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Na-Ion Solvation and High Transference Number in Superconcentrated Ionic Liquid Electrolytes: A Theoretical Approach Fangfang Chen, Patrick C. Howlett, and Maria Forsyth J. Phys. Chem. C, Just Accepted Manuscript • DOI: 10.1021/acs.jpcc.7b09322 • Publication Date (Web): 07 Dec 2017 Downloaded from http://pubs.acs.org on December 8, 2017

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The Journal of Physical Chemistry C is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

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The Journal of Physical Chemistry

Na-ion Solvation and High Transference Number in Superconcentrated Ionic Liquid Electrolytes: A Theoretical Approach Fangfang Chen,* Patrick Howlett and Maria Forsyth* Institute for Frontier Materials (IFM), Deakin University, Burwood campus, Melbourne; ARC Centre of Excellence for Electromaterials Science (ACES), 221 Burwood HWY, Burwood, Victoria, 3125.

ABSTRACT

Ionic liquids have been extensively studied for developing next-generation Li and Na ion batteries because they are potentially safer replacements for conventional organic solvents in liquid electrolytes. Some recent work has drawn our attention to high lithium and sodium salt concentration ionic liquid systems which demonstrate high alkali-metal-ion transference numbers and support cycling at high current densities. Here we present an in-depth theoretical study of ion dynamics in a concentrated room temperature ionic liquid, N-propyl-Nmethylpyrrolidinium bis(fluorosulfonyl)imide ([C3mpyr][FSI]) with a sodium salt (NaFSI), focusing on how the solvation structure of a Na ion changes with salt concentration, and how this

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affects its dynamics. These findings will help to understand the behaviour of superconcentrated ionic liquid materials that will guide experimentalists in optimizing ionic liquid based electrolyte materials.

1. INTRODUCTION Research on sodium-ion batteries has shown steady growth, driven by a communal goal to bring the Na-ion battery (NIB) to market as an alternative option to the widely used Li-ion battery (LIB). 1-5 The initial motivation originated from the fact that Na and Li ions both belong to the alkali metal family, and thus share many similar chemical properties. More attractive aspects of NIBs are the abundance of Na, ensuring a more sustainable supply, probably at a cheaper cost, for battery production. However, the majority of research publications on Na-ion batteries nowadays have focused on positive and negative electrode materials, with only a small proportion related to electrolyte materials.2-4,

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Commercially-used organic solvents are still

widespread as electrolytes, although they are well known to carry a safety risk due to their poor thermal stabilities. Developing safer electrolyte materials has become an essential task if we are to see widespread use of such energy storage devices. Room temperature ionic liquids (RTILs) are tailorable, ionically conductive materials, which have shown many advantages over normal organic solvents, including low volatility and better thermal and chemical stabilities.7 Therefore, they have attracted extensive interest as potential safer electrolyte materials for developing new Li- or Na-ion batteries.8-11 In a conventional electrolyte design, how to choose an optimal Li salt concentration in an ionic liquid is commonly determined with respect to the maximum ionic conductivity. It is known that mixing an ionic liquid with increased concentration of Li salts generally increases the viscosity of the liquid


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mixture due to extensive ionic association; this consequently decreases the ion mobility and also ionic conductivity. For that reason, high concentrated ILs were rarely considered in the past.12 Another reason for the focus on low concentration ionic liquid electrolytes is that the solubility of Li salt is low in many common RTILs,13 and this is due to many reasons of which the nature of the IL anion is the most important one.13-14 The solubility of a Na salt in ILs can be lower than its corresponding Li salt,15 which was recently explained by differences in chemical bonding between Li and Na salts.16 However, with the development of many new RTILs, higher salt concentrations were achievable and have been investigated. These superconcentrated IL systems, also termed as “ILin-salt”17 when mole fraction of salt is greater than half, have shown many unexpected excellent properties.18-23 For example, a 1:1 Li salt: IL concentration ratio in a LiFSI / C3mpyrFSI system produced stable cycling at high current density and a high Lithium ion transference number.18, 22 For a number of different sodium IL based electrolytes, promising results were also reported including an increase in sodium ion transference numbers at higher salt concentrations.19-21, 24 High lithium or sodium ion transference number is a key criterion for a battery electrolyte, however, the exploration on the underlying mechanism in superconcentrated ILs is still in an initial stage, and it is expected to be different from the transport mechanism in dilute systems. This surprisingly improved behavior of this concentration regime compared to the traditional IL electrolytes has aroused our interest in those superconcentrated IL systems. Previous works suggested that changes in the anion environment, i.e. the formation of bulk alkali-anion aggregate domains, could account for the changes in Na or Li ion transference numbers.19-20,

