Open Access Article
Benjoe Rey B.
Visayas
a,
Shyam K.
Pahari
a,
Tugba Ceren
Gokoglan
b,
James A.
Golen
a,
Ertan
Agar
b,
Patrick J.
Cappillino
*a and
Maricris L.
Mayes
*a
aDepartment of Chemistry and Biochemistry, University of Massachusetts Dartmouth, MA 02747-2300, USA. E-mail: maricris.mayes@umassd.edu; pcappillino@umassd.edu
bDepartment of Mechanical Engineering, Energy Engineering Graduate Program, University of Massachusetts Lowell, Lowell, MA 01854, USA
First published on 26th November 2021
Recent advances in clean, sustainable energy sources such as wind and solar have enabled significant cost improvements, yet their inherent intermittency remains a considerable challenge for year-round reliability demanding the need for grid-scale energy storage. Nonaqueous redox flow batteries (NRFBs) have the potential to address this need, with attractive attributes such as flexibility to accommodate long- and short-duration storage, separately scalable energy and power ratings, and improved safety profile over integrated systems such as lithium-ion batteries. Currently, the low-solubility of NRFB electrolytes fundamentally limits their energy density. However, synthetically exploring the large chemical and parameter space of NRFB active materials is not only costly but also intractable. Here, we report a computational framework, coupled with experimental validation, designed to predict the solubility trends of electrolytes, incorporating both the lattice and solvation free energies. We reveal that lattice free energy, which has previously been neglected, has a significant role in tuning electrolyte solubility, and that solvation free energies alone is insufficient. The desymmetrization of the alkylammonium cation leading to short-chain, asymmetric cations demonstrated a modest increase in solubility, which can be further explored for NRFB electrolyte development and optimization. The resulting synergistic computational–experimental approach provides a cost-effective strategy in the development of high-solubility active materials for high energy density NRFB systems.
Despite having great potential for grid-scale application, NRFB technology is still in its infancy with technical hurdles that must be overcome, including low solubility of active-materials, which limits energy density, and poor stability, leading to low cyclability.13–16 To date, most research has focused on improving the performance of individual components such as high-energy-capacity electrolytes.17 Moreover, electrolyte viscosity, which is correlated with conductivity and diffusivity, is another important issue in the development of NRFB systems and is gaining attention in the community.18–20 Electrolyte systems with low viscosity, high diffusivity, and high ionic conductivity are ideal.12,21 The demand for higher energy density systems, pushing towards higher active material concentration, has resulted in higher viscosity in NRFB electrolytes which hinders practical applications due to pumping losses and decreased conductivity.19
We recently elaborated on an NRFB active-material, leveraging a bio-inspired redox molecule5,22,23 known as Amavadin (Fig. 1a), biosynthesis of which has evolved naturally in mushrooms of the Amanita genus under selection pressure for strong and specific vanadium binding. As a result, this compound and its analogs exhibit the highest stability constants ever measured for a V4+ ion.24 Using inexpensive reagents, vanadium (4+) bis-hydroxyiminodiacetic acid ([VBH]2−) (Fig. 1b) has been synthesized at a large scale which exhibits high chemical stability, even under cycling at high current and to deep states-of-charge.23 More recently, we demonstrated a synthetic strategy to increase the solubility of VBH-based NRFB materials while still maintaining stability during deep cycling for extended time periods.5 This highlights the potential of VBH-based NRFB materials as a molecular scaffold for the development of next-generation flow battery electrolytes.
