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Importance of Blocking Inaccessible Voids on Modeling Zeolite Adsorption: Revisited Paula Gómez-Álvarez, A. Rabdel Ruiz-Salvador, Said Hamad, and Sofia Calero J. Phys. Chem. C, Just Accepted Manuscript • DOI: 10.1021/acs.jpcc.7b00031 • Publication Date (Web): 12 Jan 2017 Downloaded from http://pubs.acs.org on January 19, 2017

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The Journal of Physical Chemistry

Importance of Blocking Inaccessible Voids on Modeling Zeolite Adsorption: Revisited Paula Gómez-Álvarez, A. Rabdel Ruiz-Salvador, Said Hamad, and Sofia Calero*

Department of Physical, Chemical and Natural Systems Universidad Pablo de Olavide, Ctra. Utrera km 1. ES-41013, Seville, Spain

*Email: [email protected]

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Abstract We have carried out a geometry-based analysis of the need of artificial blocking in a collection of zeolites, for various gases of industrial and environmental relevance (carbon dioxide, methane, nitrogen, oxygen and argon), and we have studied its influence on the heats of adsorption and saturation uptakes, which are key properties for gas separation and storage, respectively. Our results highlight the importance of blocking some of the pores of the zeolites in order to avoid the spurious inclusion of guest molecules in inaccessible regions during Monte Carlo simulations. We can thus avoid the overestimation of adsorption and also identify non-adsorbent zeolites for these gases by introducing pore blockings. We discuss the limitations of the current approaches to perform automatic blocking, and we check the reliability of the results obtained with our blocking method, by comparing with self-diffusion coefficient values calculated using Molecular Dynamics simulations.

Keywords Monte Carlo simulation, diffusion, pore accessibility, pore window, heat of adsorption, molecular size


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1. Introduction In recent years, Molecular Simulation methods have been widely used to investigate adsorption performance of guest molecules in porous media. It is important to assess the accessibility of the pores, but this is a problem that has been scarcely addressed using large databases of materials, since molecular diffusion studies using Molecular Dynamics (MD) simulations, with accurate potentials, are computationally expensive. Gran Canonical Monte Carlo (GCMC) simulations are a very useful tool for studying adsorption in nanoporous solids.1-4 The huge success achieved in the last decade obeys first to the reproduction of complex experimental data, as for example hydrogen adsorption, 5-11 hydrocarbon separation

12-16

and CO2 capture,

17-21

providing insights into the underlying adsorption mechanisms,

which help to rationalize the experimental results. These simulations, 22-26 have shown to have a high predictive power, since they can be used to perform reliable computational screenings for the selection of materials for targeted applications.27-36 Monte Carlo (MC) methods sample the configurational space without considering molecular transit processes over energy barriers. They can therefore be used to find relative and absolute minimum energy configurations, at an acceptable computational cost. 37-39 However, the study of molecular adsorption in nanoporous solids requires the use of methods that take into account the energy barriers that need to be surpassed for the molecules to reach a potentially given adsorption site. When the cross-section diameter of the molecules is comparable to the size of the window delimiting the pore access, these energy barriers increase exponentially with the molecule size. In the case of molecules whose molecular size is larger than the window size, one expects that the available site will not be occupied, and therefore the molecule would never reach it. This is the usual case for many zeolites, which contain cavities only accessible through small pore windows. For example, the pure silica zeolite frameworks LTA and CHA have pores large enough to host branched hydrocarbons, but the small size 3 ACS Paragon Plus Environment


