Article pubs.acs.org/jced
Porosity and Ring Formation in Conjugated Microporous Polymers Lauren J. Abbott and Coray M. Colina* Department of Materials Science and Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, United States S Supporting Information *
ABSTRACT: Pyrene-based conjugated microporous polymers (CMPs) have been shown to exhibit significant microporosity and strong luminescence, but their structures are not well understood due to their insolubility and amorphous nature. Here, a series of pyrene-based CMPs with varying monomer compositions is studied using molecular simulations. The results are in good agreement with available experimental BET surface areas and powder X-ray diffraction data. As the monomer composition is adjusted to increase the degree of cross-linking, greater porosity is formed. Additionally, with high cross-linking degrees, the formation of 3-, 4-, 5-, and 6-monomer rings are found to be more prevalent. The increase in strained rings within the network structures correlates with shifts in optical spectra due to the increased conjugation. Together with experimental and other computational results, the simulations here enable a better understanding of the structure−property relationships in pyrene-based CMPs.
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INTRODUCTION Conjugated microporous polymers (CMPs)1,2 are a unique class of materials that combine the functional properties of conjugated polymers and microporous polymers. On the one hand, conjugated polymers possess good electrical properties due to the extended π conjugation and are, therefore, of interest for applications including solar cells,3 chemical sensors,4 and light-emitting diodes.5 On the other hand, microporous polymers contain permanent porosity with pore sizes smaller than 2 nm, which are effective for applications such as gas storage, separations, and heterogeneous catalysis.6−9 The properties of CMPs are tunable by varying monomer structures, monomer ratios, and reaction conditions, as well as functionalization and postsynthesis modification, such that they can be tailored to suit a wide variety of applications.10−18 In particular, several studies have found a link between the porosity of systems with their optical properties. Upon increasing the proportion of bi- to tetrafunctional monomers in spirobisfluorene-based CMPs, Schmidt et al.19 measured lower surface areas and a shift in the fluorescence bands to shorter wavelengths. For tetraphenylethene-based CMPs, Xu et al.20 showed that, when more cross-links were formed, the porosity of the networks increased, while the wavelengths of the absorption and fluorescence bands also increased. Lastly, Zwijnenburg et al.21 found an upward shift in the wavelength of the fluorescence bands in pyrene-based CMPs that corresponded also to the order of porosity. In these instances, it has been suggested that an increase in the rigidity of the structure is responsible for the greater porosity, as well as limiting the rotation of the benzene rings to maintain greater conjugation. Although trends have between observed between porosity and optical properties in CMPs, a better understanding of these © XXXX American Chemical Society
structure−property relationships is still needed. Unfortunately, experimental characterization of their structures is not straightforward due to their insolubility and amorphous nature, so recent research has looked to molecular simulations in order to achieve additional insight. Developing realistic and accurate models of amorphous networks is a nontrivial task given their complex structures and, as such, has been the subject of numerous publications.22−27 One approach adopted by Cooper and co-workers for simulating CMPs has been to analyze model “clusters” or “fragments”. For the series of poly(aryleneethynylene) networks, for example, Jiang et al.10,11 employed model clusters to study the structural geometry and flexibility, as well as the porosity. However, as the authors noted, these fragments did not likely capture the entanglements and concatenation of the extended network, resulting in overestimated pore volumes. In more recent work, Zwijnenburg et al.21 presented ab initio calculations of model ring fragements of pyrene-based CMPs complementary to optical absorption and fluorescence spectra. They were able to identify a compelling relationship between the shifts in the optical spectra and ring-induced strain likely formed in the networks. Although these model studies provide some important initial insight, additional simulations of bulk systems would enable a more complete understanding of the structures of these types of CMPs. Special Issue: Modeling and Simulation of Real Systems Received: March 10, 2014 Accepted: June 19, 2014
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dx.doi.org/10.1021/je5002329 | J. Chem. Eng. Data XXXX, XXX, XXX−XXX
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In this work, we utilize the recently developed Polymatic simulated polymerization algorithm27 to generate bulk models of pyrene-based CMPs proposed by Cooper and co-workers,28,29 which are synthesized from monomers 1,3,6,8tetrabromopyrene, A4, and 1,3-dibromo-7-tert-butylpyrene, B2, as illustrated in Figure 1. The initial experimental system
