The Importance of Phase Behavior in Understanding Structure

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Chapter 13

The Importance of Phase Behavior in Understanding Structure-Property Relationships in Crystalline Small Molecule/Polymer Gels Kevin A. Cavicchi,* Marcos Pantoja, and Tzu-Yu Lai Department of Polymer Engineering, The University of Akron, Akron, Ohio 44325-0301, United States *E-mail: [email protected].

A wide-range of crystalline small molecules are able to self-assemble into three-dimensional solid networks in solvents and polymers producing organogels. The design of small molecule organogelators (SMOGs) is still largely empirical as gelation is a complex process dependent on both the thermodynamics and kinetics of crystallization and assembly. This chapter demonstrates how the underlying phase behavior of two example SMOG/polymer systems are useful to understanding the properties of the gels. The two systems discussed are SMOGs as clarifying agents for semi-crystalline isotactic polypropylene and fatty acid swollen, crosslinked natural rubber shape memory polymers.

Introduction Small molecule organogelators (SMOGs) are molecules that gel non-aqueous fluids through their supramolecular self-assembly into three-dimensional, load-bearing networks (1). A large class of SMOGs form gels through the nucleation and growth of anisotropic crystals (2–4). SMOGs of this type have been discovered with a wide-range of non-covalent interactions (van der Waals, hydrogen bonding, pi-pi interactions, metal coordination, and ionic bonding), and © 2018 American Chemical Society Horkay et al.; Gels and Other Soft Amorphous Solids ACS Symposium Series; American Chemical Society: Washington, DC, 2018.

network morphologies (platelets, fibers and spherulites) (5). This diversity in chemical structure and fluid compatibility has led to the development of SMOGs as viscosity modifiers and nanoscale templating agents across a range of fluids for cosmetics and personal care products (6, 7), food science (8, 9), pharmaceuticals (10–12), organic electronics (13), oil recovery (14, 15), separations (16, 17), and nanomaterials synthesis (18, 19). This ubiquity across different applications has driven the refinement of empirical design approaches and screening methods using combinatorial chemistry, crystal engineering and solvent parameters (20–22). In turn, the increased ability to design SMOGs has allowed researchers to develop new SMOGs that respond to stimuli beyond temperature including light, mechanical force, enzymes, and ions (23). Despite these advances in SMOG design, the synthesis and application of many SMOGs are still very empirical processes (5, 20). It is known that gel formation depends strongly on the kinetics of crystallization, which depends on thermodynamic properties such as the gel transition temperature and the extent of undercooling varied by step changes in temperature or the cooling rates through the gel transition (24, 25). Furthermore, significant variation in the gel morphology can occur as the solvent or gelation pathway (cooling rate, gelation temperature) are varied (26–28). However, the full phase diagram of SMOG solutions is rarely measured. A simple example of the utility of examining the phase behavior of a SMOG solution was recently shown by Crist et al. (29) They found that liquidliquid phase separation occurred at higher concentration in solutions of a bisamide SMOG in trans-decalin. This results in an invariant melting point below the liquidliquid miscibility gap and therefore a region where the gel transition temperature is invariant with concentration. While the behavior of the gel transition temperature vs. SMOG concentration had previously been observed, it had not been adequately explained (30, 31). The objective of this chapter is to further demonstrate the importance of the phase diagram of SMOG organogels to understanding their structure-property relationships and improving the design of gels. Two examples are discussed where a SMOG is used to modify the properties of a polymer. In the first example, the use of SMOGs to act as nucleating agents in isotactic polypropylene and modify its optical properties is discussed. Here measurement of phase diagrams was crucial to understanding the non-monotonic dependence of the optical properties on the SMOG concentration in the polymer (32, 33). This work is a beautiful example of the application of material science in soft matter systems. Their similarity to more classical problems in metallurgy, such as steel manufacturing and second phase hardening (i.e. Gunier-Preson zones) (34), first inspired the authors to delve into the field of SMOGs. The second example is from the authors’ own work, where fatty acids are used to convert crosslinked natural rubber, a commodity elastomer, into a shape memory polymer (35). The phase diagram was used to understand differences in the varation of the shape memory behavior with the fatty acid concentration among different fatty acids.

246 Horkay et al.; Gels and Other Soft Amorphous Solids ACS Symposium Series; American Chemical Society: Washington, DC, 2018.