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| Fig. 1 Amavadin (a), a naturally occurring vanadium chelate, isolated from mushrooms in the Amanita genus and (b) the related, proteo-analog, [VBH]2−. | ||
The solubility of active-materials is a critical factor in determining the energy density of NRFBs.2,25 However, synthetically exploring a large parameter space to identify soluble species empirically is an inefficient approach. Solubility can be calculated by comparing the stabilization of the gas-phase ions upon solvation
with that of the organization of the ions into a crystal lattice
(see Fig. 2). In the well-known thermochemical Born–Fajans–Haber cycle (Fig. 2),26 the latter factor can be expressed in terms of free energy of sublimation
which describes the energetics of a material's phase change from solid to gas, and is approximately the negative of
(see ESI,† eqn (2)). This thermochemical cycle has been utilized in previous solubility studies in pharmaceutics,27–29 druglike molecules,30,31 and systems like LiO2 and Li2O2.32 These works involved neutral molecules and disregarded some thermochemical corrections. With full thermochemical corrections, a similar approach was used by Chen and Bryantsev to predict the melting points of ionic liquids.33
Despite the straightforward description of solubility, accurate calculations of
have proven challenging and computationally expensive.33 As such, recent computational approaches to determine RFB active-material solubility have focused only on
5,25 In our previous work,5 we demonstrated that solvation energies are insufficient to describe the experimental solubility trend for VBH with long-chain alkylammonium counter cations. This implies a critical role for
in determining the solubility of active materials in NRFB electrolytes and highlights the importance of its accurate calculation in any quantitively useful prediction of solubility.
In this paper, we report a computational framework designed to predict the solubility trends of electrolytes, tracking both the thermodynamic contributions due to free energy of active-material/solvent interactions and free-energy of the active-material crystal lattice. These calculations make use of extensive information on the solid-state geometries of VBH with various cations, provided by eight crystal structures, for input geometries. These structures, correspond to the reduced and oxidized forms of [VBH] with symmetrical alkylammonium cations, having one to four carbon atoms in each chain. Two of these are newly reported, herein (see Fig. 3b, c and Table S6†), and five of these have been reported previously.5,22,23 One of the eight structures, corresponding to [N3333]2[VBH], was of high enough quality to obtain structural information (unit cell, Cartesian coordinates, and bonding parameters for starting geometries) but not of publication quality. The solubility predictions were validated by preparing and characterizing several [VBH] compounds with symmetric and asymmetric counter-cations in +4 (e.g., Fig. 3d) and +5 (e.g., Fig. 3b) redox states and measuring their solubility in various solvents. This work provides valuable insights into tuning electrolyte solubility. We present a synergistic computational–experimental design approach focusing on short-chain, asymmetric alkylammonium cations that would potentially yield highly soluble VBH active material. Lastly, we briefly describe the viscosities of the electrolyte solutions as well as the role of solvent.
We employed desymmetrization by substitutions on the smallest ([N1111]+) and largest ([N4444]+) cations that were used in experiment (Fig. 3a). At most two substitutions were performed in each set, generating groups of monosubstitutions, symmetric disubstitutions, and asymmetric disubstitutions. To probe the steric effect of alkyl chain length, we used ethyl (2), n-propyl (3), and n-butyl (4) for [N1111]+. For the larger cation, [N4444]+, the steric effects were also probed using a methyl (1) substituent and the relatively bulkier sec-butyl (s) and tert-butyl substituents (t). To investigate electrostatic effects, we modified the [N4444]+ with trifluoromethyl (c) substituent. Fig. 3e–h shows representative structures of the symmetric and desymmetrized [N4444]+.
To benchmark our calculations, we compared the calculated molar volumes of the simplified crystals to the molar volumes of the experimentally crystallized active materials for [Nxxxx]y[VBH] (where x = 1, 2, 3, 4 and y = 1, 2). Table S1† shows the experimental molar volumes, Vm (exp), and Vm (calc) of the simplified crystal structures. Despite the volume that the trapped solvent molecules occupy, the simplified models captured the local arrangement of the ions in the bulk crystal. This is especially true for the [N2222][VBH] and [N3333][VBH] crystals, which had no solvent impurities in the crystal lattice, where the calculated molar volumes differed only by 2.17% and 0.53%, respectively, from the actual molar volumes. The simplified V4+ crystals also performed well in replicating the actual molar volumes with the closest prediction obtained from [N4444]2[VBH] at 0.41% difference. This suggests that the crystal simplification approximation does capture local regions of the actual crystal structures with considerable accuracy.