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of the windows, ca. 4 Å, makes the pores inaccessible for these molecules. In order to take into account the above limitation in MC-based screenings, one can fill in advance the identified inaccessible pores with purely repulsive pseudoatoms that prevent such pores from being occupied by adsorbates. This procedure is known as artificial blocking of the pores. In 1996, Bates et al. showed that it was necessary to block the access to the sodalite cages (also known as β-cages) in order to accurately model the adsorption of hydrocarbon molecules in zeolite A (LTA framework).40 For some years, this result was mostly ignored. 41 But in 2010 Krishna and van Baten wrote a comment42 to a paper that reported a higher adsorption capacity in LTA and DDR zeolites 43 than the value published by them.44 The discrepancy was explained by the lack of blocking for the inaccessible sites. Although this situation is less likely to appear in Metal-Organic Frameworks due to their larger window sizes, it might also occur, as shown by Jiang and co-workers.45 Despite the publication of the two mentioned papers, artificial blocking of inaccessible pores has been scarcely used during the last years.This is not consistent with the wide use of classical methods in modelling zeolite adsorption. For instance, only for published works in 2015 Scholar Google indexes 624 records using the combined words “adsorption”, “Grand Canonical Monte Carlo” and “zeolite”. In the past, it was difficult to find the location of the sites where the pore blocking should be centered as well as the ratio of the blocking sphere, but it is important to know that now this can be done in a fully automatic way through freely available software. In this study we focus on the importance of using artificial pore blocking, if it would be required, as a routine procedure when modeling adsorption in porous materials. We address the effect of appropriate artificial blocking on the adsorption of a set of relevant gas molecules in all known experimental zeolite frameworks. In contrast to previous studies, where the flexibility of the zeolites is not considered at all, in this work we introduce an approach that allows a partial inclusion of the effect of window flexibility on the 4 ACS Paragon Plus Environment

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molecular accessibility to the pores.

2. Methods The crystal structures of the zeolites are taken from the collection of the experimentally known zeolite topologies indexed and collected by the International Zeolite Association (IZA). The starting zeolite structures were obtained from the IZA database.50 We ignored those that have interrupted frameworks. After the success of atomistic modelling techniques for studying the effect of flexibility on the structural features of zeolites, Forster and co-workers recently shown that flexibility also has an impact on modelling adsorption in nanoporous materials.51 Zeolite structures were relaxed using interatomic potential approaches. This is commonly done when a large set of zeolite structures are studied for the good balance between accuracy and computational cost. The results of such type of calculations are in excellent agreement with experimental data, in terms of both geometry and thermodynamic properties.54-59 In our study, we used the well-known shell-model potentials developed by Sanders et al.60 to optimize the zeolite structures using lattice energy minimization techniques, as implemented in the GULP code. Short range interactions were handled in real space within a cutoff of 16 Å, while Coulombic interactions were computed with the Ewald summation method. 63 We used the NewtonRapson minimizer

64

for the structural relaxation, switching to the RFO method once a large degree of

relaxation was achieved, to ensure that real minima were reached (all vibrational frequencies are real numbers).65 The use of the minimum energy configuration has been previously proved to be necessary in the study of zeolites.66-69 The determination of pore size, in terms of both the sizes of the pore delimiting windows and the internal diameters of the pores, depends on the choice of the framework atomic radii. The most relevant is the radius of the oxygen atom, which is frequently considered to be 1.35 Å, 70 as in IZA 5 ACS Paragon Plus Environment


