Identifying Promising Zeolite Frameworks for ... - ACS Publications

Identifying Promising Zeolite Frameworks for Separation Applications: A Building-Block-Based Approach. Michael Fischer ... *E-mail: [email protected]...
0 downloads 0 Views 3MB Size
Article pubs.acs.org/JPCC

Identifying Promising Zeolite Frameworks for Separation Applications: A Building-Block-Based Approach Michael Fischer and Robert G. Bell* Department of Chemistry, University College London, 20 Gordon Street, London WC1H 0AJ, United Kingdom S Supporting Information *

ABSTRACT: The concept of natural tilings provides a unique definition of the building blocks that constitute zeolite frameworks. Knowledge of the natural tiling permits the identification of different frameworks with similar structural properties. On the basis of results from earlier work, which showed a close association between energetically preferred carbon dioxide adsorption sites and certain structural building units, we propose a list of criteria to identify natural tiles that could lead to a high affinity of a zeolite framework toward CO2. After identifying all recognized framework types that incorporate tiles with these features, we perform grand-canonical Monte Carlo simulations of CO2 adsorption and CO2/N2 mixture adsorption in these structures. Out of a set of 37 frameworks, we identify eight systems that exhibit relatively high CO2/ N2 adsorption selectivities and CO2 working capacities. An inspection of the natural tilings of these systems reveals that they contain a relatively limited number of natural tiles, most of which occur in several of the eight systems. A subsequent analysis of the CO2 adsorption sites shows that identical tiles usually afford adsorption sites with very similar geometries and adsorption energies, highlighting the connection between the presence of certain tiles and the material’s affinity for carbon dioxide. While the results are not directly transferable to real-world applications, this study demonstrates that an analysis of the natural tiling permits the judicious choice of candidate topologies that are particularly promising for a given task, provided that some initial information on the relationship between the structural features and the property in question is available. Similar approaches can be imagined for various applications in adsorption and catalysis.



INTRODUCTION Various classification schemes have been proposed to rationalize the topology of zeolites by deconstructing the framework into smaller building units. While the primary building unit of zeolites is the TO4 tetrahedron, classifications based on larger building units can provide information about the pore topology and permit the identification of structurally related systems (e.g., two zeolites that contain the same type of cage). The structure database of the International Zeolite Association (IZA)1 includes three different types of classification for each recognized zeolite framework, namely, the secondary building units (SBUs), the composite building units (CBUs), and the natural tiling. SBUs correspond to fragments of up to 16 T atoms from which the whole framework can be generated. CBUs are more complex units, such as double six-rings or double-crankshaft chains, defined in a more intuitive manner. While both concepts have their merits, there are also some important disadvantages (see ref 2 for a more exhaustive discussion). First, the assignment of the building units is not generally unambiguous. Second, the description of the framework in terms of SBUs or CBUs does not necessarily provide useful information about the presence of certain types of pores and about their accessibility. In contrast to this, mathematical tiling theory presents a rigorous approach to enumerate zeolitic frameworks systematically.3 We have © 2013 American Chemical Society

previously generated hypothetical zeolite frameworks from polyhedral tilings of three-dimensional space, whose stability was then predicted using computational chemistry methods.4,5 Furthermore, from a geometric analysis of the tiles, we showed how the thermodynamic viability of a particular framework may be related to its topology.6 In a tiling, the underlying net of a zeolite framework type is represented as a space-filling assembly of polyhedra, the tiles. The edges and vertices of the tiles correspond to those of the net.7 In principle, different tiling schemes could be chosen to describe a given net. Therefore, a set of rules was developed by Blatov and co-workers that permits an unambiguous decomposition into units that are referred to as natural tiles.8 The natural tilings of 194 zeolite frameworks were reported in 2010 by Anurova et al.,2 and complete information for a total of 201 zeolite frameworks is currently available from the IZA database.1 As discussed in detail in ref 2, the concept of natural tilings has various advantages, and we summarize those that are most relevant to the present study: (1) The natural tiling gives a complete description of the underlying net. (2) The natural tiling is unambiguous. (3) The tiles correspond to cavities, cages, or Received: June 4, 2013 Revised: July 17, 2013 Published: July 18, 2013 17099

