Metal Organic Frameworks: An interplay between experimental and theoretical information

Metal Organic Frameworks: An interplay between experimental and theoretical information BY FRANCISCO JOSÉ GALLARDO BASILE Final Project Submitted in partial fulfillment of the requirements for the Double Degree in Physics and Materials Engineering University of Seville June 25, 2019 Advisers: Professor Regla Ayala Espinar Professor Carlos López Cartes Abstract A theoretical investigation related to the different stability of HKUST-1 in water and ethanol is carried out. We present a comparative quantum mechanical study of the accuracy of different DFT approaches and basis sets versus MP2 and experimental evidences. In this study BP86, BP86-GD3(BJ) and M06 functionals with Pople, Dunning and Aldrich basis sets are considered. The influence of the basis sets happened to be a factor that has to be taken into consideration. Besides, it is concluded that the inclusion of dispersive corrections is needed for a proper description of HKUST-1-solvent interaction. M06/Def2SVPP is selected for describing our system because it presents the best results compared to experimental and theoretical values. Discrepancies between water and ethanol are due to the topology of the solvent molecules rather than the interaction energy with the MOF. From a experimental point of view, the use of different modulators to control the morphology and crystal size of HKUST-1 by using a procedure at room temperature is tested. Resumen Se ha llevado a cabo un estudio teórico sobre la establidad del HKUST-1 frente a agua y etanol. En dicho estudio, se presenta un análisis comparativo desde el punto de vista mecano-cuántico de la precisión de los diferentes métodos DFT y las diferentes bases con respecto a resultados ab-initio (MP2) y experimentales. Los funcionales BP86, BP86-GD3 (BJ) y M06 y las bases de Pople, Dunning y Aldrich se contemplan en este trabajo. La influencia de la base elegida desmostró ser un factor importante y debe ser considerada en datalle. Además, se hace necesario la inclusión de correcciones dispersivas para una descripción adecuada de la interacción HKUST-1-disolvente. M06/Def2SVPP se selecciona para describir nuestro sistema debido a que presenta los mejores resultados en comparación con los valores experimentales y teóricos. Se concluye que las discrepancias entre el agua y el etanol se deben a la topología de dichos disolventes y no a la energía de interacción con el MOF. Desde un punto de vista experimental, se pone a prueba el uso de diferentes moduladores para controlar la morfología y el tamaño cristalino del HKUST-1 mediante un procedimiento a temperatura ambiente. Contents 1 Introduction 1 1.1 Metal-organic frameworks (MOFs) . . . . . . . . . . . . . . . . . . . . . . . . 1 1.1.1 Mainfeatures............................... 1 1.1.2 Applications ............................... 2 1.1.3 Methodsofsynthesis........................... 4 1.1.4 HKUST-1................................. 6 1.2 Scope ....................................... 7 2 Methods 8 2.1 Computationalchemistry............................. 8 2.1.1 Hartree-Fock and post-Hartree-Fock methods. . . . . . . . . . . . . . . 8 2.1.2 Density functional theory . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.1.3 Basissettypes .............................. 11 2.1.4 Basis set superposition error . . . . . . . . . . . . . . . . . . . . . . . 12 2.2 Experimental ................................... 14 2.2.1 Procedure................................. 14 2.2.2 Characterization ............................. 14 3 Results & discussion 15 3.1 Smallmodel.................................... 17 3.1.1 Interaction with H2Omolecules ..................... 18 3.1.2 Interaction with ethanol molecules . . . . . . . . . . . . . . . . . . . . 26 3.2 Bigmodel..................................... 27 3.3 Experimental ................................... 29 4 Conclusions 31 References 33 1 Introduction 1.1 Metal-organic frameworks (MOFs) Metal-organic frameworks, known as MOFs, are a novel class of microporous crystalline materials consisting of a regular array of metal nodes (ions or clusters) linked by multidentate organic ligands. They can be considered as hybrid compounds in the sense they are a combination between organic and inorganic species that can lead to materials with unique properties [1]. An illustrative example is shown in figure 1. Figure 1: MOFs are made up by organic linkers (organic building units) and metallic clusters (inorganic building units) [2]. These materials have drawn enormous attention during the past decades due to their main features and versatile applications [3][4]. 