Synthetic Design of Polyester Electrolytes Guided by Hydrophobicity

Article pubs.acs.org/Macromolecules

Synthetic Design of Polyester Electrolytes Guided by Hydrophobicity Calculations Erol Yildirim,† Deivasagayam Dakshinamoorthy,‡ Matthew J. Peretic,‡ Melissa A. Pasquinelli,*,† and Robert T. Mathers*,‡ †

Fiber and Polymer Science Program, North Carolina State University, Raleigh, North Carolina 27695, United States Department of Chemistry, The Pennsylvania State University, New Kensington, Pennsylvania 15068, United States

‡

S Supporting Information *

ABSTRACT: Partition coefficients (LogP) help to quantify hydrophobicity, which can be used to guide the design of polymer electrolytes with targeted properties. Thus, this study combined synthetic experiments and molecular modeling to produce polyester electrolytes that solubilize lithium salts. These polyester electrolytes were derived from natural sources and polymerized with different ratios of polyols (diglycerol, glycerol, and diethylene glycol) and citric acid in the presence of lithium salts (LiTf and LiTFSI). The Fisher esterification produced homogeneous, cross-linked films with high optical transparency, whereas the lithium salts increased glass transition temperatures. The LogP values of monomers and the resulting polyesters were predicted using cheminformatics tools and indicate changing diglycerol to glycerol or diethylene glycol alters the hydrophobicity. Comparison of different molecular modeling methods with predicted LogP values demonstrate that LogP values are a reliable means of tailoring physical and chemical properties of these polymer electrolytes. Additionally, LogP values greatly benefit from being extremely less expensive from a computational standpoint as well as more convenient for calculating precursory quantitative information.

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INTRODUCTION Hydrophobicity and hydrophilicity have been recognized as important considerations during the investigation and optimization of polymer electrolytes and conductive polymeric materials.1,2 In fact, the degree of hydrophobicity strongly influences mixing,3 solubility,4 ion conductivity, prevention of ion clustering,5 oxygen permeation,6 and corrosion of electrodes.7 Yet, determining the balance between hydrophobicity and hydrophilicity remains a challenge for polymer electrolytes. As depicted in eq 1, partition coefficients (LogP) describe how small molecules, monomers, or drugs would prefer to dissolve in a two-phase system. In regard to the various types of LogP values, the most prevalent has been octanol−water partition coefficients (denoted Kow, LogPo/w, or LogPoct).8 These LogPoct values quantify hydrophobicity on a continuum and range from positive (hydrophobic) to negative (hydrophilic). To account for polymerization of monomers, computational assessment of oligomers has been proposed to model the behavior of homopolymers and copolymers.9

influence of a long alkyl chain (i.e., decylphosphonic acid, LogPoct > 0) with a very hydrophilic analogue (i.e., phosphoric acid, LogPoct < 0).14 The second strategy involves incrementally increasing hydrophobicity by varying the number of methyl groups on monomers,1,15 the size of perfluorinated surfactants,16 the number of carbon spacers in poly(ether− thioethers),17 or the type of side chains.18−20 Although these empirical approaches have been quite successful, opportunities exist to more succinctly express hydrophobicity on a continuum. As such, we wondered if the design of polymer electrolytes could benefit from a screening tool to computationally predict how structural changes to monomers or ionic additives will change hydrophobicity. For instance, from an intuitive approach, the addition of methyl groups to bisphenol A (BPA) increases hydrophobicity in Scheme 1 and benefits polymer electrolytes.1 However, calculating LogPoct values clearly illustrates more than an order of magnitude difference between BPA and the tetramethyl analogue. In addition to quantifying the influence of methyl groups, LogPoct values also have potential to illuminate the effect of trifluoromethyl groups. For instance, in Scheme 2, lithium triflate (LiTf) and lithium bis(trifluoromethane sulfonyl)imide (LiTFSI) have differences in hydrophobicity.

LogP = log([solute in organic phase]/[solute in water]) (1)

Two general types of empirical investigations have been noted in recent years. The first involves picking two components with very different hydrophobicity. For instance, polystyrene has been combined with PEG,10,11 sulfonated polystyrene,12 or a polyacrylate with alkylphosphonium bromide groups.13 Other examples include comparing the © XXXX American Chemical Society

Received: July 6, 2016 Revised: September 23, 2016

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DOI: 10.1021/acs.macromol.6b01452 Macromolecules XXXX, XXX, XXX−XXX

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Macromolecules Scheme 1. LogPoct Values (Materials Studio) Illustrate the Influence of Methyl Substituents on Hydrophobicity

Scheme 3. Chemical Structures for (a) Citric Acid (CA) as Well as the Polyols, (b) Glycerol (G), (c) Diglycerol (DG), and (d) Diethylene Glycol (DEG)

TGA, and UV/vis spectroscopy are detailed in the Supporting Information. Generally, the polycondensation of polyols and CA at 110 °C was inspired by solvent-free methodologies57 of polyols39,58 and citric acid.59 To provide homogeneous films, addition of lithium salts was enhanced by a small quantity of water (0.5 mL). Typical film thicknesses were ∼1.0 mm, and the diameter was ∼6.8 cm (see Figure S14).