25

These aggregate structures seemed to promote a fast exchange of Na

coordination environments and thus led to fast Na motions. Recent battery studies also


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demonstrated that designing an IL system with a high fraction of salt to operate at intermediate temperatures might be a novel strategy for optimized battery design.21 Here, we have conducted further extensive modelling analysis of the microscopic organization of concentrated IL systems and the solvation/coordination structure of the sodium ions, to reveal the structure-dynamics relationships and possible underlying mechanism for high Na transport.

2. COMPUTATIONAL METHODS 2.1 Force field All studies were conducted based on classic all-atom molecular dynamics simulation with a non-polarizable atomistic model. The force field parameters for [C3mpyr][FSI] were taken from a widely accepted generic and systematic CL&P force field,26 which was specifically developed for ionic liquids. The Lennard-Jones potential parameters of the sodium ion are those used same in both the OPLSAA and Amber94 force fields. The details of force field parameters can be found in our previous work.25 The non-integer charges on ion molecules due to the charge transfer (or intermolecular polarization) have already been confirmed in ionic liquid systems either theoretically or experimentally,27-30 and these studies all demonstrate the necessity of employing scaled charges for non-polarizable force fields. Although there are shortcomings for the uniform scaling method, it is still prevalently adopted for classic MD simulation on ionic liquids using nonpolarizable force fields due to its simplicity, low-computational cost and predicting reasonable results on structure and dynamics properties. A scale factor of 0.67 has been used before for the neat [C3mpyr][FSI] system as the calculated densities fit well with experimental results.25 The same scale factor was also adopted here for the mixed NaFSI salt [C3mpyr][FSI]. We calculated


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densities for three systems with 10, 30 and 50 mol% NaFSI concentrations, respectively. The calculated densities, listed in table 1, show a good agreement with experimental results (Figure S1), 24 with only small deviations less than ± 1%.

Table 1. Calculated densities of [C3mpyr][FSI] with different NaFSI concentrations. Salt Concentration 10%

393K

348K

Error

298 K

Error

1.293

1.327(1.328a)

-0.075%

1.381(1.368a)

+0.95%

30%

1.374

1.418(1.419a)

-0.07%

1.473(1.462a)

+0.75%

50%

1.486

1.533(1.532a)

+0.065%

1.587(1.578a)

+0.57%

a

Experimental data from Matsumoto et. al. 24

The self-diffusion coefficients D of ionic liquid cations and anions, calculated previously at 25°C (298 K) for 10 and 30 mol% sodium salt mixed systems, were found to be always approximately a factor of two lower than NMR measured results, and this is actually also acceptable if compared to the deviations from the full charge model, which are generally much slower with orders of magnitude in size. 25, 31 In this work, the MSDs calculated for the 10 mol% system using a full charge model demonstrate significantly slower dynamics as shown in Figure S2. Therefore, we believe a scale factor of 0.67 is an acceptable value and necessarily to use for this work. Furthermore, recent research work by A. Yethiraj et al. has shown that using scaled charge atomistic models sometimes underestimate the cohesive energy in some ILs and thus lead to the wrong phase behavior of the mixtures.

32

In order to exclude the possibility of drawing

incorrect conclusions by charge scaling, we also conducted simulations on a few of systems using the full charge model, and results will be compared with the scaled charge calculations.