1.1.1 Main features The main features of MOFs can be summarized as follows: Simple design. In most cases, it is possible to use simple equipment, and commercial reagents and solvents [5]. High versatility. The number of different ‘components’ available to synthesize a new MOF from is almost unlimited. This is due to the possibility of using the whole periodic table to select a metal and the rich organic chemistry to choose or modify an organic linker, and even develop a new one. Therefore, there are wide opportunities for development of materials with tailored properties and adjustable composition. Additionally, MOFs do not have to contain only one type of metal or linker. All these specifications considerably affect the properties of the 1 final material. The investigation of the role played by all these variables is still in progress. Tunable pore size and a modifiable pore surface. The choice of the initial building components makes possible to vary some parameters, such as the pore size (increasing pore diameter up to 98 Å) [6], as well as the specific surface area (up 7140 m2/g) [7]. In this way according to the final goal, the pore size can be very different. Stability. MOFs present to certain extent thermal stability (raging from 200oC to 500oC) [8]- [11] as they are composed by strong bonds (e.g., C-C, C-H, C-O and M-O). However, it has been a ferocious challenge to make them chemically stable because link-displacements reactions have a great tendency to occur when the MOFs are treated with solvents over extended period of time (days). Nonetheless, some MOFs with high chemical stability such as pyrazolate-bridged MOFs (stable for 2 weeks in a wide range of aqueous solutions at 100oC) have been reported [12]. The promising advances on chemical stability are expected to enhance their performance in the capture of carbon dioxide from humid flue gas and broaden MOFs’ application to water containing processes. Open metal sites. Some MOFs present molecules coordinated to metal nodes that can be removed without destroying the whole structure despite the change of the coordination number. This fact causes unsaturated sites, which could interact with guest molecules (adsorbents or reagents). These sites are called "uncoordinated metal sites" or "open metal sites". Functionalization. MOFs can be functionalized to modify or improve their properties respect to a given application. The functionalization can be done during the synthesis or after that. Likewise, it can affect the ligand, the metal or both of them simultaneously. 1.1.2 Applications The use of aforementioned MOFs features allows them to participate in many applications such as: ion exchange, adsorption and storage of gases, separation processes, drug release processes in medicine, sensors and catalytic processes among others [13]. Gas storage applications built on the porosity and specific interactions with MOFs are currently a hot topic in the field. Nevertheless, cautious optimism must be our stand because gas storage accomplishments have been made on small scale lab experiments with pure gases or selected gas mixtures. It still remains a challenge to make the transition from laboratory to in- 2 Figure 2: Typical properties and applications of MOFs. Metal-organic frameworks exhibiting the lowest and highest values for the indicated property, and those reported first for selected applications, are shown [1]. dustrial scale taking into account possible issues like the heat dissipation upon gas absorption, the fast kinetics and the stability upon water vapor and reactive gas impurities. Fuel cells in mobile applications is a promising way to avoid carbon consumption as a source of energy and therefore avoid problems arising from CO2emission. The use of MOFs as inexpensive proton-conducting membranes for fuel cells represents a new direction in MOF research due to their tunable pore size and functionality as well as their chemical and thermal stability. MOFs have also the potential to be used in medicine applications as drug delivery. It has been reported different MOFs which were able to absorb anti-tumor and anti-AIDS active agents. The size and the functionalization of the pore were shown to control the storage capacity. Catalysis is of continuous importance. Convenience of MOFs as catalysts are seen in the simple separation of a heterogeneous catalyst, the adjustment of the pore size to yield selectivity, regioselectivity and/or shape and size selectivity by building an convenient environment around the catalytic center in the restricted space available [14]. 3 1.1.3 Methods of synthesis The primary objective in MOF synthesis is to establish the procedure that leads to defined inorganic building blocks without decomposition of the organic linker. At the same time, the kinetics of crystallization must be convenient to allow nucleation and growth of the desired phase [15]. At the beginning, the prime focus was on the assembly of organic and inorganic building blocks in order to form porous structures. Since weak interactions between the building blocks were expected, rather mild reaction conditions were applied. At the same time, chemists working on the synthesis of zeolites began to look at the use of organic molecules not only as structure-directing agents but also as reactants to be incorporated in as a part of the framework structure. For this purpose, elevated reaction temperatures are commonly