Scheme 2. LogPoct Values (Materials Studio) for LiTf and LiTFSI

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COMPUTATIONAL METHODOLOGY Different molecular modeling tools were employed in this study, depending on the desired properties for different ratios of CA with DG, DEG, and G: LogPoct values were predicted using a new strategy9 that is based in cheminformatics (see Scheme S12); molecular surface areas were calculated from molecular mechanics calculations; the total hydrophobic surface areas (TASA) and the relative hydrophobic surface areas (RASA) were estimated through the calculation of Jurs topological descriptors; cohesive energy densities and Hildebrand solubility parameters were calculated for the average of five lowest energy amorphous cells of polyester thermosets from 40 amorphous cells of polyesters optimized by molecular mechanics methods; mixing energies were predicted using an off-lattice extended Flory−Huggins approach; adsorption configurations and adsorption energies for the lithium salts were calculated with Monte Carlo (MC) calculations; and interaction energies of the lithium salts and monomers of polyesters given in Scheme 3 were calculated with density functional theory (DFT). The predicted structures for the polyesters are given in Schemes S1−S11, and the different initial structures for the calculations with the lithium salts are given in Scheme S13. Please refer to the Supporting Information for detailed methodology for all calculations.

The incorporation of lithium salts into polymer systems has received enormous attention.21 Many of these investigations have focused on synthesis, conductivity, or ion transport.22,23 Polymer electrolytes can be produced by dissolving polymer and salt and then evaporating the solvent. Selected examples include poly(ethylene oxide)/poly(vinyl chloride) blends,24 poly(vinylidene fluoride)/poly(vinyl alcohol) blends,25 polycarbonates,26−28 polyesters,29−33 and cellulose.34 While the notion of hydrophobic character has been recognized as important,35 elucidating new methods to quantify hydrophobicity has great potential. As a result, this report focuses on the melt polymerization of a new polyester thermoset containing lithium salts. Because of the ongoing quest for safer electrolytes,36 as well as biomass-derived monomers,37−41 solvents,42−45 polymers,46−52 and thermosets,53−56 the polymerization of renewable molecules has been examined. Specifically, citric acid (CA) has been investigated with a series of polyols (Scheme 3): diglycerol (DG), glycerol (G), and diethylene glycol (DEG). This choice of monomers was guided by a new strategy9 (see Scheme S12) for quantifying hydrophobicity of polymer electrolytes. Quantitative information acquired by hydrophobicity values were compared and validated with results from different levels of molecular modeling calculations and reveals that the use of the predicted LogPoct values is a more convenient and quick approach for calculating precursory quantitative information in order to guide the design of polymer materials, particularly polyester electrolytes.

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RESULTS AND DISCUSSION Characterization of Monomer Hydrophobicity. Initially, the hydrophobicity of three different polyols was investigated to determine how chemical structure and number of hydroxyl groups would ultimately influence the design of polyester electrolytes. As a result, both experimental studies and computational chemistry calculations were performed to better understand and quantify hydrophobicity. Solvatochromatic dyes, like Nile Red, change color depending on the polarity of the solution and give a visual indication of hydrophobicity.60 Figure 1 contains the LogPoct values of G, DG, and DEG, which were normalized by Connolly surface area, and plotted against

EXPERIMENTAL METHODOLOGY

Materials, experimental procedures for the polymerization, and characterization of the resulting films by FTIR spectroscopy, DSC, B