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database. This value was reported by Shannon as the effective ionic radius, and therefore it is directly related to bond distances.71 However, our interest lies in computing sizes that are of relevance for intermolecular distances, so we have chosen the radii recommended by the Cambridge Crystallographic Database Centre (CCDC),72 which correspond to the van der Waals radii 73 of the oxygen and silicon, of 1.52 Å and 2.10 Å respectively. We note that previous studies using pore blocking totally ignored the influence of framework flexibility. However, the influence of framework flexibility on the accessibility to the pores is known from decades ago, and early inferred by Barrer and Vaughan on interpreting adsorption behavior in small pore solids.74 To account for this issue, we introduce an approach that, although based on a static picture of the material, can be considered as pseudo-flexible in terms of atomic motions. The approach is based on analyzing the deformations of the 8-membered rings that are reported in several zeolites.75-78 We focus on the window size distribution curves, in order to find the largest deformation values that can be found with an significant probability. We selected 0.15 Å as a representative value for the instantaneous increase of the pore window size. Constructing realistic deformable frameworks for the whole set of zeolites studied here is very expensive, so we have developed a simple but meaningful method, which consists on reducing the radius of the oxygen atoms in the calculations, thus increasing the effective pore window size. By decreasing the size of the oxygen atoms we are able to introduce the instantaneous, effective increase of window size that takes place in flexible zeolites, which allows the crossing of some molecules that would otherwise not cross. We used a value of the oxygen atom of 1.37 Å (i.e. 1.52 Å - 0.15 Å) for the calculation of pore window features in this pseudo-flexible approach. This is a lower limit value, since for pores delimited by larger windows the pore entrance deformations are expected to be higher. Although, at the same time, in those cases the interest in molecular sieving by size-exclusion is usually lower. It is worth noting that this is a reasonable method with which to take into account pore blocking, accounting also for the effect of 6 ACS Paragon Plus Environment

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molecule size on window accessibility, it will overestimate the values of the accessible surface area and pore volume. For the calculation of these properties, the average size of the windows is a more realistic value, and therefore the unmodified value of the oxygen radius, 1.52 Å, seems appropriate. The accessible space within a porous material depends on the molecular size, so the artificial blocks were calculated using various molecular probe radii, rp, to cover a wide variety of adsorbates. Particularly, we considered rp = 1.7 Å, 1.8 Å and 1.9 Å, which are representative of the kinetic diameters of carbon dioxide (CO2, 3.4 Å), argon (Ar, 3.4 Å), oxygen (O2, 3.46 Å), nitrogen (N2, 3.64 Å), and methane (CH4, 3.8 Å). The determination of the inaccessible voids, and the subsequent pore blocks (location and radius of the pseudoatom) was carried out using the Zeo++ software package.79 This tool is based on the Voronoi tessellation,80 and allows a high-throughput, geometry-based analysis of crystalline porous materials. It should be noted that appropriate artificial blocking using Zeo++ is currently restricted to molecules whose cross section is circular-shaped. We also used this code to obtain the pore volume, surface area, and pore sizes of the zeolites. In particular, we focus on the Pore Limiting Diameter (PLD), due to its close relation with molecular diffusion and the accessibility to the pores, as well as with pore blocking. The PLD of a structure is defined as the largest diameter that a sphere can have, and still diffuse through the structure, so that it is impossible for any sphere with a larger diameter to travel through the structure without overlapping one or more frameworks atoms. Although real molecules are not hard spheres, it is clear that gas molecules that are significantly smaller than the PLD will be able to diffuse freely through the porous material, and vice versa. We use the heat of adsorption as a probe property to evaluate the influence of artificial blocking of inaccessible voids on the adsorption of various guest molecules. The heat of adsorption, Qst, is a measure of the framework-adsorbate affinity at the low-coverage regime, and therefore varies strongly with the degree of confinement of the molecules within the nanopores. This property was computed at 7 ACS Paragon Plus Environment