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2.2 Simulation details Simulated systems consist of an ionic liquid [C3mpyr][FSI] (Figure 1) mixed with NaFSI salts at three experimentally reported concentrations of 10, 30 and 50 mol% (50 mol% is the saturation concentration in experiment). To investigate the effect from an even larger proportion of the NaFSI salt, a 90 mol% system was also created as an artificial model system. Neat NaFSI salt was also calculated as a reference. To compare the results between real systems (10–50 mol%) and the reference system (90 mol%), the temperature was set to 393 K, the melting temperature of a pure NaFSI salt.33 The full charge simulations were carried out at 10 and 90 mol% salt concentrations at two temperatures of 393 K and 500 K, and the latter was necessarily used in order to achieve enough ion dynamics, which is absent at 393 K. 216 ions including NaFSI salt were randomly placed in a simulation box using Packmol.34 The system was first relaxed at a high temperature of 600 K by running 1 ns equilibration, using Berendsen thermostat and barostat in an NPT ensemble. Then it was cooled down to 393 K step by step. Equilibration calculation at each temperature was also carried out using an NPT ensemble, with an Nóse-Hoover thermostat and a Hoover barostat, with the relaxation constant of 0.5 and 6.0 ps, respectively. The pressure was set to 1 atm and the timestep is 1.0 fs. A subsequent NVE run produced an 8 ns trajectory for dynamics analysis using a time step of 2.0 fs. The cutoffs for van der Waals force and the real space of Ewald were 11 Å. The SHAKE algorithm was used for bond constrains with a shake tolerance of 1.0 × 10-6. The Velocity Verlet integration algorithm was adopted. The Ewald summation method with a precision of 1×10-6 was used to treat Coulomb interaction in a periodic system. All MD simulations were conducted using DL_Poly Classic software. 35


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Figure 1. Chemical structure of [C3mpyr][FSI] ionic liquid. 3. RESULTS AND DISCUSSION 3.1 Radial distribution function analysis The structural changes were investigated by calculating the radial distribution function (RDF), which describes how density of particle B varies as a function of distance from a particle A. The RDF of Na–NFSI in Figure 2(a) presents the arrangement of FSI– around sodium ions. Multiple peaks between 2 and 6 Å are attributed to three types of Na−FSI coordination geometries, which were illustrated next to the peak in the figure. The nearest small peak at 2.75 Å (R1) is assigned to the closest coordination (K1) between Na+ and the negatively charged N, usually also stabilized by another O atom in FSI–. This is a rare coordination condition, but has also been identified between Li+ and FSI– in Li salt mixed IL systems.36 In most cases, Na+ coordinates to multiple O atoms through either bidentate (K2) or monodentate (K3) geometry, corresponding to the bifurcate RDF (Na-NFSI) peaks at around 4.25 (R2) and 4.85 Å (R3) in Figure 2(a), respectively. The relative peak intensities obviously change with different salt concentrations; the peaks assigned to bidentate coordination decrease whereas those assigned to monodentate geometry increase at elevated salt concentrations. A similar increase in the proportion of monodentate coordination with increasing salt concentration has also been reported between


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either Li+ and FSI– or Li+ and TFSI– in polarizable force-field based MD simulations for a number of IL electrolytes, where Li+ mole fractions are less than 0.38.37-39

Figure 2. RDF of (a) Na–NFSI and (b) NFSI–NFSI. Coordination number profiles of Na-FSI were plotted only at three salt concentrations. Three Na-FSI coordination geometries were also presented next to their characteristic peaks.

The coordination number (CN) was calculated through integrating the RDFs and results are given in Table S1. CN of Na-NFSI, representing the number of anion in the Na ion’s first coordination shell, was read at three valleys of R1, R2 and R3 for 10, 30 and 50 mol% systems. Since the cutoff distance at R2 can only be decided from the 50 mol% system, it was also used