Clarifying Agents for Isotactic Polypropylene It is known that soribitol derivaties and 1,3,5-benzene trisamides are able to act as clarifying agents for isotactic polypropylene (i-PP) (36–39). Clarifying agents are a specific type of nucleating agent that, in addition to raising the crystallization temperature of the melt, improve both the mechanical and optical properties by drastically reducing the spherulite size (40, 41). In particular, they are referred to as clarifying agents due to their ability to increase the clarity (light scattered at a small angle < 2.5°) of i-PP articles (32, 42). Thierry et al. noted that 1,3:2,4dibenzylidene sorbitol (DBS) is both an excellent clarifying agent and SMOG for polar solvents through their assembly into three dimensional fibrillar networks with sub-micron diameters (41). The ability of the fibers to act as an epitaxial nucleating surface and the high surface area of the fibrillar network leads to a high nucleation density and therefore a large number of small spherulites. While there are still differences among the refractive indicies of the amorphous and crystalline polymer and the fibrillar network, the small length scale of these entities limits the light scattering, resulting in materials with high optical transparency. It was known early on in the study of clarifying agents that there is an optimum concentration for maximum clarity (43). The variation in clarity and haze (scattered light at 2.5 - 90°C) is shown in Figure 1 for 1,3:2,4-bis(3,4-dimethyldibenzylidene) sorbitol (DMDBS) in i-PP as reported by Kristiansen et al. (32) The maximum clarity and minimum haze is observed at 1.0 wt% DMDBS with a rapid loss in transparency with increasing DMDBS content. The origin of the non-monotonic optical behavior was determined from the investigation of the phase behavior of i-PP/DMDBS. Figure 2 shows the phase diagram measured on heating and cooling by a combination of DSC, rheology, and optical microscopy. It is noted that liquid-liquid phase separation of the molten solution was observed above 2 wt% DMDBS. Therefore, on cooling from the homogenous liquid state through the miscibility gap, DMDBS droplets would form resulting in large DMDBS crystals. While the DMDBS fibrils would still form and act as nucleating sites, the presence of larger DMDBS crystals would scatter light reducing the clarity and increasing the haze. A schematic diagram relating the morphology and the phase diagram is shown in Figure 3. Region II shows the wt% DMDBS range where DMDBS forms fibrils directly from the homogeneous liquid, which results in both small DMDBS and i-PP crystals leading to high clarity and low haze. In addition to the liquid-liquid miscibility gap in region III, there is a eutectic point separating region I and region II. Below the eutectic composition, the i-PP would crystallize first on cooling reducing the ability of DMDBS to act as a clarifying agent to modify the morphology of the i-PP crystals.


Figure 1. Optical properties of isotactic polypropylene (i-PP)/ 1,3:2,4-bis(3,4-dimethyldibenzylidene)sorbitol (DMDBS) for different compositions. Writing instruments viewed through injection-molded plaques containing 0.1, 0.5, 2, and 10 wt % of DMDBS (top) and measured values for haze (▴) and clarity (■) as a function of the DMDBS content (bottom). Reprinted with permission from ref. (32). Copyright 2003 American Chemical Society.


Figure 2. Crystallization (top) and melting (bottom) temperature/composition diagrams of the binary system i-PP/DMDBS. In the diagrams the symbols refer to experimental data obtained by (●) DSC, (closed star/open star) rheology, and (Δ) optical microscopy. The denotation D refers to DMDBS, P to i-PP, L to liquid, and S to solid. Reprinted with permission from ref. (32). Copyright 2003 American Chemical Society.


Figure 3. Proposed schematic, monotectic phase diagram of the binary system i-PP/DMDBS. Indicated are four relevant composition ranges I, II, III, and IV that divide the phase behavior below the eutectic point (I), along the lower liquidus (II), along the miscibility gap (III), and above the monotectic point (IV) and inserted are sketches and actual optical micrographs (crossed nicols) of the various states of matter of representative mixtures of compositions in those ranges. Adapted with permission from ref. (32). Copyright 2003 American Chemical Society.


Figure 4. Temperature/composition diagrams for the (pseudo-)binary system i-PP/1 obtained in cooling (top) and heating (bottom) experiments. Symbols refer to data for different transitions: crystallization and dissolution/melting (▵, ▴) and solid-state transition of 1 (●), crystallization or melting of the polymer and eutectic (▪) and clearing point (?), respectively. Open symbols denote experimental data obtained from optical microscopy and solid symbols refer data obtained by thermal analysis. The denotation L refers to liquid and S to solid; subscripts ‘a1’ and ‘a2’ refer to the two solid-state structures of additive 1, and ‘p’ to i-PP. Reprinted with permission from ref. (33). Copyright 2006 Elsevier.


Figure 5. Top: optical micrograph displaying liquid–liquid phase separation at 270 °C in a mixture containing 25 wt% of 1 in i-PP. Bottom: photomicrograph, taken between crossed polarizers at 80 °C, of the solid-phase structure of a 50/50 i-PP/1 wt%-mixture. The structures in the upper left corner crystallized from a droplet rich in 1. Reprinted with permission from ref. (33). Copyright 2006 Elsevier.