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room temperature via Monte Carlo molecular simulations in the canonical ensemble (NVT), using the Widom insertion method.81 The calculation of the adsorption properties at finite pressures, using GCMC, would require significantly larger computational resources, due the large set of framework structures under study. We note that the purpose of the present work can be achieved without employing results at finite pressures. Nevertheless, the adsorption capacity of the set of zeolites for a specific adsorbate, methane, has been determined, as an example of the effect that pore blocking has on molecular loading. All simulations involving guest molecules were performed using the RASPA code.82 In previous studies,34 due to the lack of an automatic procedure for determining pore blocking, MD simulations were used for this purpose, i.e. to detect which structures do not allow the diffusion through certain windows. We used MD simulations to evaluate the reliability of the computed pore blocks, in the case of carbon dioxide. In the Henry regime, self-diffusion is fast enough to be observed in MD studies of molecular diffusion, and thus a single molecule was considered for the simulation. We used a time step of 1 fs, and performed production runs of 100 ns, in the NVT ensemble. The temperature, T, was set to 298 K, and maintained using the Nose-Hoover thermostat.83 The intermolecular interactions were computed as the combination of Lennard–Jones and Coulombic terms. All zeolite structures were treated as rigid frameworks, with atomic charges of q Si = +0.786 e- and qO = -0.393 e-.84 Regarding the adsorbates, CO2, N2, and O2 molecules were modeled as rigid molecules with partial charges distributed so that the experimental quadrupole moments are reproduced. More specifically, CO2 was defined as a linear molecule with d CO=1.149 Å and partial charges qO = - 0.3256 e- and qC = + 0.6512 e-.85 The N2 molecule was described by a linear, three-site model,86 with dNN=1.1 Å and partial charges on the N atoms and the center of mass with respective values of -0.405 e- and +0.810 e-. The O2 molecule was represented by a three-site model, 87 with 8 ACS Paragon Plus Environment

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dOO=1.2 Å and a negative point charge of 0.112 e - on each O atom, as well as a balancing positive point charge of 0.224 e- at the center of mass of the molecule. Ar and CH 4 were defined as single LennardJones interacting centers. Guest-guest and guest-host L-J parameters for CO 2 and CH4 were taken from García-Sanchez et al.84 and Dubbeldam et al.,88 respectively. The parameters for the remaining adsorbates are defined in work of Martin-Calvo et al.89 Since the most relevant dispersive interactions are those of oxygen atoms, interactions of Si atoms were not explicitly considered; they are instead embedded in the contributions associated to the bonded O atoms. The number of unit cells in the simulation box was chosen so that the minimum length in each of the axis was larger than twice the cutoff distance. Periodic boundary conditions90 were employed in the three dimensions.

3. Results and discussion The first question we need to address, when dealing with molecular adsorption in nanoporous solids, is whether the geometric features of the solid would allow the adsorbate molecule to get into the pores. Usually, the focus has been put put on the comparison between the kinetic diameter of the adsorbate molecule and the PLD of the solid. Obviously, if the latter is smaller, there will be no molecular adsorption in experiments, but it could still be possible to observe molecular adsorption in Monte Carlo calculations. The PLD of all zeolite frameworks can be calculated employing a number of codes. However, as we will show here, the identification of inaccessible pores in solids for a particular molecule in terms of geometrical features cannot be performed with a method solely based on the overall PLD, as the local accessibility to the pores should be considered by analyzing the size of the pore delimiting windows. We take this fact into account by blocking inaccessible pores in the zeolites to prevent molecular adsorption. We found that a large set of zeolites, those displayed in Table 1, are 9 ACS Paragon Plus Environment


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not likely to permit the access of the studied adsorbates to their channel systems. In the dilute adsorption regime of the studied molecules in these solids, the computed host-guest energies result in positive values when applying pore blocking. This fact suggests that, indeed, no molecular adsorption occurs. In contrast, by omitting the pore blocks, favorable (negative) adsorption energies were found, which should be interpreted as an evident spurious result. Thus, to computationally account for the issue of the existence of inaccessible pores, the generation and use of artificial blocks in MC simulation studies is necessary. As mentioned in above, the impact of pore window flexibility can be considered in a pseudo-flexible approach, by using a smaller radius (1.37 Å) for the framework oxygen atoms. By doing so, some of the non-adsorbent zeolites listed in Table 1 become accessible to the adsorbate molecules. They have been labeled with an asterisk.