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for other systems. The CN at R1 indicates the K1 coordination increasing slightly from 0.3 to 0.7 when salt concentration increases from 10 to 90 mol%; the CN at R2 remains almost unchanged around 2.5 to 2.6, but the number of K2 (bidentate) coordination actually decreases from 2.2 to 1.9 when CN of K1 was excluded; CN at R3 increases the most from 4.3 to 6.1, and the number for K3 coordination (monodentate) also increases significantly from 1.8 to 3.5. The coordination numbers for Na-O were calculated at their first RDF valleys (Figure S3), showing a negligible change from 6.3 to 6.4. All these results suggest a change in sodium ion’s first coordination structure at increased salt concentrations, i.e. the increased CN of anion with the bidentate coordination geometry. As each Na+ requires at least 4 FSI– to coordinate, a given FSI– has to coordinate to multiple Na ions when the ratio of FSI– and Na+ is significantly less than 4:1, i.e. the concentration of sodium salt is larger than 25 mol%. Therefore, in order to provide multiple coordinating sites, the number of the monodentate coordination will certainly increase. The RDFs from a full charge simulation were also calculated and the comparison between two models was presented in Figure 3. The main difference in RDFs from the full charge simulation was on the shape and position of these peaks, which become sharper and slightly left-shifted (Figure 3 (a)-(d)). Such a change is not surprising since electrostatic interaction between ions becomes stronger without charge scaling, which slows ion motion significantly as indicated by the mean square displacement presented in Figure S2. The slow movement of ions results in the sharper RDF peaks and a more distinct change in the Na-N RDF spectra (Figure 3(e)) across different salt concentrations. Increasing the temperature to 500 K stimulates the ion dynamics, and the change in Na-N RDFs (Figure 3(f)) becomes much similar to the change in Figure 2 (a). The CN predicted from the full charge model is lower than the results from the scaled charge simulation, but still presents the similar change of +0.7, –1 and +1.7 for K1, K2 and K3


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coordination, respectively, in comparison to the CN changes of +0.4, -0.3 and +1.7 from the scaled charge model. A decrease of 0.4 in CN of Na-O was found for the full charge model, which however increases by 0.1 in the scaled charge model. Nevertheless, The results from the full charge model support the conclusion drawn from the scaled charge model, i.e. increased CN and monodentate coordination geometries when salt concentration increases.

(a) Na-N 10%

(b) Na-N 90%

(c) Na-O 10%

(d) Na-O 90%

(e) Na-N 393 K

(e) Na-N 500 K


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Figure 3. Comparisons of RDFs between full charge (1.0) and scaled charge (0.67) systems for Na-NFSI (a-b) and Na-O (c-d) at 393 K; and between Na-NFSI in 10 mol% system and 90 mol% system at 393 K (e) and 500 K (f) for full charge model.

RDF of NFSI–NFSI in Figure 2(b) demonstrates significant structural rearrangements between anions in these IL–inorganic salt mixtures. Evidently, it shows a structure transition from a neat ionic liquid to a neat molten NaFSI salt, due to the formation of bulk Na-FSI regions (also known as “ion aggregates” or “ion clusters”) as salt concentration increases. These aggregates have distinct short-range order, characterized by the gradual growth of two RDF shoulders around 4 Å and 5.5 Å. The other RDF peaks are also affected by such an IL to salt structural transition. Interestingly, by 30 mol% NaFSI, the FSI-FSI peak at around 10 Å disappears and approaches the molten salt environment. Three snapshots from 10, 50 (presented previously), 19 and 90 mol% systems in Figure 4 give a more intuitive understanding about structural transformation within these mixtures. The 10 mol% salt system is dominated by ionic liquid and the Na ions are only sparsely distributed; ion aggregates (separated by IL cations) become clearly visible and occupy a certain volume when the Na salt concentration is 50 mol%, and they are further interconnected in the 90 mol% system so that the whole system appears as a molten NaFSI salt, with IL cations dispersed throughout. Previous Raman spectroscopic analysis21 also perceptibly shows the variation of anion environment for the alkali ions relative to their concentration, and this change was believed to affect their transport. A gradual increase in ion aggregates with increasing salt concentration, coupled with a concomitant increase in viscosity, was considered to be the main reason for reduced ionic conductivity in many ionic-liquid based or polymer based electrolytes. Indeed, for


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the concentrations usually of interest in electrolytes, this hypothesis has been confirmed both experimentally and theoretically.40-42 However, when the salt concentration exceeds this ‘normal’ range (typically 0.5 to 1.0 mol kg-1) both the structural and dynamic picture may be different. This is what we want to investigate further here.