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hydrophobicity and functionality of the polyol. For instance, the different functionalities ( f n) of DG (f n = 4), G ( f n = 3), and DEG (f n = 2) shifted the position of the maximum along the x-axis. For comparison (Table S1), the range of values in Figure 2 was less than poly(hydroxyethyl acrylate) (PHEA) (LogPoct/SA = −0.0026) and more closely resembled poly(vinyl alcohol) (LogPoct/SA = −0.0060). As indicated in Figure S15, the trend with respect to stoichiometry is independent of the choice of software tool for predicting LogPoct, even though each approach calculates a different absolute value for LogPoct. This significant observation supports the utility of using LogP values to guide synthetic design. In order to compare LogPoct values with other computational techniques, solubility parameters (δ) (Figure 3) were calculated for different monomer ratios of CA polymerized with G, DG, and DEG. Although the magnitude of the vdW component of δ, which was calculated by neglecting electrostatic interactions, is higher than the electrostatics contributions for all three polyol systems, the change in vdW with varying [DG]/[CA] ratio is less significant. However, the electrostatics component of δ has the same trend with the total solubility parameter; thus, it can be inferred that the trend in δ as a function of monomer ratios is mainly dependent on the electrostatic interactions. Both the total δ and electrostatic contribution to δ have the opposite trend with the LogPoct values in Figure 2, which suggests that increasing solubility by higher polar (electrostatic) interactions between chains reduces the hydrophobicity of the polyester. Also note the computational cost of these calculations; for each polymer composition, the construction of 40 amorphous cells and their 5000 step molecular mechanics minimization of these cells completed after ∼8 h on a single intel-i7-860 core, and thus the total computational time for all systems is ∼120 h. In contrast, the LogPoct calculations for all structures at all different ratios lasted less than a minute and resulted in a similar conclusion. To visually correlate which functional groups in the molecular models found in Figure 2 contribute to an increase or decrease in LogPoct values, local polar and nonpolar sites were mapped with red and blue colors on the molecular surfaces. As shown in Figure 4, clear differences in hydrophobicities result with changes in stoichiometry for G, DG, and DEG based polyesters. The degree of local hydrophilic and hydrophobic sites agrees with the total value of LogPoct calculated with different software programs (Figure 2 and Figure S15) and emphasizes that increasing hydrophilic (red) sites are the main reason for the more negative LogPoct values for DG and G, without surface area correction. Based on LogPoct values and visual inspection of images in Figure 4c, DEG exhibits less hydrophilic sites than G and DG. Thus, LogPoct calculations are the most convenient way to get precursory molecular level information without time-consuming DFT and classical molecular simulations. To further elaborate on Figure 4, a Jurs topological QSAR descriptor, known as the relative hydrophobic surface area, was investigated as a function of stoichiometry (Figure 5) and compared to LogPoct values. Interestingly, the general trend for the relative hydrophobic surface area in Figure 5 is the same as the LogPoct results in Figure 2. However, the main advantage of using LogPoct values over other fast topological descriptors like the Jurs method relates to the physical meaning of partition coefficient in different solvents, which can be validated experimentally; in contrast, absolute low partial atomic charges

Figure 1. Comparison of the hydrophobicity of G (◆), DG (●), and DEG (▲). The inset picture is a photo of the color differences resulting from Nile Red in neat G (left cuvette), neat DG (center cuvette), and neat DEG (right cuvette).

the λmax values for Nile Red. The visual differences in color suggest that hydrophobicity decreases as follows: DEG > DG > G. Hydrophobicity of Polyester Thermosets. In addition to Figure 1, cheminformatics tools were also used to predict LogPoct values for potential polyesters. In previous work where we introduced this approach, the hydrophobicities of homopolymers and copolymers were successfully modeled by linear oligomers of 3−5 and 6−10 units, respectively.9 In contrast, this study employs larger branched oligomers with 11−14 monomer units to more accurately represent multifunctional monomers and cross-linking in a thermoset. As such, a series of molecular models for DG, DEG, and G polymerized with CA are proposed in Schemes S1−S11. To represent connections between the model and the rest of the thermoset, OH groups on DG, DEG, and G were converted to acetate groups and COOH groups on CA were symbolized as methyl esters. As depicted in Figure 2, the average degree of hydrophobicity, which was quantified by LogPoct/SA, varied with

Figure 2. Influence of stoichiometry on predicted LogPoct values of thermosets as a function of the ratio of CA with G, DG, and DEG. The LogPoct values were normalized by molecular surface area (SA).

stoichiometry. Remarkably, the maximum for DG in Figure 2 corresponds to the stoichiometry that contains equal numbers of OH and COOH groups. At this stoichiometry, a thermoset with 100% conversion would not have any unreacted OH and COOH in order to lower its hydrophobicity. A maximum was also noted when DG was changed to G and DEG. However, the position of the observed maximum depends on the C

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Figure 3. Total (●), vdW (▲), and electrostatic contributions (◆) to the solubility parameter for decreasing [CA] ratio polymerized with (a) G, (b) DG, and (c) DEG, calculated from a molecular mechanics energy minimization. Error bars are also indicated, although most are smaller than the symbol size.