dx.doi.org/10.1021/jp405507y | J. Phys. Chem. C 2013, 117, 17099−17110

The Journal of Physical Chemistry C

Article

finite portions of channels. (4) All windows present in the structure are revealed as faces of the tiles. Therefore, this concept can be easily employed to identify structural similarities of different frameworks. As we attempt to demonstrate in this publication, knowledge of such similarities can be very useful when searching for topologies with promising properties for a certain application. In other fields, the concept has been exploited to rationalize aluminophosphate frameworks and natural zeolites in terms of packing units, structural units that are closely related to natural tiles.9,10 It is assumed that these packing units correspond to precursor units that occur during zeolite formation. Recently, zeolites and other microporous materials, such as metal−organic frameworks (MOFs), have received much attention as potential adsorbents for the selective removal of carbon dioxide from flue gases, natural gas, and syngas.11−13 It has been proposed that pressure-swing adsorption (PSA) or vacuum-swing adsorption (VSA) using solid adsorbents could, at least for some industries, be a more cost- and energy-effective alternative to absorption in amines, or to membrane-based processes.14,15 Among zeolitic materials, synthetic aluminosilicate zeolites have been most widely investigated for selective CO2 removal.16−22 However, other experimental studies have been directed at natural zeolites,23 all-silica zeolites,19,24,25 aluminophosphates,26,27 and silicoaluminophosphates.28,29 Computational methods have been employed in a complementary fashion to experimental investigations. In particular, grand-canonical Monte Carlo (GCMC) simulations permit the prediction of adsorption isotherms, adsorption selectivities, and preferred adsorption sites at a very moderate computational expense. Until recently, typical GCMC studies usually looked at a single zeolite or sets of up to ∼30 systems.30−34 Due to increasing computational power, computational methods are now also employed in a “screening” fashion to investigate the properties of a large group of materials. For the case of MOFs, this approach has been reviewed recently by Sholl and coworkers.35 Other important contributions to the field have come from the groups of Smit (for zeolites, hypothetical zeolites, and ZIFs)36,37 and Snurr (for MOFs).38 A particularly interesting strategy has been pursued by Martin et al.:37 Having performed computations of the Henry constant of CO2 for a large set of (140 000) hypothetical zeolite structures, these authors used an automated algorithm to determine common structural features in those structures that exhibit outstanding CO2 adsorption properties. A number of structural patterns that generate CO2 adsorption sites with high binding energies could thus be identified. While this approach will certainly find further important applications in the field of MOFs, one disadvantage is that the automatically identified patterns do not correspond to any intuitive zeolite building unit, such as a specific cage type. In previous work, we have employed GCMC simulations to study the separation of CO2/N2 mixtures in 18 important zeolite frameworks, assuming a purely siliceous composition (while most frameworks are not available in their all-silica form, this assumption was made to allow for a comparison of different topologies, fixing the pore wall composition).39 An analysis of the energetically preferred adsorption sites in the most promising systems revealed that these sites are typically associated with distinct structural features: In GIS, MER, and GME, the CO2 molecules interact strongly with groups of fourrings that form double-crankshaft chains. Other preferential adsorption sites are located at the center of eight-ring windows

and in double eight-ring (d8r) units or other cavities that are accessible through eight-ring windows. In this work, we will first analyze the common features of the natural tiles associated with these preferred adsorption sites. Then we will propose a set of criteria to identify other tiles that may also lead to favorable separation properties. We perform new simulations for all zeolite frameworks from the IZA database which incorporate these tiles, excluding those systems that are nonporous to CO2. After discussing the CO2 adsorption and CO2/N2 separation properties of these systems, we finally investigate the carbon dioxide adsorption sites in the most promising frameworks and comment on the relationships between natural tiles and energetically preferred adsorption sites.