Nax C3mpyr(1-x)FSI 100% Salt

100% ILs

Salt in ionic liquid

Ionic liquid in salt

Na% 90%

50%

C3mpyr+

Na+

10%

FSI−

Figure 4. A diagram showing structural changes as NaFSI salt concentration increases. 3.2 Ion transport The transport of ions in an MD simulation is usually measured by the mean square displacement (MSD), and the larger MSD value in a given time is related to the faster diffusion dynamics. The self-diffusion coefficient, D, of an ion species can be calculated from the MSD using the Einstein relation, and this parameter is also measurable by experiment. The MSD was calculated for both IL cation and anion (via N atom) and the Na+ in Figure 5. When the salt concentration increases from 10 to 90 mol%, the MSD of either IL cation or anion (Figure 5a)


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was reduced at elevated salt concentrations, which is related to slower IL dynamics, as normally observed; whereas in the case of the Na+ the dynamics show a turning point (Figure 5b): the sodium ion motion slows down at first from 10 to 30 mol% and remains slow until the concentration is above 50 mol%, then accelerates relative to the other ions in the system. Those changes in MSD also remain same in the long trajectory calculation of 20 ns (Figure S4).

Figure 5. Mean square displacements of (a) N from both IL cation and anion and (b) the Na+ at a temperature of 393 K with a number of salt concentrations. In a given time period, the larger MSD will lead to a larger self-diffusion coefficient D. Apparent sodium ion transference number T, i.e. the contribution to conductivity due to Na+ transport, can be approximated from D through an equation:43-44 TNa =

nNa DNa nNa DNa + ncation Dcation + nanion Danion

(1)

where n is the number of moles. Here, there are two factors that govern TNa. If DNa is close to Dcation and Danion, we will obtain an increased TNa at higher salt concentrations due to an increase in nNa. Since DNa actually remains unchanged or slightly increases from 30 to 90 mol %, whereas both Dcation and Danion drop, this number will actually be even greater than what would be


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expected from concentration alone. TNa estimated previously at 298 K shows an increase from 0.05 to 0.30 when salt concentration increases from 10 mol% to 50 mol%, consistent with experimental results.25 Next we present how the proportion of fast ions varies with salt concentration. We calculated the MSD of a single ion using the same method as to calculate the MSD of one type of ions, except the final step of averaging over all same ion species. The square displacements of all ions at the end of 8 ns (R2 (8ns)) were recorded and presented in Figure 6. It is clearly seen from the figure that the number of Na ions in the highlighted area above 800 Å2 increases whereas the other two types of ions drops as the salt concentration increases. Hence, we visually selected 800 and 150 Å2 as reference values to partition ‘fast’ (> 800 Å2) and ‘slow’ ions (< 150 Å2). Furthermore, we also calculated ratio of fast ions between different species using both 800 and 600 Å2 as reference values to partition fast ions. These results are given in Table 2. Obviously, the displacements of ions presented here demonstrate the dynamically heterogeneous in these complex IL/salt systems even after MSD in Figure 5 reaching a linear regime. Such a seemingly Fickian but heterogeneous dynamics in ionic liquids is not unusual,45 and has been also reported in a wide range of different systems.46-49 It is normally found that clusters of molecules with different mobility, including super-diffusive and sub-diffusive dynamics, coexist and contribute to an overall linear MSD. In this case, ion motion is only statistically random based on MSD, but not really random. Contribution to the ionic conductivity mainly comes from fast ions. Therefore, at first, we calculated the percentage of fast ions at different salt concentrations. It is noticed that both the lowest (10 mol%) and the highest concentration (90 mol %) systems have a relatively larger fraction of fast sodium ion (~9 and 10%) than the other two intermediate concentration systems (~6 and 7%). Overall, this fraction of fast sodium ion does not change