Table 1. Zeolites needing artificial blocks to ensure a non-porous character for the targeted gas molecules. Zeolites removed from the list by using the pseudo-flexible approach are labeled by an asterisk. Molecule

Zeolite AEI* AFT AHT APD* AST AWO* BRE CAS CGF CHA* CZP DAC DDR DFT*

Ar

DOH EAB EDI EPI FRA GIS GOO IHW ITW JSN JSW LAU* LEV LOS LTJ MEP MSO MTN NON OWE* PHI RUT RWR SBN SIV SOD UEI UFI* UOZ ZON ACO AEI* AFG AFT AHT APD* AST ATT AWO* BRE CAS CDO CGF CHA*

O2

CZP DAC DDR DFT* DOH EAB EDI EPI FRA GIS GIU GOO IHW ITW JOZ JSN JSW LAU* LEV LOS LOV* LTJ MEP MSO MTN NAT NON NPT OWE* PHI RUT RWR SBN SGT SIV SOD THO UEI UFI* UOZ WEI* ZON ACO AEI* AEN AFG AFT AFX AHT APD* AST ATT AWO* BRE CDO CGF

CO2

CHA* CZP DAC DDR DFT* DOH EAB EDI EPI FAR FRA GIS GIU GOO IHW ITW JOZ JSN JSW LAU* LEV LIO LOS LOV* LTJ LTN MEP MSO MTN NAT NON NPT OWE* PHI RSN RUT RWR SAT SBN SGT SIV SOD THO TOL UEI 10 ACS Paragon Plus Environment

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UFI* UOZ VNI WEI* YUG ZON ACO AEI AFG AFT AHT APD AST AWO AWW* BRE BSV* CAS CGF CHA N2

CZP DAC DDR DFT DOH EAB EDI EPI ERI FRA GIS GIU HEU IHW ITE* JOZ JSN JSW KFI* LAU LEV LOS MEP MSO MTF* MTN NON OWE PCR RHO* RTE* RTH* RUT RWR SAS* SAV SBN SGT SIV SOD TOL UEI UFI UOZ WEI ZON AEI AFG AFN AFT AHT APD AST ASV* ATN* ATT AWO AWW* BOF* BRE

CH4

CDO CGF CGS CHA DAC DFT EAB EDI EPI ERI GIS HEU IHW ITE JOZ JRY JSN JST JSW LAU LEV LOS LTA MAR MEP MSO MTF MTN NON NPO NPT OWE PON* RHO RTE RTH RUT SAS* SAV SBN SGT SOD SOS UEI UFI UOS UOZ ZON The calculation of molecular diffusion also allows the identification of structures that are non-

porous for certain guest molecules, although at a high computational cost. Here we used MD simulations in the rigid zeolite frameworks in order to examine the reliability of the geometry-based approach for the computational determination of pore blocking, i.e. to check the reliability of the information provided in Table 1. We simulated the self-diffusion of carbon dioxide in the 65 nonporous structures that did not allow diffusion of this molecule using the geometry-based screening. It is worth noting that, by using MD simulations, we are in fact testing experimentally accessible diffusivities of relevance for practical applications. Much slower diffusivities, evidenced for instance by diffusion coefficients below 10-12 m/s2, can be tested by Transition State Theory. 90 This theory is not used here, as we focus on the prediction of materials that could be used in applications with low-cost operating conditions, ideally at room temperature and atmospheric pressure. The obtained Mean Square Displacements (MSDs) as a function of time are displayed in Figure 1, with indicating the names of those zeolites for which there is significant diffusion. We observe that carbon dioxide has indeed very slow or negligible diffusion in all but five zeolites (specified in the plot), with diffusion coefficients in the range of 10-9-10-10 m2/s. Below, we analyze the case of these five zeolites. This reasonably good 11 ACS Paragon Plus Environment


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agreement between results from MC simulations using pore blocking and MD simulations validates the methodology. It should be noted that there are a few structures experimentally known as adsorbents of these gas molecules, such as for example CHA, 94 DDR95 and RHO.96 This non-correspondence can be ascribed to framework flexibility induced by gas adsorption (at finite pressures) or to the presence of extra-framework cations. It is worth noting that by considering the pseudo-flexible approach, i.e., by reducing the radius of the framework oxygen atoms, CHA, DDR and RHO zeolites (that exhibit adsorption in experiments) and DFT and APD zeolites (highlighted in Figure 1) do not require artificial blocks and appear indeed as adsorbents, as indicated in Table 1. However, while MD calculations reveal that the latter zeolites (DFT and APD) allow diffusion of N 2,97 pore blocking is still predicted for this molecule even using a radius of 1.37 Å for the framework oxygen.