COMPUTATIONAL DETAILS

For the majority of zeolite frameworks, the GCMC simulations of CO2 single-component and CO2/N2 adsorption were carried out using the Multipurpose Simulation Code MuSiC.40 For technical reasons, the two monoclinic zeolites included in the set (HEU and SFO) could not be treated with this code, so the Sorption module of Accelrys Materials Studio was used for these systems.41 By comparing results for a few common systems, it was established that both codes deliver virtually identical results (with the exception of the decomposition of the interaction energy, where MuSiC is more versatile). Longrange dispersion and short-range repulsion were modeled using Lennard-Jones potentials, whereas atom-centered partial charges were used to represent electrostatic interactions. At least 4 × 106 equilibration steps and 6 × 106 production steps were used for the calculation of single-component isotherms, and simulations of mixture adsorption used 12.5 × 106 equilibration steps and 37.5 × 106 production steps. The calculations using the Sorption module were performed with fewer steps. A cutoff of 12.8 Å was used for dispersion interactions, whereas Ewald summation was employed for electrostatic interactions. In the calculations using MuSiC, the contributions to the interaction energy were pretabulated on grids, with a resolution of at least 0.2 Å. The GCMC simulations were carried out for a pressure range up to 1 bar and a temperature of 298 K. For the CO2/N2 mixture, two different compositions were considered, an equimolar composition and a 1:9 composition. The latter case corresponds to the approximate composition of typical flue gases (neglecting water and other additional species). From the simulations of CO2 adsorption, the isosteric heat of adsorption qst was derived as qst = −⟨Utot /N ⟩ + RT

(1)

Here, ⟨Utot/N⟩ is the average interaction energy per adsorbed molecule (in kJ mol−1) and R is the gas constant. The total interaction energy, Utot, was decomposed into its different contributions: Utot = UvdW,sf + Ues,sf + Uff

(2)

UvdW,sf and Ues,sf correspond to the dispersive and electrostatic contribution to solid−fluid interactions, whereas Uff includes all fluid−fluid interactions. The theoretical CO2 working capacity, assuming VSA conditions (adsorption pressure of 1 bar, desorption pressure of 0.1 bar), was calculated from the binary mixture isotherms according to 17100

dx.doi.org/10.1021/jp405507y | J. Phys. Chem. C 2013, 117, 17099−17110

The Journal of Physical Chemistry C

Article

Figure 1. Visualization of preferred CO2 adsorption sites and the natural tile constituting their atomic environment in GIS (t-gsm), MER/RHO (topr), MER (t-pau), and GME (t-gme). Molecules shown in green and orange are located within cages, whereas molecules in blue and dark red are located at eight-ring windows. Overlapping images of molecules are included to emphasize the full symmetry. Figure prepared based on results published in ref 39.

Δn(CO2 ) = n(CO2 )p ‐ ads − n(CO2 )p ‐ des

parameters and the REPEAT charges for all systems are supplied in the SI.

(3)



The ideal adsorption selectivity was calculated as n(CO2 )/n(N2) S(CO2 /N2) = p(CO2 )/p(N2)

RESULTS AND DISCUSSION Choice of Framework Types. The preferred CO 2 adsorption sites in GIS, MER, GME, and RHO (as well as three other zeolite frameworks) have been discussed in detail in an earlier publication.39 According to the analysis of the natural tilings presented in ref 2, these frameworks contain the following tiles: t-gsm (GIS); t-opr, t-ste, t-pau (MER); t-gme, t-hpr, t-kno (GME); and t-opr, t-grc (RHO). In all these structures, CO2 adsorption sites where the guest−framework interaction energy exceeds −30.0 kJ mol−1 were found. A reevaluation of these CO2 adsorption sites shows that they are associated with the t-gsm tile in GIS, the t-opr and the t-pau tiles in MER, the t-gme tile in GME, and the t-opr tile in RHO (while the tile as such is a more abstract concept, we use the term “tile” here as being synonymous with the atomic arrangement corresponding to a tile’s vertices and edges). The adsorption sites and their structural environment are displayed in Figure 1. Before discussing the properties of the tiles in more detail, we need to clarify why these particular structural arrangements lead to such high affinities for CO2: The dispersive part of the interaction, which is the dominant contribution, is determined by the distances to the surrounding framework atoms. A geometric arrangement of framework atoms that allows for many “close” contacts with atoms of the CO2 molecule, i.e., contacts close to the equilibrium distance, will thus lead to a strong dispersive interaction. The equilibrium distances calculated from the force-field parameters correspond to d(O_CO2−O_zeo) = 3.44 Å and d(C_CO2−O_zeo) = 3.30 Å. To highlight the importance of these close contacts, the guest−framework distances have been measured for the two adsorption sites observed in GIS. All contacts with framework oxygen atoms of less than 4 Å are displayed in the SI (Figures S1 and S2). For the CO2 site at the cage center, there is a total of 18 such close guest−framework contacts, and it can be seen that the CO2 molecule fits nicely into the space surrounded by a crankshaft-like arrangement of three four-rings. An even larger number of close contacts is found for the site at the center of the eight-ring window, with a total of 22 guest−framework contacts below 4 Å. Some of these contacts are in fact significantly shorter than the equilibrium distance, highlighting that the position of local minima is determined by the optimal balance of the interactions with all neighboring framework atoms, not just by a few close contacts. Later in this paper we