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dramatically compared to that of a fast IL ion species, which dropped from 12.4% to 0 for C3mpyr+ and from 20.4% to 1.4% for FSI–. This indicates that the increased NaFSI salt restricts fast IL ions whereas it facilitates fast Na ions. By 90 mol% NaFSI, it also appears that the dominant mobile (i.e. ‘fast’) species is Na+, indicating a decoupling of Na+ dynamics from the bulk electrolyte as shown recently in superconcentrated Li IL electrolytes.50 The ratio between different types of fast ions was also calculated. Among all fast ions, the fraction of the Na ion increases remarkably especially when salt concentration is above 50 mol%, this also supports the increase in Na ion transport numbers. It is noticed from Table 2 that the ratio changes is independent of how to partition fast ions. Single ion MSD calculations from the full charge model (Figure S6 and Table S2) also support the results obtained here. How could lithium become faster while IL ions slow down in a super-concentrated IL? We will discuss below that the anion environment plays a key role here.

(a)

Cation Na Anion

2000

Cation Na Anion

2000

1600

(b)

1600

R2(8 ns) / Å2

R2(8 ns) / Å2

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


1200

800

400

1200

800

400

0

0

0

100

200

300

400

0

100

Ion index

200

300

400

Ion index


15


(c)

Cation Na Anion

2000

(d)

Cation Na Anion

2000

1600

1600

R2(8 ns) / Å2

R2(8 ns) / Å2

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

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1200

800

400

1200

800

400

0

0 0

100

200

300

400

0

100

Ion index

200

300

400

Ion index

Figure 6. The square displacements of both IL cation, anion and Na ion at the end of an 8 ns production run for four different salt concentrations of (a) 10 mol%, (b) 30mol%, (c) 50 mol% and (d) 90 mol%.

Table 2. Percentages of ‘fast’ ions of each type and ratios of fast ions. Different MSD values of 800 and 600 Å2 was used to partitioning fast ions.

Percentage of fast ions (> 800Å2) of each type Type of ion 10 mol%

30 mol%

50 mol%

90 mol%

Na+

9.1%

6.3%

7.4%

10.3%

FSI–

20.4%

12.5%

4.6%

1.4%

C3mpyr+

12.4%

8.6%

3.7%

0

Ratio of fast ions (Na: Anion: Cation) Fast ion partition 10 mol%

30 mol%

50 mol%

90 mol%

> 800 Å

1: 22: 12

1: 6.75: 3.25

1: 1.25: 0.5

1: 0.15: 0

> 600 Å

1: 18.25: 13.5

1: 2.9: 2.8

1: 1.5: 0.3

1: 0.37: 0


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A change in anion environment has been claimed to be associated with an increase lithium ion transference number in many different concentrated electrolyte systems, including not only ionic liquid based systems11-12 but also concentrated poly (ethylene carbonate)-based polymer electrolytes.51 NMR, FT-IR and density functional theory studies all suggested a weaker (or looser) alkali ion coordination structure could be the primary cause for reasonable conductivity and high alkali ion transference number. Our simulation results here actually provide further direct evidence to support the crucial role the coordination structure plays on enhancing alkali ion (in this case Na+) dynamics in high concentrated ILs. The average number of FSI (NFSI/CN) in first coordination shell of a sodium ion increases from 4 to 6, as shown in Figure 2, suggesting the Na-FSI nearest neighbor coordination structure becomes looser at higher salt concentrations. Since restructuring of the Na coordination shell is continuous, CN also varies with time accordingly. The coordination state of a ‘fast’ or ‘slow’ Na ion in each time frame of a total 4000 time frames (8 ns MD trajectory) was monitored. The percentage of each coordination size in a total of 4000 coordination states was calculated and then averaged over all selected fast or slow sodium ions, and plotted in Figure 7. We use a log– scale for the Y–axis to better present the diversity of CN since, at the extreme ends, the percentage of these coordination states that exist at any moment in time is very small. Figure 7 clearly shows that the coordination states (NFSI) are significantly affected by salt concentration, but not by the defined ‘fast’ or ‘slow’ state. NFSI could span between 2 and 10, but the dominant number for each concentration is consistent with CN calculated from RDF in Figure 1. For example, the dominant Na-FSI coordination state has 4 FSI– in both 10 mol% and 30 mol% systems, and 5 and 6 FSI– in 50 mol% and 90 mol% system, respectively. These higher