employed. Coordination chemistry has accounted for introducing electrochemical and mechanochemical synthesis. On the other hand, from zeolite chemistry, the notions of solvothermal reaction conditions, structure-directing agents and mineralizers as well as microwave-assisted synthesis or steamassisted conversion have also been introduced [16]. Why are different syntheses methods necessary for MOFs? Starting from the same reaction mixtures, they can lead to different MOFs. They may have an impact on reaction time, yields, and/or particle size and morphology. Besides, appropriate methods for large-scale production are also required. In the last 20 years, different synthesis methods have been applied such as room temperature synthesis, conventional electric heating, microwave heating, electrochemistry, mechanochemistry, and ultrasonic methods. These are shown in figure 3. Conventional synthesis is carried out by conventional electric heating without any parallelization of reactions. Depending on the reaction temperature, conventional synthesis can be distinguished between solvothermal (the solvent and the precursor are heated in a closed system at temperatures above the boiling point of the solvent, this increases the pressure, facilitating the interaction between the solvent and the precursor during the synthesis) and nonsolvothermal (it takes place below or at the boiling point under ambient pressure). The last one can be then subdivided into the ones which take place at room-temperature and the ones at elevated temperatures. Combination of metal ions as salts and the linkers usually in water or in an organic 4 Figure 3: Overview of synthesis methods, possible reaction temperatures and final reaction products in MOF synthesis [15]. solvent is how MOFs are usually prepared [17]. The required energy for the adequate reactions to occur can be introduced through other mean such as by an electric potential, electromagnetic radiation, mechanical waves (ultrasound), or mechanically. The duration, the pressure and the energy per molecule that is introduced into a system strongly depend on the energy source that it is used. For example, it has been reported the synthesis of MOFs using mechanochemistry, that is, by grinding two or more solids using a mechanical ball mill and therefore avoiding the use of solvents [18]. Another example was reported when MOF-5 was synthesized by sonochemistry in just 30 minutes compared with the conventional solvothermal syntheses which takes around 1 day [19]. 5 1.1.4 HKUST-1 [Cu3(BTC)2(H2O)3] (where BTC is benzene-1,3,5-tricarboxylate) was first prepared in 1999 at Hong Kong University of Science and Technology in 80 percent yield [20]. HKUST-1 is the nickname that was given to this new compound based on its place of origin followed by a number. HKUST-1 is one of the first 3-D MOF. It consists of Cu2units coordinated by four carboxylate groups in the well-known paddle-wheel structure of copper acetate. It crystallizes with the formation of a highly porous cubic structure with a complicated 3D network of channels. Along the a-axis there are large square channels of 9x9 (ÅxÅ) (see figure 4). HKUST-1 is stable up to 240oC and can be considered a metal open site MOF. Thus, water molecules coordinating the copper atoms can be eliminated thermally without loss of the structural integrity and exchanged by other ligands [20]. (a) (b) Figure 4: Two views of the packaging diagram with the cubic unit cell of 3D-[Cu3(BTC)2(H2O)3]·∼10H2O (HKUST-1, a = 26.34 Å[20]) to illustrate the zeolite analogy of this highly symmetric and porous framework. The disordered water molecules in the pores are not shown, nor are the H atoms on the aqua ligands and on carbon in the packing diagrams. The different objects in this figure are not drawn to scale. HKUST-1 has been widely studied from both experimental [21]-[23] and theoretical [24]- [29] methods. As a rule, the former methods have been focused on improving its properties for a given application during the synthesis procedure or in a subsequent step. The latter ones have been trying to explain the mechanism of interaction between HKUST-1 and hosting molecules. However, far less attention has been paid in the description of its stability in different media. It 6 the intermolecular interactions. BSSE becomes more evident for smaller basis sets. It can be explained as follows: as monomer A approaches monomer B, the dimer can be badly stabilized because monomer A utilizes the extra basis functions from monomer B and vice-versa. Therefore, this effect has to be considered when calculating a property such as binding energy or interaction energy. ∆Eint(AB) = E(AB|ab AB)−E(A|a A)−E(B|b B)(5) where Eint(AB)represents the dissociation energy of dimer AB, E(AB|ab AB)represents the total energy of the dimer AB when optimized within the dimer itself and calculated in the presence of basis sets for A and B, E(A|a A)represents the total energy of the monomer A when optimized isolated by itself and calculated in the presence of basis sets for A and E(B|b