Figure 6. Top: optical micrograph, taken in reflected light, of a sample produced with a ‘diffusion–screening’ method by placing powder of 1 in the center of a compression-molded film of i-PP and allowing the additive to radially diffuse at 220 °C, after which the sample was cooled down to room temperature. The clear ring is indicative of the clarifying ability of compound 1. Bottom: corresponding optical micrograph taken in transmittance with crossed polarizers and a λ/4 plate. A schematic of the i-PP/1 monotectic phase diagram is drawn onto the micrograph to approximate the different characteristic optical regimes and the corresponding composition ranges. Reprinted with permission from ref. (33). Copyright 2006 Elsevier.


Further evidence of the influence of the phase behavior on the morphology and clarifying ability of SMOGs was reported by Kristiansen et al. for N,N’,N”tris-isopentyl-1,3,5-benzene-tricarboxamide (1) in i-PP (33). Qualitatively similar phase diagrams to the DMDBS/i-PP system were obtained and are shown in Figure 4. In the 1/i-PP system measurements were made over a much larger wt% 1 range compared the DMDBS/i-PP system. Quantitative measurement of the clarity and haze of the 1/i-PP samples vs. wt% 1 showed similar behavior to Figure 1. The reported optimum composition range and values for high clarity (98%) and low haze (ca. 27%) in injection molded plaques was 0.25 – 1 wt% 1, corresponding to the region where 1 solidifies directly from the liquid on cooling through the lower liquidus line. The haze and clarity display an upturn and downturn, respectively, in the composition region where the lower liquidus approaches the monotectic temperature at ca. 2 wt% 1. Figure 5 shows optical micrographs of 25 wt% 1 in i-PP in the liquid-liquid phase separated and solid states, where a 1-rich phase resulting from the crystallization in a phase separated droplet is clearly observed. Figure 6 shows a compression molded sample where 1 was placed in the center of the film and allowed to radially diffuse producing a composition gradient from high to low 1 concentration from the center of the film. The variation in the optical clarity of the film clearly shows that there is an optimal concentration range for 1 to act as a clarifying agent as schematically shown by the phase diagram overlaid on the micrograph under crossed polarizers in the bottom half of the figure. It should be noted that while the phase behavior is the key component in the function of clarifying agents in semi-crystalline polymers, other criteria must be met at the same time. In addition to establishing a region where the clarifying agent and semi-crystalline polymer sequentially crystalize from the homogeneous melt, the clarifying agent also must be able to crystallize into three dimensional fibrillar networks and act as an epitaxial nucleating agent for the surrounding polymer (44, 45). Given the many criteria that must be satisfied it is therefore crucial to examine the phase behavior of complex SMOG/semi-crystalline polymer systems which are instrumental in further developing high performance clarifying agents (46). While there has clearly been success in the design of clarifying agents in modifying the optical properties of i-PP, this research field is not complete as it is only one of many semi-crystalline polymers. For example, clarifying agents for polyethylene have recently been reported (47, 48). This field has a potentially broad future due to growing interest in other semi-crystalline polymers, such as bio-based polylactide (49), and conjugated polymers for organic electronics (50).

Shape Memory Polymer/Small Molecule Blends Shape memory polymers (SMPs) are a class of polymers where their elastic recovery can be turned on and off by the application of an external stimulus (51). This is accomplished by preventing the elastic retraction of a polymer network through vitrification, crystallization, or additional, reversible crosslinking (52). While many SMPs are composed of a single polymer, such as a polyurethane (53), there has been recent interest in decoupling the elastic network, providing shape recovery, and the reversible network, providing shape fixity, through blending 254 Horkay et al.; Gels and Other Soft Amorphous Solids ACS Symposium Series; American Chemical Society: Washington, DC, 2018.

elastomers and small molecules (54). While this concept is analogous to SMOG/ solvent organogels there are a few key differences. First, the medium being gelled is not a liquid, but a viscoelastic solid, which produces the shape memory effect. Second, a much higher loading of the SMOG is typically used compared to SMOG/ liquid organogels. In SMOG/liquid organogels the fluid is immobilized above the percolation threshold of the SMOG network (i.e. at the minimum gelation concentration). In contrast, the SMOG network in an SMP must not only form a percolating solid network, but be able to resist the elastic contractive forces of the surrounding elastomer network. While there are numerous examples of polymer/small molecule SMPs (55–63), the systematic study of the mechanical properties of the SMOG/polymer network and the shape memory properties has only recently been reported by Pantoja et al. using fatty acid swollen, natural rubber bands (35). An example of the excellent shape memory property of fatty acid swollen natural rubber is shown in Figure 7. The sample was deformed and fixed to ca. 400% strain by heating the sample above the melting point of stearic acid; uniaxially stretching the sample and then cooling it to room temperature under load, allowing the stearic acid to crystallize into a ‘house of cards’ network that restricts the movement of the natural rubber chains (64); and recovered to the original shape by heating the unloaded sample above the melting point of stearic acid. The figures of merit characterizing the shape memory polymer are the fixity (F) and recovery (R). These are in turn calculated from the uniaxial strains in the sample during the shape memory cycle: the initial strain prior to stretching (εi), the applied strain during deformation (εa), the fixed strain after cooling and unloading the sample (εf), and the residual strain after heating and recovering the unloaded sample (εr). These strains are given by,