(4)

Here, the numerator corresponds to the molar ratio in the adsorbed phase, while the denominator corresponds to the molar ratio in the gas phase (the ratio of partial pressures). Simulation snapshots obtained from simulations of CO2 adsorption at 1 bar were used to determine the preferred adsorption sites in a number of structures of particular interest. To find the local minima, a geometry optimization was carried out using the Forcite module of Accelrys Materials Studio,41 with the same force-field parameters as in the GCMC simulations. Having identified different starting positions for the determination of local minima, a subsequent optimization with a single CO2 molecule per supercell was performed. The coordinates and the solid−fluid interaction energy Usf were determined for all nonequivalent positions. The geometries, partial charges, and Lennard-Jones parameters of carbon dioxide and nitrogen were taken from the TraPPE force field.42 The structural data of the zeolite frameworks were extracted from the IZA database, which provides crystallographic information for all recognized zeolite frameworks.1 As most frameworks are not experimentally accessible in their purely siliceous form, the idealized, distanceleast-squares-minimized, siliceous structures were taken from the IZA database. In cases where experimental data are available, the lattice parameters from the IZA database agree well with the experimental values.43 Supercells of sufficient size were used, and inaccessible areas of the structures were blocked using noninteracting spheres in the GCMC simulations. Partial charges located at the framework atoms were obtained from density-functional theory (DFT) calculations using the REPEAT method.44 The DFT calculations were performed using the mixed Gaussian and plane-wave code CP2K,45,46 employing the PBE exchange−correlation functional47 and relativistic Goedecker−Teter−Hutter pseudopotentials.48 Further details are given in the Supporting Information (SI). In previous work, we have empirically derived a set of LennardJones parameters for the zeolite oxygen atoms that are designed to be combined with REPEAT charges.39 These parameters were combined with the TraPPE parameters for the fluid molecules using Lorentz−Berthelot combination rules in order to represent dispersive solid−fluid interactions. All force-field 17101

dx.doi.org/10.1021/jp405507y | J. Phys. Chem. C 2013, 117, 17099−17110

The Journal of Physical Chemistry C

Article

tions (CO2:N2 = 1:1 and CO2:N2 = 1:9), were carried out for the 37 zeolite frameworks identified above, assuming a temperature of 298 K. All resulting adsorption isotherms, as well as the isosteric heats of CO2 adsorption, are provided in the SI. Figure 2 summarizes the most important results by plotting the isosteric heat of CO2 adsorption at 1 bar against the CO2 uptake under the same conditions.