B) represents the total energy of the monomer B when optimized isolated by itself and calculated in the presence of basis sets for B. Consequently, a generic term E(X|z Y)represents the total energy of X optimized in the geometry z using the basis sets for Y. Equation 5 can be corrected by estimating how much monomer A is badly stabilized by the extra basis functions from monomer B and vice versa as ∆EBSSE(A) = E(AB|ab A)−E(A|a A), ∆EBSSE(B) = E(AB|ab B)−E(B|b B), (6) where we are evaluating the energy of monomer A in the dimer basis, placing all the basis functions of monomer B on the atomic centers of monomer B while ignoring the electrons and the nuclear charges of monomer B (and likewise for monomer B). Therefore, the corrected interaction energy is calculated using the Counterpoise (CP) method [44] as ∆ECP int (AB) = E(AB|ab AB)−E(A|ab AB)−E(B|ab AB)(7) where ECP int (AB)is the CP-corrected interaction energy and it has been assumed that the geometries of monomers A and B do not change significantly as they approach each other [45]. All calculations have been performed with gaussian G09 [46] and G16 [47] program. 13 2.2 Experimental 2.2.1 Procedure All reagents were purchased commercially and used without further purification. A room temperature synthesis was carried out to obtain HKUST-1. To prepare sample 1, BTC sodium aqueous solution was prepared by dissolving H3BTC (1.78g) in NaOH solution (81mL, 0.38M). Cooper aqueous solution was obtained by dissolving Cu(NO3)2·3H2O (3.66g) in 80mL of distilled water. Then the cooper solution was added dropwise to the BTC solution under stirring. Stirring remained for 24h. Blue precipitate was subsequently collected by centrifugation, washed with ethanol several times and dried in oven overnight. Sample 2 was prepared as sample 1 but KBr (7.85g) was added to BTC solution as a modulator. In Sample 3, BTC solution was prepared by dissolving H3BTC (1.78g) in 50mL of ethanol and 8 mL of (CH3CH2)3N (triethylamine or TEA), being the TEA the modulator. 2.2.2 Characterization Powder diffraction is an experimental technique for the study and analysis of materials, based on the phenomenon of X-ray diffraction by crystalline solids. The X-rays are scattered by the electrons that surround the atoms when their wavelength is of the same order of magnitude as the atomic radius. The X-ray beam coming out after this interaction encloses information about the position and type of atoms found in its path. The measurements have been made in a powder diffractometer Panalytical X’PERT PRO with automatic sample loader at the Material Science Institute of Seville (ICMS). The diffractograms have been registered in a range 2θof 5o-60o, a step of 0.02oand acquisition time of 200 seconds per point. Physical adsorption is a special type of adsorption which is described as the accumulation or deposit of material (adsorbate) in a plane or surface (unlike the absorption that is a volumetric process). Nitrogen adsorption isotherms were recorded at 77K in a Gemini V-device 2365 // V1.00 of Micromeritics at the Inorganic Chemistry Department of the Faculty of Chemistry. Before gas adsorption, the samples were activated at 200 oC in N2flow for 1 hour. This produces the partial or total loss of water or solvent that the samples could contain (blocking the adsorption centers during the analysis). Surface areas were determined by the BET method [48]. 14 3 Results & discussion Our aim is to understand the different behavior of HKUST-1 in water and ethanol in terms of computational chemistry, namely, on a quantum mechanical study. In the case of stability in a given solution, the quality of the model directly derives from the accuracy with which one can describe the microscopic interactions between the solvent and the MOF framework. To this purpose the first decision that must be taken is the selection of the most appropriate computational approach for an accurate modeling of solvent-HKUST-1 interactions. This step is not straightforward because at quantum mechanical level it is not possible to consider the extended structure of HKUST-1. Therefore, MOFs need to be represented by a cluster model that relies on a finite number of atoms centered at a region of interest (see figure 6). Figure 6: HKUST-1 building unit. A small model, where dangling bonds are saturated by hydrogen atoms is the simplest model that can represent a MOF and enables the application of high-level computational approaches and large atomic centered basis sets. Unfortunately, the electronic environment of the atoms in the cluster can be affected by spurious effects related to the limited size of the model. This can be overcome by considering larger cluster, which will require a concomitant reduction of the quality of the computation approach, or by embedding the small model in a region of surround- 15 ing atoms that are treated with a low level computational approach. Clearly, a compromise between accuracy and feasibility must be reached. Bearing in mind all these considerations and the computational facilities