We note that bulk morphological variation is neglected in this approach resulting in systematically high lattice energies, especially for crystals with large Z. Nevertheless, the simplified approach employed here, which is empirically calibrated by solubility measurements, provides a middle ground for both computational cost and accuracy. It is an excellent tool for exhaustive screening and exploration of materials to a depth that would not be possible by synthetic approaches. Table S7† lists the formula unit Cartesian coordinates for each of the simplified crystals in both +4 and +5 redox states.
and free energies of sublimation 
As the magnitude of
increases, sublimation becomes less favorable leading to a more stable crystal. Eqn (1) implies that the greater the magnitude of
the lower the solubility. Since
is approximately the negative of the
(ESI eqn (2)†), a material would become more soluble as the
becomes less negative.
Fig. 4a and b illustrate the performance of the models in predicting the trends of
(data shown in Table S3†). The first four points, corresponding to the four symmetric [Nxxxx]y[VBH], show that as the cation size increases,
becomes less negative. This result correlates with experimental solubilities (Table 1), where increasing the size of the cation destabilizes the crystal lattice and increases solubility. This experimental trend was not captured by
(described in Section 2.5) demonstrating that the solubility of the VBH crystals is dictated more by the changes in the
than changes in the 
Within the +4 and +5 group, [N1111]2[VBH] and [N1111][VBH] crystals have the most negative
with about 99–196 kJ mol−1 and 15–45 kJ mol−1 lower than the other symmetric compounds, respectively (Table S3†). This difference between the scale of the relative
as a response to the change of cation can be attributed mainly to the electrostatic potential of the V4+ and V5+ states. Increasing cation size destabilizes the coulombic interactions in the lattice by increasing ion separation and interactions with neighboring ions, which has a greater effect in [VBH]2−.
In general, both the alkyl chain length and bulkiness promoted lattice destabilization. However, because of the greater electrostatic potential of the dianionic [VBH]2−, the cation modifications on the V4+ group resulted in lower
than [N4444]2[VBH]. The closest were the monosubstituted [N444c]2[VBH] and the asymmetric disubstituted [N441t]2[VBH], which are only 2.9 and 15.0 kJ mol−1 more stable than [N4444]2[VBH], respectively (Table S3†). This can be attributed to the charge screening by the bulky tert-butyl and the electronegative trifluoromethyl groups. On the other hand, in the lower electrostatic potential of the [VBH]− anion, there are more pronounced effects of charge screening and ion separation and several of the desymmetrized cations resulted in V5+ crystals with higher
than [N4444][VBH] (Table S3†) such as the monosubstituted [N444t]+, the symmetric disubstituted [N44ss]+, and the asymmetric disubstituted [N44st]+ and [N44ct]+.

on the solubility prediction and compare with the magnitude of
we calculated the
of the symmetric and asymmetric VBH active materials in several solvents (Fig. 5 and Table 2, full list of solvents in Table S2,† and heat maps of V4+ and V5+ compounds in Tables S4 and S5†). Of the three solvents (THF, MeCN, and DMSO) that were used in the experimental solubilities, our calculations predicted that the solvent with the most favorable
for V4+ compounds is MeCN, while for V5+ compounds, it is DMSO. These are consistent with the general experimental solubility trends (i.e., the solubilities for V4+ are highest in MeCN, while V5+ solubilities are highest in DMSO, Table 1). However,
alone could not explain the solubility trends with respect to the size of the alkylammonium chain. For example, for the four symmetric V4+ compounds in MeCN with increasing chain length ([N1111]2[VBH] to [N4444]2[VBH]),
were determined to be −1107, −1060, −1045, −1050 kJ mol−1 (Table 2), contrary to experimental solubilities of 0.004, 0.330, 1.090, and 0.800 (Table 1), respectively.