will consider the effects of framework distortion and of longerrange forces. A survey of the 201 structures in the IZA database delivers a total of 18 framework types that contain at least one of the four tiles considered in Figure 1. However, in order to find as many promising topologies as possible, other tiles that are sufficiently “similar” to these tiles should also be included. To facilitate the identification of these tiles, we summarize the structural features that appear to be most significant, especially with regard to the presence of strong CO2 adsorption sites: all tiles possess eight-ring windows, and several energetically favorable adsorption sites are found at the center of these windows. On the other hand, none of the tiles possesses rings that are larger than eight-rings. Such larger rings are often associated with more open structural arrangements, i.e. less narrow pores, in which the total solid−fluid interaction is weaker. Finally, preferred adsorption sites at the center of the cages are usually associated with a strong interaction of CO2 molecules with assemblies of edge-sharing four-rings, a feature that is nicely visible for the adsorption sites shown in green in Figure 1. On the basis of these observations, we therefore define three criteria that all tiles to be included in this study should meet: (1) The tile should have eight-ring faces. (2) None of the tile’s faces should be larger than an eightring. (3) At least two of the tile’s faces should be four-rings that share a common edge. We emphasize that these criteria are to a large extent empirical, as they are based on the key observations made for the energetically preferred adsorption sites in GIS, MER, GME, and RHO. As such, the set of criteria is based on a limited amount of information, since only 18 zeolite frameworks were included in our previous study.39 Future studies, e.g., based on the screening approach,36−38 could well lead to deeper insights into the structure−property relationships and might enable a refinement or reformulation of the criteria. In total, 33 of the natural tiles that build up the 201 recognized zeolite frameworks for which the natural tiling is available fulfill these criteria. There are 44 frameworks that contain at least one of these tiles. Both the 33 tiles and the corresponding 44 frameworks are listed in the SI (Tables S39 and S40). Without discussing the statistics exhaustively, it is worth mentioning that the t-gme tile is the most frequent of the 33 tiles, occurring in eight framework types, and that the PAU framework contains five different tiles conforming to the three criteria. Six of the 44 frameworks (CHA, ERI, GIS, GME, MER, RHO) were already included in our earlier study,39 and the results for these systems will be integrated into the present study. For seven frameworks (AFN, APC, BRE, CGF, −LIT, LTN, SAT), the radius of the largest diffusing sphere1,49 is smaller than the kinetic diameter of the CO2 molecule (3.3 Å), so it is expected that these systems are nonporous to CO2. Therefore, no GCMC simulations were performed for these systems. The natural tilings of the most relevant frameworks for this publication have been visualized, using information available from the Reticular Chemistry Structure Resource7 and employing the program Gavrog 3dt.50 These figures are also included in the SI. The natural tilings of other framework types are available from the IZA database.1 Simulation Results: Single-Component Adsorption. GCMC simulations of CO2 single-component adsorption and CO2/N2 mixture adsorption, assuming two different composi-

Figure 2. Simulation results: CO2 single-component adsorption. Plot of the isosteric heat of CO2 adsorption against the amount of CO2 adsorbed (p = 1 bar, T = 298 K). The green lines serve to guide the eye: The vertical line marks n(CO2) = 2.5 mmol g−1, while the horizontal line marks qst(CO2) = 30 kJ mol−1. Selected framework types are labeled.

An evaluation of the amount of CO2 adsorbed at 1 bar shows that 19 of the 37 systems have an uptake above 2.0 mmol g−1, and eight of these exhibit an uptake above 2.5 mmol g−1. Compared to materials of real interest, even the uptake of the best performing framework, GIS, is probably too low, as capacities ranging from 4 to 8.5 mmol g−1 have been reported for cation-exchanged zeolites,19 carbons,51,52 and MOFs.53,54 Given the low surface areas and homogeneous pore wall chemistry of all-silica zeolites, however, an uptake exceeding 2.0 mmol g−1 is already a reasonably high value, and our earlier study has shown that lower uptakes are predicted for the large majority of “common” zeolite frameworks.39 The isosteric heat of CO2 adsorption is another quantity of interest that can be derived from the single-component simulations, as it represents the affinity of the material toward carbon dioxide. Recent molecular simulation studies of MOFs have shown that a correlation can be developed between the isosteric heat of adsorption, or the difference between the heats of CO2 and N2 adsorption, and the CO2/N2 selectivity.55,56 In a rigorous approach, the isosteric heats of adsorption of different materials should be compared for a given loading. However, as we are most interested in the materials’ properties at a pressure of 1 bar, we compare them for a given pressure. For completeness, the evolution of qst as a function of the loading for each framework is shown in the SI. Most systems exhibit a moderate increase of qst with loading, which can be explained by an increasing contribution of attractive CO 2 −CO 2 interactions. At a pressure of 1 bar, 12 of the 37 frameworks exhibit an isosteric heat of CO2 adsorption of more than 30 kJ mol−1, eight of which fall in a range between 30 and 32 kJ mol−1. The qst values of ABW, GIS, SIV, and JBW exceed 32 kJ mol−1, with JBW reaching 39.2 kJ mol−1. In our previous study of 18 17102

