytes and helps to interpret battery performance. Acknowledgements Computational resources were provided by the Center for Research Computing (CRC) at the University of Notre Dame. ASSOCIATED CONTENT

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Supporting Information. The following files are available free of charge. Integration of center of mass and site-site RDFs. Comparison of RDFs calculated at 300 K and 500 K. Calculated center of mass CNs at 300 K. Dynamic heterogeneity analysis of the catholyte system via van Hove function and non-Gaussian analysis. Number of molecules used in simulation boxes. Deconvolution of peaks in Raman spectra for the region of O-H stretching mode of water and nitroxyl vibration, respectively, and corresponding fitting statistics. (PDF)

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(16) Akash S.; Yong Z.; Thomas G.; Seungmin O.; Joan F. B.; Mark J. M.; Edward J. M. How Mixing

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AUTHOR INFORMATION Corresponding Authors Kensuke Takechi: [email protected]

TEL: +81-561-71-7751

Edward Maginn: [email protected]

TEL: +1- 574-631-5687

Present Addresses Ruidong Yang: Nafion™ Ion Exchange Materials, The Chemours Company, 200 Powder Mill Road, Wilmington, DE 19803 USA Kensuke Takechi: Materials Informatics Research-Domain, Toyota Central R&D Labs., Inc., 41-1 Yokomichi, Nagakute, Aichi 480-1192, Japan Author Contributions The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript. ‡These authors contributed equally.

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