where lx is the length of the sample and the subscript (li, la, lf, or lr) is the same subscript as the particular strain (εx). From these strains, fixity (F) and recovery (R) are calculated as,

Figure 8 shows the fixity and recovery for a 2.94N load for natural rubber bands swollen with lauric (LA), myristi c (MA), palmitic (PA) and stearic acid (SA). An optimum loading is seen for high fixity and recovery around 50 wt% fatty acid. An interesting question from these results is, why do the LA swollen samples behave differently from the other fatty acids, which show very similar behavior? Specifically, in Figure 8 while the recovery and fixity overlap for the MA, PA, and SA samples, the LA samples shows significantly lower values than these three acids at less than 50 wt% fatty 255 Horkay et al.; Gels and Other Soft Amorphous Solids ACS Symposium Series; American Chemical Society: Washington, DC, 2018.

acid. The fixity is dependent on the modulus and the yield strength of the fatty acid network, which should both scale with the wt% acid in the elastomer, similar to other cellular solids (65). Ultimately a high modulus of the fatty acid network is needed to reach ca. 100% fixity as any deformation of the solid acid network will allow the retraction and recovery of the elastic polymer network. Figure 9 shows the storage modulus of the fatty acid swollen rubber measured by constant frequency strain sweeps. Power law behavior is observed with a distinct change in the power-law exponent at intermediate fatty acid concentrations. This change in slope is assigned as the mechanical percolation threshold and is plotted as dashed vertical lines in Figure 8. A correlation between the mechanical percolation and the upturn in the fixity vs. wt% fatty acid in Figure 9 demonstrates how the mechanical properties of the solid fatty acid network drive the fixation of the deformed elastomer.

Figure 7. Shape memory cycle of natural rubber band swollen with 59% stearic acid strained to ca. 400% at 72 °C and fixed at room temperature with a fixity of 98% and a recovery of 98%.

Figure 8. (a) Fixity and (b) recovery vs. weight percent acid for 2.94 N applied load. Vertical lines correspond to fatty acid network percolation threshold from Figure 9. Adapted with permission from ref. (35). Copyright 2018 John Wiley & Sons, Inc. 256 Horkay et al.; Gels and Other Soft Amorphous Solids ACS Symposium Series; American Chemical Society: Washington, DC, 2018.

Figure 9. Fatty acid network modulus vs. weight percent fatty acid. Horizontal dashed line represents the modulus of neat rubber. Reprinted with permission from ref. (35). Copyright 2018 John Wiley & Sons, Inc.

Similar to the fixity data, the modulus data also show that LA is different from the other three fatty acids, with a lower modulus at all wt% fatty acid, resulting in poor fixity. While this demonstrates the direct connection between mechanical properties of the fatty acid solid network and the shape memory properties, it does not explain why LA has a lower modulus than the other fatty acids at equivalent loading. Figure 10 shows the phase diagram of the four fatty acids in high molecular weight polyisoprene. It is clear that LA is more soluble at low temperature than the other three acids. To estimate the solubility limit at room temperature the liquidus line was fit to the Flory-diluent model,

where Tm is the melting temperature of the fatty acid vs. the volume fraction of fatty acid, φ2, A quantifies the Flory-Huggins interaction parameter (χ = A/T), and ΔHfo and Tmo are the standard enthalpy of formation and melting temperature, respectively, of the pure fatty acid, and R is the universal gas constant. Using the lever rule, the wt% of the solid fatty acid was calculated as a function of overall wt% fatty acid in the swollen natural rubber. From this calculation, the modulus data in Figure 9 were replotted as E’ vs. wt% solid acid in Figure 11. This adjustment shifts the LA data closer to the other fatty acids. There is likely also a vertical shift in the data due to the soluble lauric acid plasticizing the natural rubber and softening the network, shifting the curves down with respect to the other fatty acids. However, this effect is difficult to quantitatively calculate. 257 Horkay et al.; Gels and Other Soft Amorphous Solids ACS Symposium Series; American Chemical Society: Washington, DC, 2018.