distance of 6 Å. Cycles of polymerization steps were carried out inbetween molecular dynamics simulations in the NVT ensemble with T = 300 K, which kept the density of the system constant throughout the simulated polymerization. The polymerization cycles were carried out until no more bonds could be made within the 6 Å cutoff after at least 500 ps of molecular dynamics. After an initial polymerized structure was achieved, the system was equilibrated using a 21-step molecular dynamics scheme27,35 with Tmax = 1000 K, Pmax = 5 × 104 bar, Tfinal = 300 K, and Pfinal = 1 bar. This scheme incorporates simulations at high temperatures and pressures to effectively equilibrate the glassy structures to accurate densities in ∼1.5 ns. It has been shown to produce structures with accurate and consistent densities in structure generation of several other microporous materials.25,37−43 For each system, the results are given as the mean and standard deviation from five independent boxes obtained using the described methodology. The equilibrated systems had final box lengths of L ≈ (39−45) Å. All energy minimizations and molecular dynamics simulations during the polymerization and equilibration were performed using the LAMMPS simulation package44 with a time step of 1 fs. The temperature and pressure were kept constant using the Nosé−Hoover thermostat and barostat, each with a relaxation time of 100 fs. In accordance with previous work,43 the Lennard-Jones cutoff was shortened to 5 Å during the polymerization to provide better dispersion between the molecules to more accurately mimic the solvated state of the system. The cutoff was extended to 15 Å during the equilibration to provide the correct interactions between the polymer segments. Long range electrostatics were accounted for using the particle−particle particle−mesh (PPPM) method with an rms accuracy of 10−4.
Figure 1. Chemical structure of A4−B2 CMPs, containing the tetrafunctional monomer 1,3,6,8-tetrabromopyrene, A4, and the bifunctional monomer 1,3-dibromo-7-tert-butylpyrene, B2.
presented by Jiang et al.,28 YPy, which was composed entirely of the A4 monomer, had large porosity with a BET surface area of 1508 m2·g−1, as well as strong fluorescence. Later, Cheng et al.29 introduced B2 monomers in order to improve the solubility of the networks, such that a broader range of processing options could be exploited. Using a 1:2 ratio of A4:B2 monomers, they were successfully able to create a soluble hyperbranched CMP, SCMP1; however, the porosity in this system was significant reduced, resulting in a smaller BET surface area of 505 m2·g−1. Here, we utilize molecular simulations to extend the study of these pyrene-based CMPs in the bulk state for A4:B2 monomer ratios of 1:0, 3:1, 1:1, 1:3, and 0:1 (corresponding to A4 monomer fractions of fA = 1.0, 0.75, 0.5, 0.25, and 0.0, respectively) in order to gain a better understanding of their structure−property relationships. In particular, we focus on the influence of the monomer composition on porosity and the presence of rings, which are believed to affect the optical properties.
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RESULTS AND DISCUSSION The simulated polymerization approach utilized here provides an effective means for obtaining statistical copolymers of the CMPs with a random ordering of the A4 and B2 units in the final structures to provide a realistic representation of the true systems. Just as experimental synthesis conditions (e.g., solvent, monomer concentration, temperature, catalyst, etc.) have a large influence on the network structure and properties, the parameters of the simulated polymerization are also important. Previous work with hyper-cross-linked polymers,25,43 for instance, has shown that the porosity of the final equilibrated system is heavily dependent on the density of the system during the simulated polymerization and cross-linking. In order to obtain realistic models of the CMPs presented here, the 1:0 A4:B2 network was polymerized at densities of ρpolym = 0.5, 0.6, 0.7, 0.8, and 0.9 g·cm−3 for comparison with experimental data. Note that these densities refer to the structures during the simulated polymerization and cross-linking and not the final densities achieved after the equilibration was performed. The properties of the final polymerized structures, including the densities, are given in Supporting Information Table S2. For comparison with the experimental data, the equilibrated samples were characterized by surface areas, as, which give an indication as to the extent of microporosity within the material. Although these are usually calculated experimentally from nitrogen adsorption isotherms using BET theory,45 it is possible to obtain a more direct geometric measure from the simulations by “rolling” a nitrogen-sized probe molecule across the surface of the atoms.46 However, because geometric and BET surface