in kJ mol−1, of the [Nxxxx]y[VBH] active materials, in the +4 (where y = 2) and +5 (where y = 1) states, in tetrahydrofuran (THF), acetonitrile (MeCN), and dimethylsulfoxide (DMSO) SMD solvents
| Vanadium (+4) species | Vanadium (+5) species | |||||
|---|---|---|---|---|---|---|
| THF | MeCN | DMSO | THF | MeCN | DMSO | |
| Symmetric | ||||||
| 1111 | −984.5 | −1107.1 | −1099.3 | −414.9 | −457.9 | −461.1 |
| 2222 | −943.3 | −1060.0 | −1046.6 | −394.3 | −434.4 | −434.7 |
| 3333 | −931.3 | −1044.8 | −1025.1 | −388.3 | −426.8 | −424.0 |
| 4444 | −938.0 | −1050.0 | −1024.5 | −391.7 | −429.4 | −423.7 |
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| Monosubstituted | ||||||
| 1112 | −973.3 | −1094.3 | −1085.1 | −409.3 | −451.5 | −454.0 |
| 1113 | −969.2 | −1089.5 | −1078.7 | −407.2 | −449.1 | −450.8 |
| 1114 | −969.4 | −1089.2 | −1077.0 | −407.3 | −449.0 | −449.9 |
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||||||
| Symmetric disubstituted | ||||||
| 1122 | −963.0 | −1082.6 | −1071.9 | −404.2 | −445.7 | −447.4 |
| 1133 | −956.1 | −1074.2 | −1060.4 | −400.7 | −441.5 | −441.6 |
| 1144 | −957.1 | −1074.3 | −1057.6 | −401.2 | −441.5 | −440.2 |
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||||||
| Asymmetric disubstituted | ||||||
| 1123 | −959.5 | −1078.3 | −1066.1 | −402.4 | −443.5 | −444.5 |
| 1124 | −959.8 | −1078.2 | −1064.5 | −402.6 | −443.5 | −443.7 |
| 1134 | −956.6 | −1074.2 | −1059.0 | −400.9 | −441.5 | −440.9 |
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||||||
| Monosubstituted | ||||||
| 444c | −931.1 | −1045.2 | −1023.7 | −388.2 | −427.0 | −423.3 |
| 4441 | −946.1 | −1060.6 | −1039.5 | −395.7 | −434.7 | −431.2 |
| 444s | −929.6 | −1041.4 | −1016.2 | −387.5 | −425.0 | −419.6 |
| 444t | −926.8 | −1038.3 | −1014.2 | −386.0 | −423.5 | −418.5 |
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||||||
| Symmetric disubstituted | ||||||
| 44cc | −914.4 | −1029.2 | −1011.4 | −379.9 | −419.0 | −417.1 |
| 44ss | −921.1 | −1032.4 | −1008.1 | −383.2 | −420.6 | −415.5 |
| 44tt | −914.5 | −1025.6 | −1002.6 | −379.9 | −417.2 | −412.7 |
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||||||
| Asymmetric disubstituted | ||||||
| 441c | −945.6 | −1063.2 | −1046.1 | −395.4 | −436.0 | −434.5 |
| 44cs | −921.5 | −1035.1 | −1013.8 | −383.4 | −421.9 | −418.3 |
| 44ct | −919.8 | −1033.2 | −1012.8 | −382.5 | −421.0 | −417.8 |
| 441s | −938.3 | −1052.5 | −1031.8 | −391.8 | −430.6 | −427.3 |
| 441t | −935.9 | −1050.1 | −1030.1 | −390.6 | −429.4 | −426.5 |
| 44st | −918.8 | −1030.2 | −1006.5 | −382.1 | −419.5 | −414.7 |
To understand this better, within the implicit solvation model based on density (SMD) approach, we can decompose the
further into two main contributions: (1) the ΔGENP and (2) ΔGCDS. The ΔGENP takes into account the bulk-electrostatics from the solute electronic kinetic and electronic-nuclear coulombic energies in the presence of the solvent (EN) and the solution polarization (P) free energy.34,35 The ΔGCDS accounts for the non-electrostatic effects of cavitation (C, energy required to make room in the solvent for the solute), dispersion (D, change in dispersion energy upon dissolution), and changes in the solvent structure (S, energetic and entropic effects from structural changes in the solvent).34,35 By evaluating ΔGENP and ΔGCDS separately, we can gain insights into the effects of the structural modifications of the cations to the 
As mentioned earlier, in all solvents and for both +4 and +5 states considered,
increases (more positive) with cationic size (Table 2, Fig. 5a and b), indicating that solvation becomes less favorable. This could be attributed mainly to the reduced bulk-electrostatic interactions (ΔGENP) as the cation size is increased (Fig. 5c). The smaller cations have more favorable bulk-electrostatic interactions (Fig. 5c). Electrostatic potential maps from natural population analysis charges reveal that the unit charge of the cations is distributed over the hydrogens of the carbon atoms adjacent to the nitrogen atom (Fig. S2†). In general, as the alkyl chain length increases, the solvent access towards these hydrogen atoms becomes more restricted, thus reducing bulk-electrostatic interactions. Interestingly, the [N3333]+ and [N4444]+ cations have similar ΔGENP (Fig. 5c) across all solvents, suggesting that the bulk-electrostatic penalty diminishes beyond three carbon atoms (e.g., for [N111x]+ and [Nxxxx]+ in MeCN, see Fig. 5g and h).