and molecular solvent accessible surface areas are physically less meaningful in an experimental study. Impact of Li Salts on DG/CA Polyester Thermosets. Given the positive LogPoct values for LiTf (1.79) and LiTFSI (2.99), the addition of these lithium salts to thermosets is proposed to increase hydrophobicity and shift the trend in Figure 3 toward more positive values. This hypothesis is also supported by observations that adding LiTFSI to latexes61 and polycarbonates62 increases their hydrophobicity. In order to pick an appropriate polyester matrix to solubilize lithium salts, the experimental insight in Figure 1 and the cheminformatics perspectives in Figures 2−5 gave a starting point for choosing a polyol and stoichiometry. Consequently, DG, which has an intermediate hydrophobicity relative to G and DEG, was chosen. After deciding to focus on polyesters films with DG as a polyol, a series of control experiments were devised to optimize the solubility of LiTf and LiTFSI in DG in order to prepare homogeneous films. These included visual inspection of various stoichiometry, DSC measurements, melting point determination, and TGA measurements. First, visual inspection revealed that DG had potential to dissolve LiTf and LiTFSI over a wide stoichiometry range ([DG]/[Li] ∼ 0.5−2) without the need for organic solvents. For comparison, lithium salts were much more soluble in DG compared to sodium and potassium analogues (Figure S1). Additionally, the lithium salts appeared more soluble in DG than several other solvents with alcohol and ether functionalities (Figure S2) such as ethylene glycol (EG) and diethylene glycol (DEG). Second, DSC (Figure S3) detected a remarkable decrease in the crystallinity after heating and mixing LiTFSI with diglycerol for 15 min. Based on these DSC results and stoichiometry experiments, heating LiTFSI with an excess of DG prior to the melt polymerizations will enhance homogeneity. Third, data from a melting point apparatus confirmed that an opaque LiTf/DG mixture prepared at ambient temperature became completely clear with heating (Figure S4). In terms of the polymerization process, a combination of heat and high surface area allowed citric acid and DG to undergo Fisher esterification and form a polyester thermoset (Scheme 4). Mixing and preparation of clear, homogeneous films (Figure S5) was further enhanced by grinding citric acid particles to LiTf-CA > LiTFSI-DG > LiTFSI-CA. This order indicates that structure and polarity of Li salt is more important than [DG]/[CA] ratio for mixing; however, from a practical standpoint, certain [DG]/[CA] ratios are necessary (see Figure 7) when mixing relatively hydrophobic salts with

Figure 4. Local hydrophobic (blue) and hydrophilic (red) regions on the molecular surface of polyester thermosets using varying ratios of CA with (a) G, (b) DG, and (c) DEG. For clarity, the 2D chemical structures are shown next to each molecular surface.

triflate.64 Based on computational studies, LiTFSI in PEO has 4.6 ether oxygen atoms coordinated to Li+.65 For comparison, copolymers with ester and ether groups have ∼3−4 carbonyl oxygen atoms surrounding a Li+ ion along with ∼1−2 ether oxygen atoms depending on structure of the polymer chain.32 E

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Macromolecules Scheme 4. Polymerization of DG and CA

Figure 8. Effect of stoichiometry and addition of LiTf on the glass transition temperature (Tg). Films were heated for 30 h at 110 °C without lithium salts (◆) and with 0.50 (▲) and 0.25 equiv (■) of LiTf. The solid line represents a linear regression fit (R2 = 0.9645) for samples without lithium salts (◆).

Figure 6. FTIR spectra for polymerization of citric acid and diglycerol at 110 °C with a ratio of [DG]/[CA] = 1.5. The y-axis contains the normalized area of the OH and COOH absorbances (3700−3100 cm−1). The polymerizations were run without lithium salt (●) and with 0.50 equiv of LiTf (◆) and 0.50 equiv of LiTFSI (▲). The solid lines represent logarithmic regression.

Table 1. Thermal Analysis Data for [DG]/[CA] = 1.25 as a Function of Polymerization Time Conducted at 110 °C entry

time (h)

Tg (°C)

Td,max (°C)

1 2 3

20 30 45

24.8 30.5 56.8

321 329 358

coordinations, taking 26−36 h in real time to calculate, even with the minimal basis set with eight 1233 dual socket Intel Xeon Processors servers. In other words, these sophisticated calculations are 105 times more expensive computationally compared to LogPoct calculations. Surface adsorption energies were calculated with the Monte Carlo simulated annealing method, which were conducted with a 30 × 30 × 30 Å3 amorphous cell with 30 Å vacuum slab in the z-direction. Rigid molecule adsorption energies for LiTf and LiTFSI are given in Figure 10a for three salt molecule adsorption onto the polyester surface with three different [DG]/[CA] ratios. Figure 10b is the lowest energy structure for LiTf on the surface of cell with [DG]/[CA] = 1.0. Both the LiTf and LiTFSI adsorption energies increase with increasing [DG]/[CA] ratio. However, the amount of increase in the interaction with relatively more hydrophobic LiTFSI is less than for LiTf. We expect that [DG] will still be higher