dx.doi.org/10.1021/jp405507y | J. Phys. Chem. C 2013, 117, 17099−17110

The Journal of Physical Chemistry C

Article

framework types,39 only GIS and MER were found to have isosteric heats of CO2 adsorption above 30 kJ mol−1. A comparison of selected qst values with those obtained in a largescale screening study by Smit and co-workers shows good agreement (results of this study are available from www. carboncapturematerials.org), indicating that the results are not highly sensitive to the specific set of force-field parameters used.36 As discussed previously, the use of REPEAT charges permits the unambiguous decomposition of the total interaction energy into electrostatic and dispersive contributions, which constitutes an important advantage over fully empirical force fields. This decomposition was performed for those systems where qst exceeds 30 kJ mol−1, and the results are shown in Figure 3. In our earlier investigation, it was found that Figure 4. Simulation results: CO2/N2 mixture adsorption. Plot of the CO2/N2 selectivity versus the CO2 working capacity (CO2:N2 = 1:9, pads = 1 bar, pdes = 0.1 bar, T = 298 K). For clarity, the selectivity is displayed on a logarithmic scale. The green lines serve to guide the eye: The vertical line marks Δn(CO2) = 0.5 mmol g−1, while the horizontal line marks S(CO2/N2) = 40. Selected framework types are labeled.

Concerning the working capacity, the values obtained for the majority of systems are low, ranging below 0.5 mmol g−1. Six systems exhibit higher capacities, but only GIS and JBW have working capacities exceeding 1.0 mmol g−1. In a survey of different groups of ordered porous materials, promising values of between 2.5 and 4.3 mmol g−1 were obtained for cationexchanged zeolites and MOFs with accessible metal sites.13 This shows that even those siliceous systems that are predicted to have a (relatively) high affinity toward carbon dioxide, which translates into a high CO2 uptake at low pressures, cannot compete with materials that incorporate specific interaction sites. Therefore, we re-emphasize that the main objective of this study is not a prediction of optimized materials for real applications but a rationalization of the relationships between topological features and affinity for carbon dioxide. Concerning the CO2/N2 selectivity, it is convenient to define a threshold of S(CO2/N2) = 40, as this value corresponds to a reasonably high selectivity that is surpassed by cationexchanged zeolites and some MOFs,13,57 but not by carbons 51,57 and most zeolitic imidazolate frameworks (ZIFs).58 Of the framework types studied here, seven exhibit selectivities above 40, reaching values as high as 350 (JBW) and 136 (ABW). We note that, for JBW, a quantitatively similar result was obtained in an earlier GCMC study.34 Despite this very high selectivity, this feature was not discussed in more detail due to the very low working capacity under PSA conditions. Taking together the results for the working capacity and the CO2/N2 selectivity summarized in Figure 4, it is quite straightforward to define a subgroup of framework types that warrant most attention due to their promising properties: This group consists of ABW, ATN, ATT, GIS, JBW, PHI, SIV, andas a borderline case with a selectivity very close to 40 PAU. Interestingly, a very similar set of “most interesting” systems (possibly including one to three additional entries) would arise if the selection had been based on the quantities derived from CO2 single-component adsorption, shown in Figure 2. When it is considered that experimental studies often have to rely on single-component adsorption data due to the

Figure 3. Isosteric heat of CO2 adsorption for those systems where qst > 30 kJ mol−1 at p = 1 bar, T = 298 K. The isosteric heat is decomposed into the following contributions: Dispersive solid−fluid interaction, electrostatic solid−fluid interaction, fluid−fluid interaction, and (constant) RT term. Because the calculations for HEU were performed with a different code, no decomposition into solid−fluid and fluid−fluid interactions was possible for this case.

the contribution of electrostatic interactions to the total solid− fluid interaction can vary by nearly 1 order of magnitude in different zeolite frameworks, ranging from