Figure 10. Experimental (circles) and modeled (lines) fatty acid-polyisoprene phase diagram. Reprinted with permission from ref. (35). Copyright 2018 John Wiley & Sons, Inc.

Figure 11. Fatty acid network modulus vs. weight percent solid fatty acid. Horizontal dashed line represents the modulus of neat rubber. Reprinted with permission from ref. (35). Copyright 2018 John Wiley & Sons, Inc. This work shows that the measurement of the fatty acid/polymer phase diagram was crucial to elucidate the variation in the properties of different fatty acid swollen, natural rubber, shape memory polymers. More generally, these results demonstrate that the efficiency of an SMOG to form solid networks in elastomers for shape memory is directly related to their solubility limit, even though the SMOG is used at significantly higher concentrations to achieve good shape memory. For example, it would be interesting to compare the efficiency of fatty acids with paraffin waxes, which also form similar platelet crystal structures, 258 Horkay et al.; Gels and Other Soft Amorphous Solids ACS Symposium Series; American Chemical Society: Washington, DC, 2018.

but would have a different room temperature solubility, with the waxes being more soluble in polyolefins based on their solubility parameters (58, 66). Another important question for future research is, how does the efficiency of structure formation and mechanical percolation of different SMOGs ultimately affect shape memory? For example, Figure 12 shows the phase diagram of R-12hydroxystearic acid (12-HSA) and stearic acid (SA) in n-dodecane. In addition to having lower solubility in the alkane, 12-HSA is a more efficient organogelator where the difference between the minimimum gelation concentration (12-HSA: 0.019 vol%, SA: 2.1 vol%) and the solubility limit (12-HAS: ca. 0 vol%, SA: 0.2 vol%) are smaller for 12-HSA compared to stearic acid. This implies that 12HSA is able to achieve mechanical percolation more efficiently, likely due to two factors: first, its fibrillar structure, which fills space more easily than platelets and second, differences in the kinetics of crystallization due to the larger undercooling achievable in 12-HSA from the distinct low concentration plateau compared to the more parabolic shape of the stearic acid liquidus line. Assuming similar power law exponents for different SMOGs, achieving mechanical percolation at lower concentration would allow the critical modulus needed for good shape memory to be achieved at lower concentration. Unfortunately, 12-HSA is unable to swell natural rubber, preventing the direct comparison of these two materials, leaving the answers to these questions to future research.

Figure 12. Cloud-point curves of R-12-hydroxystearic acid (12HSA) and stearic acid (SA).

Conclusions This chapter has shown the measurement of phase diagrams is exteremly useful in understanding the structure-property relationships of SMOG/polymer gels. While the measurement of full phase diagrams can be an intensive process it is necessary to interpret complex systems, such as the semi-crystalline and 259 Horkay et al.; Gels and Other Soft Amorphous Solids ACS Symposium Series; American Chemical Society: Washington, DC, 2018.

crosslinked polymer networks shown as examples. In general phase diagrams serve as an additional tool to aid in the study of gelation by crystalline small molecules, a complex thermodynamic and kinetic process.

References 1. 2. 3.

4. 5.

6.

7.

8.

9.

10. 11. 12. 13. 14.

15.