17


NFSI gradually increase in number at elevated salt concentrations. The largest NFSI that could be observed in a given system also increases from 7 (10 mol%) to 10 (90 mol%). We stress that, although these large ion pairs (CN > 6) are hardly likely to be the gas phase energy minimum states determined from DFT calculations, they could still be metastable, transition states in the liquid phase or indeed temporarily stabilized in ion aggregates during the course of the MD simulation. The formation of these large Na(FSI)x complexes is extremely important for Na+ dynamics in a viscous salt-IL mixture. DFT calculations on Na-anion coordination structures showed that the weaker binding energy is associated with the larger CN,40, 52 suggesting the cage of the Na+ in this work would become looser in the high salt concentration systems so as to promote the process of reorganising Na+ and FSI– into different solvation complexes, which is also directly related to the Na+ hopping.

10% slow 10% fast 30% fast 30% slow 50% slow 50% fast 90% slow 90% fast

100

10

Percentage(%)

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

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1

0.1

0.01

2

3

4

5

6

7

8

9

10

11

NFSI (coordination size)

Figure 7. The averaged percentage of different coordination size (CN) over 8 ns for selected ‘fast’ or ‘slow’ Na+ at different salt concentrations. Therefore, we have quantitatively recorded the number (frequency) of two types of the change in Na+ coordination, including (1) the change in CN (losing or gaining FSI–); and (2) the


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occurrence of anion exchange (illustrated in Figure 8), in an 8 ns trajectory and on selected ‘fast’ and ‘slow’ sodium ions. The change in CN of a given Na+ was checked between any two adjacent time points, i.e. between t and t+∆t. Anion exchange was counted when one or more FSI– left at moment t, and on the other hand, one or more new FSI– joined in at moment t+∆t or t+2∆t. Here a longer time interval of 2∆t was also considered for anion exchange because a certain fraction of anion exchange actually occurs via an instantaneous transition structure at time t+∆t, i.e. losing an FSI– happens at moment t while gaining a new FSI– into the coordination sphere at t+2∆t. Occasionally, the transition structure lasted for a longer period of time (i.e. waiting for a new FSI– to join the coordination environment) but this situation was found to be rare and therefore ignored in the analysis here. These changes were calculated on selected fast (red stars) and slow Na+ (black stars) at each salt concentration, the frequency of change was also calculated over all selected Na+ in each system (triangles).

2400

2000

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CN change_slow Na ions CN change_fast Na ions AN exchange_slow Na ions AN exchange_fast Na ions Average CN change Average AN exchange

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Figure 8. Frequency in CN (solid stars) change or anion exchange (hollow stars) for selected fast and slow Na+ and their average values (green triangles) in four systems with 10, 30, 50 and 90 mol% salt concentrations.


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Overall, both CN change and anion exchange happen more frequently when salt concentration increases and this is independent of whether it is a fast or slow Na+. The averaged frequency of all selected ions, demonstrated by triangle symbols, increases as salt concentration increases for both CN change (solid triangles) and anion exchange (hollow trigangles). Hence we confirmed that both the CN size and the anion change occur at the same time in the coordination shell of the Na ions, which supports the conjecture that a larger CN leads to a looser binding structure and thus promotes the Na+ hopping. Interestingly, the ‘slow’ ions appear to have a similar number of anion exchanges or CN change as the ‘fast’ ones have, whereas we may have expected this to be less frequent. Through calculating the displacement of a given Na+ ion from its initial position as a function of time. Whether or not a CN change or anion exchange occurs at the same time (Figure S5) was also compared. We found that these coordination changes could lead to two types of Na+ displacement, either a small oscillation (more frequently) or a large jump (occasionally). A further analysis of the trajectory file showed that small displacements were related to the localized movements, whereas a large displacement in a short time is usually due to a big jump of a Na+ out of a trapped area. Here we produced two trajectories for both a ‘fast’ and a ‘slow’ Na+ over an 8 ns time in Figure 9. Different colors of red, white and blue were used to present a trajectory in time: the beginning of the trajectory is in red, the middle is in white, and the end is in blue. In a short period of time, a Na+ ion can move back and forth within a certain relatively confined area, as shown from the circled area in the trajectory in Figure 9, it can also hop from one trapped area to another in a long distance. The trajectory of a ‘slow’ Na+ is more confined, whereas it is diffusive for a ‘fast’ Na+ due to more long-distance hops. This again confirms the heterogeneous ion dynamics in these systems. Whether a Na+ could move farther or not can be a random event