Figure 1. MSDs of a single CO2 molecule in the zeolites reported in Table 1, as a function of time calculated at 298 K by MD simulations. Names are shown for the zeolites that allow CO2 diffusion. 12 ACS Paragon Plus Environment

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The use of the pore blocking in our Monte Carlo calculations leads to considerable variations in the heats of adsorption, Qst. These values are displayed in Figure 2, for the five guest gas molecules considered, and only for those zeolites that are adsorbent for these molecules. To present the data in a comparative way, the abscise axes are ordered in such a way that the zeolites show decreasing values of heats of adsorption for non-blocked zeolites. As can be seen, there is a notable number of topologies for which the Qst values obtained without blocking are significantly larger, i.e., the adsorption is overestimated if appropriate artificial blocks are not considered. As it is apparent from the figure, most variations correspond to zeolites with the highest Qst values. This can be rationalized on the basis of that stronger host-guest affinities usually correspond to the smaller pore/molecular size ratios, and small pores are commonly delimited by small PLD. On the other hand, there are few cases, where blocking increases the heat of adsorption. Preventing the access to large pores, adsorption occurs in smaller pores, with the subsequent increase of the strength of the host–guest interactions. Although we found a number of topologies with non-accessible voids for these guest gas molecules, the coincident Qst values reveal that for most of the adsorbent zeolites all the pores are accessible (i.e., no artificial blocks are required). Obviously, this number will be reduced with increasing the molecular size of the adsorbate. To illustrate this, Figure 3 shows the accessible space, in particular the accessible volume (AV) and the accessible surface area (ASA), of the whole set of zeolites, for probe radii of 1.7 Å and 1.9 Å. Although these radii (corresponding to kinetic radii of carbon dioxide and methane respectively) are very similar, they lead to considerable differences on the available space.



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Figure 2. Heats of adsorption Qst at 298 K for a) Ar, b) O2, c) CO2, d) N2, and e) CH4 molecules in nonblocked (red circles) and blocked (green circles) zeolites. Only adsorbent zeolites are displayed. For the sake of clarity, the size of red points is slightly larger than that of the green points.


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Figure 3. (a) Accessible Volume (AV) and (b) Accessible Surface Area (ASA) of the whole set of zeolites with a probe radius, rp, of 1.9 Å vs those with rp of 1.7 Å. These properties were calculated using Zeo++.79 The function x=y is depicted as a guide to the eye. Inset figures include the results for IRR and RWY, which have considerably larger accessible space, especially the latter.

We mentioned above that, by performing MD simulations, inaccessible zeolite pores could be readily detected. In order to identify in which cases this might be difficult, we show, in Figure 4, the differences in heat of adsorption between non-blocked and blocked zeolites (ΔQst

=

Qst,non-blocked -

Qst,blocked) for the various adsorbates, as a function of the PLD. The PLDs of the resulting non-porous zeolites when considering blocks (Table 1) were shown as green points on the x axis. As expected, most ΔQst values different from zero correspond to zeolites with PLDs smaller than the kinetic diameter of the adsorbates, but there is also a number of cases with larger PLDs, mainly ranged between 6 Å and 8 Å. These zeolites, with ΔQst ≠ 0, represent frameworks having either non-connected cavities or cavities connected through windows with small diameters (smaller than those of the guest molecules), but still with a channel system through which the adsorbates can diffuse. We note that these inaccessible pores are difficult to detect employing the diffusions obtained by MD simulations.