Molecular Gels: Materials with Self-Assembled Fibrillar Networks; Weiss, R. G., Terech, P., Eds.; Springer: Dordrecht, Netherlands, 2006; pp 1−13. Liu, X. Y.; Sawant, P. D. Formation kinetics of fractal nanofiber networks in organogels. Appl. Phys. Lett. 2001, 79, 3518–3520. Raghavan, S. R. Distinct Character of Surfactant Gels: A Smooth Progression from Micelles to Fibrillar Networks. Langmuir 2009, 25, 8382–8385. Sangeetha, N. M.; Maitra, U. Supramolecular gels: Functions and uses. Chem. Soc. Rev. 2005, 34, 821–836. Weiss, R. G. The Past, Present, and Future of Molecular Gels. What Is the Status of the Field, and Where Is It Going? J. Am. Chem. Soc. 2014, 136, 7519–7530. Morales, M. E.; Gallardo, V.; Clares, B.; Garcia, M. B.; Ruiz, M. A. Study and description of hydrogels and organogels as vehicles for cosmetic active ingredients. Int. J. Cosmetic Sci. 2009, 60, 627–636. Friggeri, A.; van Bommel, K. J. C.; de Jong, M.; van der Pol, C.; van Esch, J. A new class of gelators: Exploring the compatibility in cosmetics. Cosmet. Toiletries 2005, 120, 67–76. Schaink, H. M.; van Malssen, K. F.; Morgado-Alves, S.; Kalnin, D.; van der Linden, E. Crystal network for edible oil organogels: Possibilities and limitations of the fatty acid and fatty alcohol systems. Food Res. Int. 2007, 40, 1185–1193. Hughes, N. E.; Marangoni, A. G.; Wright, A. J.; Rogers, M. A.; Rush, J. W. E. Potential food applications of edible oil organogels. Trends Food Sci. Technol. 2009, 20, 470–480. Anand, B.; Pisal, S. S.; Paradkar, A. R.; Mahadik, K. R. Applications of organogels in pharmaceuticals. J Sci Ind Res 2001, 60, 311–318. Murdan, S. Organogels in drug delivery. Expert Opin. Drug Delivery 2005, 2, 489–505. Vintiloiu, A.; Leroux, J.-C. Organogels and their use in drug delivery - A review. J. Controlled Release 2008, 125, 179–192. Babu, S. S.; Prasanthkumar, S.; Ajayaghosh, A. Self-Assembled Gelators for Organic Electronics. Angew. Chem., Int. Ed. 2012, 51, 1766–1776. Bhattacharya, S.; Krishnan-Ghosh, Y. First report of phase selective gelation of oil from oil/water mixtures. Possible implications toward containing oil spills. Chem. Commun. 2001, 185–186. Jadhav, S.; Vemula, P. K.; Kumar, R.; Raghavan, R. S.; John, G. Sugar-Derived Phase-Selective Molecular Gelators as Model Solidifiers for Oil Spills. Angew. Chem. 2010, 122, 7861–7864. 260 Horkay et al.; Gels and Other Soft Amorphous Solids ACS Symposium Series; American Chemical Society: Washington, DC, 2018.

16. Beginn, U.; Moeller, M.; Keinath, S. Organogels as a Tool to Generate Anion: Cation Selective Membranes. Chem. Eng. Commun. 2005, 192, 1116–1128. 17. Fu, X.; Yang, Y.; Wang, N.; Wang, H.; Yang, Y. A novel chiral separation material: polymerized organogel formed by chiral gelators for the separation of D- and L-phenylalanine. J. Mol. Recog. 2007, 20, 238–244. 18. Simmons, B.; Liu, L.; John, V.; Taylor, C.; Schwartz, D.; McPherson, G.; Bose, A.; Agarwal, V.: Templating nanostructure through the self-assembly of surfactants. In Synthesis, Functionalization and Surface Treatment of Nanoparticles; Baraton, M.-I., Ed.; American Scientific Publishers: Valencia, CA, 2003; pp 51−65. 19. Llusar, M.; Sanchez, C. Inorganic and Hybrid Nanofibrous Materials Templated with Organogelators. Chem. Mater. 2008, 20, 782–820. 20. van Esch, J. H. We Can Design Molecular Gelators, But Do We Understand Them. Langmuir 2009, 25, 8392–8394. 21. Bonnet, J.; Suissa, G.; Raynal, M.; Bouteiller, L. Organogel formation rationalized by Hansen solubility parameters: dos and don’ts. Soft Matter 2014, 10, 3154–3160. 22. Zurcher, D. M.; McNeil, A. J. Tools for Identifying Gelator Scaffolds and Solvents. J. Org. Chem. 2015, 80, 2473–2478. 23. Segarra-Maset, M. D.; Nebot, V. J.; Miravet, J. F.; Escuder, B. Control of molecular gelation by chemical stimuli. Chem. Soc. Rev. 2013, 42, 7086–7098. 24. Liu, X. Y.; Sawant, P. D. Mechanism of the formation of self-organized microstructures in soft functional materials. Adv. Mater. 2002, 14, 421–426. 25. Lescanne, M.; Colin, A.; Mondain-Monval, O.; Fages, F.; Pozzo, J. L. Structural Aspects of the Gelation Process Observed with Low Molecular Mass Organogelators. Langmuir 2003, 19, 2013–2020. 26. Huang, X.; Raghavan, S. R.; Terech, P.; Weiss, R. G. Distinct kinetic pathways generate organogel networks with contrasting fractality and thixotropic properties. J. Am. Chem. Soc. 2006, 128, 15341–15352. 27. Huang, X.; Terech, P.; Raghavan, S. R.; Weiss, R. G. Kinetics of 5alpha -Cholestan-3beta -yl N-(2-Naphthyl)carbamate/n-Alkane Organogel Formation and Its Influence on the Fibrillar Networks. J. Am. Chem. Soc. 2005, 127, 4336–4344. 28. Beginn, U.; Keinath, S.; Moeller, M. New carbohydrate amphiphiles. Part 2. Gel formation and gel morphologies. Macromol. Chem. Phys. 1998, 199, 2379–2384. 29. Christ, E.; Blanc, C.; Al Ouahabi, A.; Maurin, D.; Le Parc, R.; Bantignies, J.L.; Guenet, J.-M.; Collin, D.; Mésini, P. J. Origin of Invariant Gel Melting Temperatures in the c–T Phase Diagram of an Organogel. Langmuir 2016, 32, 4975–4982. 30. Hirst, A. R.; Smith, D. K. Solvent Effects on Supramolecular Gel-Phase Materials: Two-Component Dendritic Gel. Langmuir 2004, 20, 10851–10857. 31. Van Esch, J.; Schoonbeek, F.; De Loos, M.; Kooijman, H.; Spek, A. L.; Kellogg, R. M.; Feringa, B. L. Cyclic bis-urea compounds as gelators for organic solvents. Chem.−Eur. J. 1999, 5, 937–950. 261 Horkay et al.; Gels and Other Soft Amorphous Solids ACS Symposium Series; American Chemical Society: Washington, DC, 2018.