An inverse trend is observed for the ΔGCDS of the symmetric cations (Fig. 5d) where increasing the cation size improves stabilization from non-electrostatic interactions. However, unlike the ΔGENP, there is no apparent diminishing effect for the ΔGCDS after three carbon atoms (see Fig. 5g and h for [N111x]+ and [Nxxxx]+ in MeCN), and it progressively became more favorable as less polar solvents were used. Furthermore, there is a clear difference between the ΔGCDS of [N3333]+ and [N4444]+ as the solvent polarity is decreased. Although the ΔGCDS contribution is significantly smaller than ΔGENP, in cations with roughly the same ΔGENP, the ΔGCDS can be the determining factor for a better
such as in the case of [N3333]+ and [N4444]+ which leads to a more negative
for [N4444]2[VBH] and [N4444][VBH] compared to [N3333]2[VBH] and [N3333][VBH], respectively, in THF and MeCN. This also provides a rationale for the experimentally observed enhanced solubility of [N4444]y=1,2[VBH] in THF.
The same observation can be made for the modified [N11xx]+ (Fig. S1a and b†) as the symmetric ones with a similar diminishing ΔGENP penalty beyond three carbon atoms. For the [N44xx]+ modifications (Fig. S1c and d†), the use of the bulkier sec- and tert-butyl appears to restrict solvent access further, leading to less favorable
when compared to the symmetric [N4444]+. In contrast, the smaller methyl substituent allowed for better solvent access, which resulted in the greatest improvement, followed by the –CF3, of
in the [N44xx]+ group.
The effect of hydrogen bonding interactions between the VBH anions and protic solvents significantly improved the ΔGENP (Fig. 5e). As expected, the response of ΔGENP towards changing the solvent is similar for both [VBH]2− and [VBH]−, which differed only in the scale due to the charge difference. Also, preference towards MeCN over DMSO is observed for the VBH anions and is due to the slight acidity of the hydrogen atoms of MeCN (Abraham's hydrogen bond acidity, αMeCN = 0.07) despite being classified as aprotic. Almost identical values of ΔGCDS (Fig. 5f) were observed for both oxidation states of the VBH anion. While solvents with acidic protons should be considered for NRFB applications only with caution, since they would be expected to affect the electrochemical stability windows negatively, this is nevertheless an interesting observation and an important consideration in optimizing the solvent to be used in an electrolyte formulation.
in MeCN of each crystal relative to the most soluble in both oxidation states, [N4444]2[VBH] and [N4444][VBH]. This approach eliminated the numerical inconsistencies from the different computational methods and approximations used to treat the bulk crystalline and solvated systems, outlined in the Methods and ESI sections,† highlighting the differences attributed only to the cation composition and solvent used. The resulting solubility values can then be interpreted as either greater than or less than the solubility of [N4444]x=1,2[VBH] in MeCN. Fig. 6 shows the relative
in MeCN for the V4+ and V5+ crystals along with the components it comprises,
and
Our results show that
is predominantly governed by the
in agreement with our experimental observation where [N1111]y=1,2[VBH] exhibited the least solubility despite having the most favorable
These results support that the models and methodology employed can reliably capture solubility trends and can be an efficient tool in tuning the thermodynamics useful for solubility improvements. The observed modest increase in solubility for the desymmetrized cations, [N1113]+ and [N1114]+ (Table 1) was also captured by the simplified models and can be explained by a modest reduction of the corresponding
compared to [N1111]+. We note that in the [N1111][VBH] crystal, the actual packing involved 16 formula units (Z = 16) and that stability from this quasi-amorphous packing is not captured by the simplified model, hence the underestimation of the calculated
for [N1111][VBH] and possibly for [N1113][VBH] and [N1114][VBH]. Nevertheless, these simplified models can provide qualitatively accurate
albeit systematically higher, approximations for crystals with smaller Z.