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Figure 4. Difference in heats of adsorption between non-blocked and blocked zeolites, ΔQst, for a) Ar, b) O2, c) CO2, d) N2, and e) CH4 molecules, as a function of PLD (red points). Green points in the x axis indicate the values of PLD of non-adsorbent structures after pore blocking (Table 1).


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As a final measure of the capability of these materials to be used in real-world applications, the influence of pore blocking on the molecular loading at finite pressures was also addressed. To do that, we compute the adsorption capacity, C (gas uptake at saturation pressures), of the whole set of zeolites with and without pore blocking for the specific case of methane. The results, shown in Figure 5, are depicted so that there is a monotonous decrease of the values of adsorption capacity for non-blocked zeolites. While this property is not affected for a number of zeolites, it is notably lower and even zero, as a consequence of the need to introduce blockings in various structures. The cases for low and zero valoes of C correspond to zeolites with low Qst values and non-adsorbent behavior respectively (see Table 1). As additional information, the zeolite with the highest adsorption capacity corresponds to RWY, followed by IRR, in agreement with the results shown in Figure 3.

Figure 5. Gas uptake at saturation pressures, C, for methane in non-blocked (red circles) and blocked (green circles) zeolites at 298 K, obtained by GCMC simulations. 17 ACS Paragon Plus Environment


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It is interesting to remark that the appropriate geometry-based calculation of pore blocking is crucial. As previously commented, Zeo++ in its current development is limited to study only molecules with circular cross-section. Erroneous adsorption data can thus be predicted for molecules not fulfilling this criterion. That is the case of benzene, which has a planar geometry, with a kinetic radius coincident with the ring diameter (5.85 Å) of the gme cages. For zeolites with these gme cages, namely GME, EON, MAZ, and OFF, and LTF, Zeo++ predicts that there is no need to introduce blocking, since the kinetic diameter is larger than the size of the such cages. In MC simulations, however, benzene fits very tightly in the resulting unblocked gme cages, as depicted in Figure 6. This fact is responsible for a strong affinity, which is in turn reflected in considerably high heats of adsorption. However, the diameter of the windows connecting the gme cages are of circa 3.2 Å size, and they are inaccessible for benzene in both diffusion experiments and MD simulations.

Figure 6. Snapshot for a single molecule of benzene in zeolite GME at 298 K, from MC simulations in the NVT ensemble.


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4. Conclusions On the basis of the industrial use of zeolites in gas storage and separation, an accurate computational prediction of heats of adsorption and gas uptakes is desirable. In particular, computational gas screenings offer relatively fast searching for candidate structures for targeted applications. In this regard, we confirmed the importance of adequate pore blocking when evaluating equilibrium adsorption through MC simulations. This is particularly relevant to avoid the spurious inclusion of inaccessible volumes, and the ensuing overestimation of the adsorption. A pseudo-flexible approach has been introduced to account for the instantaneous variations of pore window sizes, which helps providing a better agreement with experiments. It is worth noting that, even though MD simulations are more reliable to identify inaccessible pores than geometry-based computational pore blocking, MD studies incur in much higher computational costs. There is therefore room for the use of geometrybased selection of interesting structures, which could then be further studied with MD simulations. Overall, we strongly recommend the use of appropriate artificial pore blocking, calculated taking into account the sizes of the guest molecules, and including the diffusion-facilitating role of the framework flexibility via a pseudo-flexible approach. In the Electronic Supporting Information, we provide a set of files with the positions and radii of the blocking pseudoatoms, so that they can be easily used by all researchers. As shown in the case of benzene, refined methods must be developed to account for the blocking of molecules with non-circular cross-sections.

Electronic Supplementary Information: Files with the coordinates of the blockings that must be taken into account for all zeolites, considering the original and reduced radii of framework oxygen atoms (1.52 Å and 1.37 Å respectively) and for the three different considered probe radii: 1.7 Å, 1.8 Å, and 1.9 Å.



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Acknowledgements The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013) / ERC grant agreement n° 279520.

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