32. Kristiansen, M.; Werner, M.; Tervoort, T.; Smith, P.; Blomenhofer, M.; Schmidt, H.-W. The binary system isotactic polypropylene/bis(3,4dimethylbenzylidene)sorbitol: phase behavior, nucleation, and optical properties. Macromolecules 2003, 36, 5150–5156. 33. Kristiansen, P. M.; Gress, A.; Smith, P.; Hanft, D.; Schmidt, H.-W. Phase behavior, nucleation and optical properties of the binary system isotactic polypropylene/N,N′,N″-tris-isopentyl-1,3,5-benzene-tricarboxamide. Polymer 2006, 47, 249–253. 34. Porter, D. A.; Easterling, K. E. Phase Transformation in Metals and Alloys; Chapman & Hall: New York, 1981; p 149. 35. Pantoja, M.; Lin, Z.; Cakmak, M.; Cavicchi, K. A. Structure-property relationships of fatty acid swollen, crosslinked natural rubber shape memory polymers. J. Polym. Sci., Part B: Polym. Phys. 2018, 56, 673–688. 36. Smith, T. L.; Masilamani, D.; Bui, L. K.; Brambilla, R.; Khanna, Y. P.; Gabriel, K. A. Acetals as nucleating agents for polypropylene. J. Appl. Polym. Sci. 1994, 52, 591–6. 37. Kobayashi, T.; Hashimoto, T. Development of self-assembling nucleators for highly transparent semi-crystalline polypropylene. Bull. Chem. Soc. Jpn. 2005, 78, 218–235. 38. Libster, D.; Aserin, A.; Garti, N. Advanced nucleating agents for polypropylene. Polym. Adv. Technol. 2007, 18, 685–695. 39. Blomenhofer, M.; Ganzleben, S.; Hanft, D.; Schmidt, H.-W.; Kristiansen, M.; Smith, P.; Stoll, K.; Maeder, D.; Hoffmann, K. “Designer” Nucleating Agents for Polypropylene. Macromolecules 2005, 38, 3688–3695. 40. Bernland, K.; Goossens, J. G. P.; Smith, P.; Tervoort, T. A. On clarification of haze in polypropylene. J. Polym. Sci., Part B: Polym. Phys. 2016, 54, 865–874. 41. Thierry, A.; Straupe, C.; Lotz, B.; Wittmann, J. C. Physical gelation: a path towards ‘ideal’ dispersion of additives in polymers. Polym. Commun. 1990, 31, 299–301. 42. Hoffmann, K.; Huber, G.; Mäder, D. Nucleating and clarifying agents for polyolefins. Macromol. Symp. 2001, 176, 83–92. 43. Garg, S.; Stein, R.; Su, T.; Tabar, R.; Misra, A.: Light scattering studies of nucleation of polypropylene. In Kinetics of Aggregation and Gelation; Elsevier: New York, 1984; pp 229−234. 44. Abraham, F.; Ganzleben, S.; Hanft, D.; Smith, P.; Schmidt, H.-W. Synthesis and Structure–Efficiency Relations of 1,3,5-Benzenetrisamides as Nucleating Agents and Clarifiers for Isotactic Poly(propylene). Macromol. Chem. Phys. 2010, 211, 171–181. 45. Smith, T. L.; Masilamani, D.; Bui, L. K.; Khanna, Y. P.; Bray, R. G.; Hammond, W. B.; Curran, S.; Belles, J. J., Jr.; Binder-Castelli, S. The Mechanism of Action of Sugar Acetals as Nucleating Agents for Polypropylene. Macromolecules 1994, 27, 3147–55. 46. Bernland, K.; Tervoort, T.; Smith, P. Phase behavior and optical- and mechanical properties of the binary system isotactic polypropylene and the 262 Horkay et al.; Gels and Other Soft Amorphous Solids ACS Symposium Series; American Chemical Society: Washington, DC, 2018.