available for this project, we decided to start from a small model that can represent HKUST-1 e.g. by considering the [Cu2(HOOC)4] cluster model shown in figure 7b where the cooper atoms present an environment similar to the one in the MOF and all atoms are treated at the same high level approach. (a) (b) Figure 7: a) Representative structure of HKUST-1. b) Simplified model (small) where the green part shown before is replaced by H. Once the model system has been chosen, it is also required the selection of the level of computation and the quality of the basis sets. To approach this proposal, it is necessary to arrange again an agreement between accuracy and computational cost. Density functional theory (DFT) computations are usually used for this purpose. Post-HF methods can also be employed to evaluate interaction energies with high accuracy. However, because of the unfordable scaling with the size of the system, they can hardly be used directly to compute interaction energies in MOF model systems. As a rule, the test of a computational approach is made by direct comparison with accurate experimental information when it is available or high level ab initio methods when this information is missing. In the case of the hydrated MOF HKUST-1, single crystal structure analysis by Chui et al. [20] supplies a Cu −Ow (Cu-Owater) distance of 2.165 ±0.008 Å while Prestipino et al. [49] estimate a value of 2.19 ±0.02 Å from EXAFS. Nevertheless, additional 16 information about the interaction of the water molecule with the remaining atoms of the MOFs is not easily obtained by experimental evidences. The use of theoretical results obtained at high level of computation can supply additional information to test a given level of calculation. 3.1 Small model Initially, HF and DFT(BP86) methods were applied with three different Pople basis sets; 6-31G, 6-31+G* and 6-31++G**. All of them are DZ split-valence basis sets but 6-31+G* includes polarization and diffuses functions only in the heavy atoms while 6-31++G** does it in all atoms. As a first estimation, only the MOF was taking into account, and no interaction with other molecules were considered. The structure has been taken from CIF file [50]. The optimization of the structure at BP86 method showed little deviation from experimental result while HF method showed strong deviation as can be seen in table 1. The Cu −Cu distance was taken as a measurement of distortion. No matter the basis sets HF presents a significant (up to 15.57 %) lengthening of the distance between the Cooper atoms from the experimental value while DFT method barely differs. These results are confirmed graphically in figure 8 for HF. Experimental HF/ 6-31G HF/ 6-31+G* HF/ 6-31++G** bp86/ 6-31G bp86/ 6-31+G* bp86/ 6-31++G** Cu-Cu (Å) 2.52 2.85 2.91 2.91 2.51 2.51 2.50 Error (%) - +13.23 +15.57 +15.53 +0.35 +0.50 +0.69 Table 1: Comparison of the Cu −Cu distance to show deviation from experimental result. (a) (b) Figure 8: Two different views (a,b) of the results when performing the optimization of the small model using HF. 6-31G, 6-31+G* and 6-31++G** basis sets are used, all of them give rise to similar graphical results where one of the cooper atoms forms a planar structure with the 4 adjacent oxygen atoms while the other Cu moves away. 17 3.1.1 Interaction with H2O molecules Optimizations considering HKUST-1 + 2 water molecules taken into account. The water molecules were located to interact with the Cu atoms maximizing ion-dipole interactions, that is, Cu, Ow and Hw atoms being aligned in the same plane (see figure 9). Figure 9: Starting position 1. A strong electrostatic interaction between the cooper cation in the HKUST- 1 and the water molecule (which has a dipolar moment) is conjectured. The analysis of the optimized structures (figure 10) shows that again HKUST-1 is no longer stable at HF level even when accommodating the two water molecules (figures 10a and 10b). Therefore, HF level can be discarded for this study. However, BP86 results are consistent with the experimental evidences. However, there is an increase in the Cu −Cu distance when water molecules are considered and small deviations from the experimental structure (see table 2). (a) HF/6-31G (b) HF/6-31+G* & 6-31++G** (c) BP86 for the 3 basis sets. Figure 10: Optimizations made from position 1. 