Fig. 7 and 8 show heat maps of the calculated solubilities, in the logarithmic scale, of the crystals in the V4+ and V5+ states, respectively, using different solvents. In these figures, the greener a cell is, the more soluble that particular crystal is in the corresponding solvent relative to the solubility of [N4444]2[VBH] or [N4444][VBH] in MeCN. Among the branched and straight-chain, symmetric and asymmetric alkylammonium VBH compounds we investigated, in the V4+ state, the [N4444]+ cation is the most soluble, followed closely by [N444c]+ and [N441t]+. In the V5+ state, the use of the cations [N444t]+, [N44ss]+, [N44st]+, or [N44ct]+ showed better solubilities than [N4444][VBH] and will be the focus of synthetic efforts.
results suggest that alcohols could improve the solubilities of both V4+ and V5+ crystals. The more polar solvents N,N-dimethylacetate and N,N-dimethylformamide, and the less polar propanonitrile, are also promising solvents for the V5+ crystals (Fig. 8). Although alcohols appear to be promising solvents based on solubility, their protic nature could pose unwanted degradation reactions in prolonged cycling. Their affinity towards absorbing atmospheric moisture could also prove to be problematic in longer operations.36
To demonstrate the viscosity behavior of VBH electrolytes, we measured the viscosity of [N4444]2[VBH] in DMSO and MeCN at 0.01 M, 0.05 M, 0.1 M, 0.2 M, and 0.5 M concentrations (Fig. 9). Our results show that viscosity generally increases with solution concentration. Moreover, the viscosity of DMSO electrolyte depends more steeply on concentration than the MeCN electrolyte, which could considerably impede the flow performance at the concentrations that we wanted to achieve with increased pumping power requirements and slower reaction kinetics. Our findings demonstrate the vital role of the viscosity of the electrolyte solution in choosing the appropriate solvent. A rough approximation of the resulting viscosities can be obtained from the kinematic viscosities (Table S2†) of all the solvents used in the calculations. Although we predicted that N,N-dimethylacetate, N,N-dimethylformamide, and propanonitrile are favorable solvents from the perspective of active-material solubility, these solvents' viscosities are significantly higher than that of MeCN, which will likely hinder their practical applications.
Design strategies should take into account the solid-state energetics. In our efforts to find VBH compounds with high solubility, we found that, while desymmetrization of the cation can be important, it does not always lead to a more soluble active material. One design strategy for improving VBH solubility using alkyl ammonium cations is by increasing the alkyl chain lengths, which is favorable with respect to lattice free energy, but unfavorable with respect to solvation free energy because of the steric hindrance imparted by the larger cations. In this, and in previous work,5 we demonstrate that the former effect outweighs the latter, giving rise to the overall improvement to solubility observed for longer alkyl-chain cations. With the computational investigations reported herein, we elaborate that the electrostatic interaction between the cations and the solvent becomes less effective as the alkyl chain length is increased up until 3-carbon atoms, then plateaus. This implies that, as a design strategy for improving solubility, the use of alkyl ammonium cations with chain-lengths of 4-carbon atoms, or more, should exhibit a reduced lattice free energy with a decreasingly significant penalty to solvation free energy. Another design principle for improving VBH solubility is the use of bulky substituents. This effect is particularly pronounced in the V5+ crystals where lattice electrostatic interactions are lower than in the V4+ crystals. Compared to their straight-chain counterparts, sec- and tert-butyl substituents showed appreciable reduction of
and slight increase in
Nevertheless, these responses from bulky substituents, together with alkyl chain length, are promising, and will be explored in our future efforts.