47.

48.

49. 50.

51.

52. 53. 54. 55.

56. 57. 58. 59.

60. 61.

62.

63.

nucleating/clarifying agent 1,2,3-trideoxy-4,6:5,7-bis-O-[(4-propylphenyl) methylene]-nonitol. Polymer 2009, 50, 2460–2464. Hill, M. K.; Bensason, S.; Schmidt, H.-W.; Smith, P.; Aksel, S. Polyethylene compositions with improved optical properties. U.S. Patent Application 15/ 539,225, Publication No. US 2018/0022894 A1, 1/25/2018. Wang, L.; Santos, N.; Banks, A.; Huang, Y.; Hart, K.; Keaton, R.; He, Y.; Keene, E.; Hill, M. Clarification of linear low-density polyethylene using Bis-oxalamide compounds. Polym. Eng. Sci. 2018, 58, 142–149. Lunt, J. Large-scale production, properties and commercial applications of polylactic acid polymers. Polym. Degrad. Stab. 1998, 59, 145–152. Hildner, R.; Köhler, A.; Müller-Buschbaum, P.; Panzer, F.; Thelakkat, M. π-Conjugated Donor Polymers: Structure Formation and Morphology in Solution, Bulk and Photovoltaic Blends. Adv. Energy Mater. 2017, 7, 1700314n/a. Behl, M.; Zotzmann, J.; Lendlein, A.: Shape-Memory Polymers and Shape-Changing Polymers. In Shape-Memory Polymers; Lendlein, A., Ed.; Springer: Berlin, Heidelberg, 2010; pp 1−40. Lendlein, A.; Kelch, S. Shape-memory polymers. Angew. Chem., Int. Ed. 2002, 41, 2034–2057. Huang, W. M.; Yang, B.; Fu, Y. G.: Polyurethane Shape Memory Polymers; CRC Press: Boca Raton, FL, 2011; pp 31−50. Cavicchi, K. A. Shape Memory Polymers from Blends of Elastomers and Small Molecule Additives. Macromol. Symp. 2015, 358, 194–201. Weiss, R. A.; Izzo, E.; Mandelbaum, S. New Design of Shape Memory Polymers: Mixtures of an Elastomeric Ionomer and Low Molar Mass Fatty Acids and Their Salts. Macromolecules 2008, 41, 22978–2980. Meng, Q.; Hu, J. A review of shape memory polymer composites and blends. Composites Part A 2009, 40, 1661–1672. Dong, J.; Weiss, R. A. Shape Memory Behavior of Zinc Oleate-Filled Elastomeric Ionomers. Macromolecules 2011, 44, 8871–8879. Song, S.; Feng, J.; Wu, P. A New Strategy to Prepare Polymer-based Shape Memory Elastomers. Macromol. Rapid Commun. 2011, 32, 1569–1575. Zhang, Q.; Song, S.; Feng, J.; Wu, P. A new strategy to prepare polymer composites with versatile shape memory properties. J. Mater. Chem. 2012, 22, 24776–24782. Shi, Y.; Yoonessi, M.; Weiss, R. A. High Temperature Shape Memory Polymers. Macromolecules 2013, 46, 4160–4167. Brostowitz, N. R.; Weiss, R. A.; Cavicchi, K. A. Facile Fabrication of a Shape Memory Polymer by Swelling Cross-Linked Natural Rubber with Stearic Acid. ACS Macro Lett. 2014, 3, 374–377. Du, J.; Liu, D.; Zhang, Z.; Yao, X.; Wan, D.; Pu, H.; Lu, Z. Dual-responsive triple-shape memory polyolefin elastomer/stearic acid composite. Polymer 2017, 126, 206–210. Mineart, K. P.; Tallury, S. S.; Li, T.; Lee, B.; Spontak, R. J. Phase-Change Thermoplastic Elastomer Blends for Tunable Shape Memory by Physical Design. Ind. Eng. Chem. Res. 2016, 55, 12590–12597. 263 Horkay et al.; Gels and Other Soft Amorphous Solids ACS Symposium Series; American Chemical Society: Washington, DC, 2018.

64. Schaink, H. M.; van Malssen, K. F. Shear Modulus of Sintered ‘House of Cards’-Like Assemblies of Crystals. Langmuir 2007, 23, 12682–12686. 65. Gibson, L. J.; Ashby, M. F. Cellular solids: structure and properties; Cambridge University Press: New York, 1997; pp 175−231. 66. Barton, A. F. M. Solubility parameters. Chem. Rev. 1975, 75, 731–753.


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