Figure 7. UV/vis transmission at 700 nm for 0.33 equiv of LiTf that was polymerized with various ratios of DG and CA at 110 °C for 20 h.

monomers. Based on Figure 9a, different ratios of CA and DG could be used for hydrophobic salts. These results are in agreement with the experiments that indicated that increasing [DG] concentration produce better optical transparency due to the increasing OH groups. Although DFT calculations are more accurate, they are computationally expensive for five molecule F

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Table 2. For DG and CA Mixing with LiTf and LiTFSI, Mixing Energies, Average Binding Energies of Pairs, and Coordination Numbers (Units for All Energy Values Are kcal/mol) i

j

Emix

Eii

Eij

Ejj

Cii

Cij

Cji

Cjj

DG DG CA CA

LiTf LiTFSI LiTf LiTFSI

−164.94 −128.80 −134.64 −99.91

−3.31 −3.31 −5.33 −5.33

−10.23 −8.94 −5.88 −4.73

41.88 31.91 41.88 31.91

5.53 5.53 5.56 5.56

6.79 5.61 6.51 5.35

4.49 5.45 4.75 5.75

5.56 5.55 5.56 5.54

supported by molecular modeling studies that yielded LogPoct predictions as well as solubility, mixing energy, and interaction energy values. Our results suggest that calculating LogPoct values is computationally fast and yields insights that both experiments and more sophisticated modeling approaches corroborated. Thus, LogPoct calculations, which have a physical meaning, provide a simple approach to guide the design of polymer electrolytes that is connected to other properties, such as miscibility. However, the overall accuracy of LogPoct predictions will depend on several factors. These include how well the molecular models (see Scheme S1−S11) reflect the polymeric microstructure and which molecules are used in the training set of the computational software. Although the various LogPoct prediction tools that we tested provided different absolute LogPoct values, remarkably all tools yielded the same overall trend as a function of increasing stoichiometry, which is more relevant for guiding synthetic design.

Figure 9. From DFT calculations, (a) interaction energies for both Li salts coordinated by either five DG or CA, and vice versa, and (b) lowest energy structure for DG coordinated by five LiTf molecules.

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.macromol.6b01452. Table S1, Schemes S1−S13, Figures S1−S15, and Sections S1−S2 (PDF)

Figure 10. From Monte Carlo simulations, (a) adsorption energies for LiTf and LiTFSI onto polymer surface based on polymerization of DG and CA at different ratios and (b) Three LiTf molecules on the polymer surface with [DG]/[CA] = 1.0.

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AUTHOR INFORMATION

Corresponding Authors

compared to [CA] for LiTFSI salts; however, the [DG] amount always should be much higher for LiTf salts.

*E-mail [email protected] (R.T.M.). *E-mail [email protected] (M.A.P.).

CONCLUSION The investigation and design of polymeric electrolytes always include a number of hierarchical considerations. While hydrophobicity may not always be the most important facet of these complex systems, it represents a significant factor. In this regard, the concept of quantifying hydrophobicity of polymer electrolytes with LogPoct values provides a new method to design polymer materials with targeted properties by elucidating insights into the molecular differences that result from choice of monomers (Figure 1), stoichiometry (Figures 2−5), and ionic additives (i.e., LiTf versus LiTFSI) (Figures 6−10). As a proof of concept, DG and CA were experimentally reacted via a Fisher esterification to produce a polyester thermoset. Based on control experiments, lithium salts (LiTf and LiTFSI) have an appreciable amount of solubility in DG. In the case of LiTf, the most homogeneous films and highest optical clarity were obtained when [DG] ≥ ([CA] + [Li]). In comparison, LiTFSI was more soluble and a mixture of 1 equiv of CA, 1.5 equiv of DG, and 0.75 equiv of LiTFSI produced a very clear homogeneous film (Figure S15). These results were

Notes

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The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This material is based upon work supported by the National Science Foundation under Grant CHE 1308247. Thanks to Solvay Chemicals for donation of diglycerol.

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DOI: 10.1021/acs.macromol.6b01452 Macromolecules XXXX, XXX, XXX−XXX

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DOI: 10.1021/acs.macromol.6b01452 Macromolecules XXXX, XXX, XXX−XXX