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METHODS The pyrene-based CMPs were described using a united atom model with bonded terms from the polymer consistent force field (PCFF)30 and Lennard-Jones parameters from the transferable potentials for phase equilibria (TraPPE).31−33 Electrostatic potentials were calculated for the two repeat units, A4 and B2 (Figure 1), in Gaussian 0334 at the HF/6-31G* level of theory, from which discrete partial charges were fitted. During the calculations, the bromine atoms were replaced with methyl groups to provide the proper environment of the polymerized structure, following the procedures as discussed in previous work.27,35 An explicit definition of the monomers, including the atom types and partial charges for each atom are provided in the Supporting Information. Bulk representations of the CMPs were obtained using the Polymatic algorithm.27,36 By this approach, a periodic box of the A4 and B2 repeat units in the desired ratio (200 monomers total) were constructed at initial densities ranging from 0.5 to 0.9 g·cm−3. Polymerization steps were performed between reactive atoms on neighboring repeat units within a cutoff B
dx.doi.org/10.1021/je5002329 | J. Chem. Eng. Data XXXX, XXX, XXX−XXX
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areas have been shown to disagree in some amorphous, microporous materials,39,38 simulated BET surface areas can also be obtained from simulated nitrogen isotherms for a more direct comparison with the experimental results. Here, we report both the geometric and BET surface areas, ageom and s aBET s , from the simulations for a complete description of the models and adequate comparison with experiments. Further details of the surface area and adsorption calculations from the simulations are given in the Supporting Information. Figure 2
Figure 3. Average structure factors for the 1:0 A4−B2 CMPs varying the density of the system during the simulated polymerization.
simulations in closest agreement with the experimental data were those polymerized at 0.6 g·cm−3. In an X-ray scattering study of polymers of intrinsic microporosity,49 the strength of the low q scattering in this region was seen to increase with the microporosity. Likewise, for the CMPs here, the trend in the low q intensity was directly related to the surface areas and pore sizes (Supporting Information Figure S4). Overall, based on the comparisons with the experimental BET surface areas and PXRD data, the networks polymerized at a density of 0.6 g· cm−3 are chosen here as the best representation of the experimental system. With validation of the simulation models for the 1:0 network ( fA = 1.0), we extended the simulations for A4:B2 monomer ratios of 3:1, 1:1, 1:3, and 0:1 (corresponding to A4 monomer fractions of fA = 0.75, 0.5, 0.25, and 0.0, respectively) to determine the influence of the monomer composition on the porosity. Each system was generated at a density of 0.6 g·cm−3 during the simulated polymerization, based on the results of the 1:0 networks above. The properties of these systems, including the densities and surface areas, are given in Supporting Information Table S3. In Figure 4, the geometric and BET
Figure 2. Average geometric and BET surface areas for the 1:0 A4−B2 CMPs as a function of the density of the system during the simulated polymerization.
plots the simulated geometric and BET surface areas as a function of the density during the polymerization, with the experimental28 BET surface area (1508 m2·g−1) marked by the horizontal dashed line. A decreasing trend in the surface areas was observed as the polymerization density increased because the chains were locked closer together by the extensive crosslinking at the higher density, consistent with previous results for hyper-cross-linked polymers.42 The best agreement with the experimental value was observed for the systems polymerized at 0.6 g·cm−3 (aBET = 1399 m2·g−1). It is interesting to note that s although the BET surface areas were significantly larger than the geometric values in the less porous systems, as found for similar materials,39,38 better agreement was observed between the values for the more porous systems. Additional structural characterization of the simulations was provided by structure factors, which are comparable to experimental X-ray scattering or diffraction data,47 as has been demonstrated for other amorphous, microporous materials in previous work.37,48 The structure factors, S(q), relate to the probability of finding two atoms a certain distance d apart (where q = 2π/d) and, thus, can provide insight into the packing behavior of the polymer segments. Further details of these calculations are given in the Supporting Information. The structure factors from the simulations are plotted along with the experimental powder X-ray diffraction (PXRD) data28 in Figure 3. The structure factors of the simulations at different densities were very similar at high q (>1.0 Å−1), but deviated substantially in intensity below this point. In all cases, the simulations deviated slightly from the PXRD data around 1.1 to 1.6 Å−1 (4.0 to 5.7 Å), which likely indicates that some of the short-range interactions between chain segments are slightly too weak. The shoulder in the PXRD data near 0.8 to 0.9 Å−1 (∼7 to 8 Å) is present in all simulated structure factors, although the positions and intensities vary some. At low q (