This work is an in-road toward VBH active materials with very high solubility and potentially those that are liquid at operating temperature. If viscosity concerns could be mitigated, the production of such liquid active materials would significantly increase energy density and could eliminate the need for supporting electrolytes. Furthermore, the establishment of this theoretical framework, coupled with experimental verifications, opens avenues for machine learning models and other computational screens of solution properties (e.g., diffusion rates, viscosities, and ionic conductivities), both of which are parts of our in-road strategy for designing high energy density NRFB active materials. Because the methods involved in this computational protocol are available in most computational chemistry programs, this strategy can be applied to any RFB chemistry including organic aqueous systems, with the cost and complexity of such calculations largely depending on the composition and size of the system.
![]() | (1) |
is the free energy of dissolution and is the sum of the free energies of sublimation
and solvation
while R, T, and Vm are the gas constant, temperature, and the solid's molar volume, respectively. In this cycle, a substance first sublimes into the gas phase, then gets solvated into the solution phase and the free energies associated with each process determine its dissolution. The free energy of sublimation is roughly the negative of the lattice free energy
. The details of the theory and corresponding equations are given in ESI†.30–32,38–40
Starting geometries for single formula unit crystals of the systems with symmetric cations ([N1111]+, [N2222]+, [N3333]+, and [N4444]+) were extracted from the X-ray crystal structures for both reduced and oxidized states. Five of these have been reported previously5,22,23 and two are newly reported herein (Fig. 3 and Table S6†). These crystals were then equilibrated using the method discussed below. The resulting optimized crystal structures of the [N1111]+ and [N4444]+ systems were then subjected to cation modification and re-optimization.
Plane-wave-based periodic density functional theory (DFT) calculations for the sublimation free energies were performed using Quantum Espresso v6.5 (QE).41,42 The valence electronic states were expanded based on plane waves, and the core–valence interaction was described using the ultrasoft pseudopotential approach. The Perdew–Burke–Ernzerhof (PBE)43 generalized gradient approximation functional with a 1225 eV and 9796 eV basis set cutoffs for the plane wave kinetic energy and the electron density, respectively, were used. Spin-polarization was used for the open-shell systems (V4+ crystals; d1), while non-polarized calculations were done for the closed-shell systems (V5+ crystals; d0). For the bulk calculations, the Brillouin zone was sampled using a Monkhorst–Pack k-point mesh of 2 × 2 × 2 with grid offsets, resulting in less than 0.0001 eV change in the total energy compared to 3 × 3 × 3. The two-body dispersion interactions in the crystals were included using Grimme's DFT-D2 (ref. 44 and 45) method implemented in QE. The atomic coordinates and cell parameters were fully optimized to a 1 × 10−5 eV and a 1 × 10−5 eV Å−1 force threshold. Given the size of the unit cells (containing 46 to 135 atoms), the phonon frequencies were only calculated at the Gamma point.33,46
The free energy of solvation
47,48 was obtained using the implicit solvation model based on density (SMD) method34 as implemented in Orca v4.2.1.49 Each ion was first optimized in the gas phase using the PBE functional and Grimme's DFT-D3 (ref. 50) dispersion correction with the Becke–Johnson damping (D3BJ)51 with a def2-TZVP52 basis set. SMD was then employed on the gas-phase structures to obtain the standard free energy of solvation.47,53,54 A list of battery-relevant solvents used in this study is listed in Table S2.†
New compounds, [N1111][VBH], [N2222][VBH], [N1113]2[VBH], [N1113][VBH], [N1114]2[VBH], and [N1114][VBH] were verified by comparison of infrared and UV-vis spectra with closely related compounds that have been published previously.5,22,23 Furthermore, the molecular ions in positive and negative polarity were verified to match calculated values. In addition, the newly reported V5+ compounds were verified with 1H NMR, by integrating the methylene and methyl protons of alkylammonium cations and comparing with the methylene protons of [VBH], in manner similar to that reported earlier.5 Finally crystal structures of the new compounds [N1111][VBH], [N2222][VBH], and [N1114]2[VBH], are presented herein.