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that due to many complex reasons, such as surrounding environment and/or neighbouring ion dynamics, and it could change with time. What we can confirm here is that the high salt concentration overall increases the incidence of exchange in Na+ coordination, thus increases the occurrence of the Na ion-hopping event.

Figure 9. Trajectories of a ‘fast’ (blue) and a ‘slow’ (green) Na ion in a 50 mol% salt system for 8 ns. Periodic boundary conditions are not used when generating trajectories. 4. CONCLUSIONS In this work we present a detailed analysis of changes in material microstructures, Na ion coordination environment and ion dynamics in an ionic liquid system with increased Na salt concentrations. The relationship between dynamics and structure of the sodium ions in a series of electrolyte concentrations that can be considered to span the true ionic liquid regime where the sodium ions are a solute in an IL solvent, through to the molten salt systems where we approach essentially an inorganic melt. RDF analysis shows the significant ion rearrangement in the IL structure upon adding more salts, appearing as the formation of large Na-anion aggregate domains, which gradually become interconnected when the fraction of salt is more than that of the IL. The nearest coordination environment of the Na ions is also affected, with an increase in


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the coordination number, and monodentate coordination geometry, of the FSI anion. Such changes lower the binding energy of the solvation complex and thus promote the Na dynamics. The Na dynamics shows a shift from an initial drop to an increase in diffusion. In contrast, the movement of both IL cation and anion is largely slowed down at higher salt concentration. This explains the rise in Na transport number that has been measured experimentally in the high alkali salt concentration IL electrolytes. The MSD is also calculated on single ions with the ‘fast’ and ‘slow’ ions being identified in an 8 ns-time period. The fraction of fast ions responds differently to the Na salt concentration, showing as an increase in the fraction of fast Na ions in going from 30 to 90 mol% NaFSI. This is accompanied by a significant drop of the fast IL cations and anions. Moreover, examination of the changes in sodium ion first coordination shell elucidate that the solvation of the sodium ion changes more frequently in the high concentration system through changes in the number of FSI anions or anion exchange, which would facilitate the Na ion hopping event that leads to the increased fraction of fast Na ions. All analyses in this work are conducted based on molecular dynamics simulations using a nonpolarizable CL&P force field with a uniform charge scaling method. A comparison of structure and dynamics between a full charge model and scaled charge model is also discussed briefly. The results from the full charge simulations qualitatively support the conclusions drawn from the scaled charge model. But it does show some differences on predicted structures and ion dynamics. Therefore, it is suggested from this work that the cheap scaling charge technique needs to be used with care, depending on the main research questions being investigated. More advanced MD simulations are required for ion structures, e.g. solvation structure, and dynamics with a high precision.


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ASSOCIATED CONTENT Supporting Information Supporting information is s available free of charge on the ACS Publications website at DOI:

AUTHOR INFORMATION Corresponding Author *E-mail: [email protected]; [email protected] ACKNOWLEDGMENTS The authors would like to acknowledge the Australian Research Council (ARC) for financial support under FL110100013 and DP16. This research was undertaken with the assistance of resources provided at the NCI National Facility systems at the Australian National University through the National Computational Merit Allocation Scheme supported by the Australian Government.

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TOC Graphic

Na ion coordination size becomes larger and ‘looser’ in superconcentrated ionic liquids, which promotes the coordination change and the sodium ion dynamics.


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Na-Ion Solvation and High Transference Number ... - ACS Publications

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