O, s).
O, s).
O, s), 1492 (C–N, w). HR-MS (ESI, positive ion mode) m/z calculated for C4H12N+ [M]+: 74.0964, found: 74.0954. MS (ESI, negative ion mode) m/z calculated for VBH− [M]−: 342.9624, found: 343.0712.
:
1 molar ratio in a polar solvent such as methanol, acetonitrile, or DMSO, as shown in Scheme 2. Then, the volume was doubled by adding diethyl ether to aid the precipitation of the product. The red crystalline powder obtained was repeatedly washed with diethyl ether to remove traces of ferrocene. The product obtained was characterized using 1H NMR, 13C NMR, FTIR, UV-VIS spectroscopy, and HR-MS. Removal of ferrocene and tetrabutylammonium hexafluorophosphate was confirmed by 1HNMR. Details of each preparation are described below.
:
1 methanol/dmso to make 5 mL solution. FcPF6 (0.349 g, 0.00106 mol) was added to the solution and stirred for 10 min after which 20 mL diethyl ether was added to facilitate precipitation. Red powder was filtered and washed with diethyl ether until trace of ferrocene was removed. The product was dried in vacuo (yield: 0.39 g, 88%). UV-Vis (MeCN): λmax = 495 nm (ε = 242 mol−1 cm−1). IR (ν/cm−1): 2978 (w), 2934 (w), 1663 (s), 1486 (m), 1360 (m), 1330 (w), 1257 (m), 1242 (m), 1153 (m), 1010 (w), 951 (m), 915 (s), 890 (m), 722 (w), 626 (s), 595 (m), 539 (w). δH (400 MHz, CD3CN) 4.95 (2H, d, J 16.1), 4.68 (2H, d, J 16.1), 4.59 (2H, d, J 16.8), 4.42 (2H, d, J 16.1), 3.07 (12H, s). δC (101 MHz, DMSO) 170.78, 170.54, 65.42, 64.55, 54.93. HR-MS (ESI, positive ion mode) m/z calculated for C4H12N+ [M]+: 74.0964, found: 74.0949. MS (ESI, negative ion mode) m/z calculated for VBH− [M]−: 342.9624, found: 343.0705.
:
1 MeCN/EtOH to make 20 mL solution. FcPF6 (1.33 g, 0.00401 mol) was added to the solution and stirred for 20 min. 20 mL diethyl ether was added to aid precipitation of the complex and the precipitate was filtered which was then washed with 10 mL portion of diethyl ether five times until trace of ferrocene was removed. Finally, red crystalline powder was dried in vacuo (yield 1.53 g, 87%). UV-Vis (MeCN): λmax = 495 nm (ε = 241.9 mol−1 cm−1). IR (ν/cm−1): 2951 (w), 1650 (s), 1478 (w), 1402 (w), 1351 (m), 1297 (m), 1245 (m), 1213 (w), 1154 (m), 967 (w), 915 (m), 895 (m), 763 (w), 721 (w), 624 (s), 589 (m), 564 (w), 542 (w). δH (400 MHz, CD3CN) 4.94 (2H, d, J = 16.1 Hz), 4.68 (2H, d, J = 16.1 Hz), 4.59 (2H, d, J = 16.0 Hz), 4.42 (2H, d, J = 16.0 Hz), 3.16 (2H, t, J = 8.4 Hz), 3.00 (9H, s), 1.74 (2H, h, J = 7.4 Hz), 0.95 (3H, t, J = 7.4 Hz). δC (101 MHz, DMSO) 170.33, 170.04, 66.77, 64.80, 64.16, 52.17, 15.68, 10.48. HR-MS (ESI, positive ion mode) m/z calculated for C6H16N+ [M]+: 102.1277, found: 102.1289. MS (ESI, negative ion mode) m/z calculated for VBH− [M]−: 342.9624, found: 343.0724.
Footnote |
| † Electronic supplementary information (ESI) available. CCDC 2103585–2103587. For ESI and crystallographic data in CIF or other electronic format see DOI: 10.1039/d1sc04990a |
| This journal is © The Royal Society of Chemistry 2021 |