18 MOF MOF + 2 H20Experimental BP86/Basis Set 6-31G 6-31+G* 6-31++G** 6-31G 6-31+G* 6-31++G** Cu-Cu (Å) 2.51 2.51 2.50 2.64 2.59 2.59 2.52 Error (%) -0.40 -0.80 -0.80 +4.76 +2.78 +2.78 - Table 2: Comparison of the Cu −Cu distance to show deviation from experimental results. Two situations are taking into account: MOF by itself and interacting with 2 molecules of water. This lengthening is more important for the 6-31G basis set where no polarization and diffuse basis are considered. The water molecules tilted to interact with the Cu atoms and with carboxilate groups simultaneously (see figure 10c). This means that the stabilization of HKUST-1- water is due to both electrostatic and dispersion interactions. For a better understanding of the structural description, figure 11 shows the parameters described in the text. Figure 11: Cu −Ow measurements corresponds to the average distance between atoms 3-4 and 5-6. Hw −Omeasurements corresponds to the average distance between atoms 22-14 and the others in a similar position such as 24-15. d Cu −Cu −Ow corresponds to the average angle d 5−3−4and d 3−5−6. d Cu −Ow −Hw corresponds to the average angle d 3−4−24 and the others in a similar position such as d 5−6−22 and will also be referred as the tilt angle. Note that if the atoms belong to the water molecules, the atom symbol is followed by w from water. The standard error of the mean of all measurements taken was in all cases negligible so that the average value is representative. Table 3 shows interactions energy and BSSE calculated as ∆Eint (MOF −2·H2O) = E(MOF −2·H2O)−2E(H2O).(8) BSSE =ECP int −Eint (9) 19 CP-Corrected interaction energy is also included in table 3. The effects of the basis set can be analyzed. As we include polarization and diffusion on all atoms (6-31++G**), lower interactions energies are obtained. Nevertheless, there is not much difference when including this effects only on heavy atoms(6-31+G*) compared to 6-31++G**. Additionally, the BSSE is more important for 6-31G and similar for 6-31+G* and 6-31++G** basis sets. Besides, the appearance of the interaction between the hydrogen atoms of the water molecules and carboxilate groups via hydrogen bond precludes the use 6-31G because it can not describe properly the interaction. Method Basis Set ECP int (kcal/mol) Eint (kcal/mol) BSSE (kcal/mol) BP86 6-31G -17.51 -38.30 20.79 6-31+G* -15.54 -20.56 5.02 6-31++G** -15.23 -19.56 3.93 Experimental Value [51] -25.51 - Table 3: Interaction energies calculated when optimizing from position 1. The appearance of the tilt of the water molecular suggests us to also consider the direct interaction of water molecules with the carboxilate groups as initial position. For this purpose, starting position 2 (see figure 12a) is considered. The optimized structure is displayed in figure 12b and can be explained as an intermediate situation between the initial configuration and the previous minimum, that is, one water molecule interacting via hydrogen bond with the carboxylate group and the second one migrated towards the copper atom. The interaction energies (see table 4) indicate that this situation is less stable than the first one. (a) Starting position 2. (b) Optimized structure. Figure 12: a) Starting position 2 and b) Optimized structure for both bp86/6-31+G* and bp86/6-31++G** basis sets. 20 Starting Position 1 2 Method/Basis Set BP86/6-31+G* BP86/6-31++G** BP86/6-31+G* BP86/6-31++G** ECP int (kcal/mol) -15.54 -15.23 -12.02 -11.86 Table 4: Interaction energies calculated for both starting positions. A third position was also considered (see figure 13). The optimized structure evolved to that obtained from position 1. Figure 13: Starting position 3. Results were identical as for position 1. In view of this, water molecules interacting simultaneously with copper atoms and carboxilate groups (optimized position 1) are the best description for the HKUST-1-water interaction. Therefore, this position will be used from this point forward. Bearing in mind the slight differences between 6-31+G* and 6-31++G** and the computational cost of optimizations with both basis sets (see table 5), we select the use of polarization and diffuses only on heavy atoms henceforth. Cu-Cu (Å) Error (%) Cu-Ow (Å) Error (%) ECP int (kcal/mol) Error (%) Time (min) BP86 6-31+G* 2.59 +2.78 2.30 +5.02 -15.54 35.79 243 6-31++G** 2.59 +2.78 2.30 +5.02 -15.23 37.07 319 Experimental 2.52 - 2.19 - -25.51 - - Table 5: Comparison of both basis sets with experimental values. Last column corresponds to the CPU time taken for the optimizations. 21 The comparison of these results with experimental estimations (Eint=-25.51 kcal/mol [51]) indicates that there is an underestimation of the interaction energy at BP86 level (see table 3). These differences can be due to several factors: 1)distortion of the MOF structure, 2)poor description of the interaction due to their partial dispersive character of the interaction, 3)effect of the basis set and 4)size of the model. The effect of the distortion from experimental structure can be easily evaluated by constraining the HKUST-1 model structure and only optimizing the interaction with the water molecules. This way a more realistic comparison with the experimental results can be done due to only the interaction with water molecule and the experimental model structure. These results are shown in table 6. The Cu −Ow distances and the tilt angle barely change by the constraint. The interaction energy decreases to -17.76 kcal/mol (CP-uncorrected) and -12.87 kcal/mol (CP- corrected). The underestimation remains in the constrained structure. Method/Basis Set Constraint Cu-Ow (Å) d Cu-Ow-Hw (o)ECP int (kcal/mol) Eint (kcal/mol) BSSE (kcal/mol) BP86/6-31+G* - 2.30 99.30 -15.54 -20.56 5.02 MOF Structure 2.34 93.39 -12.87 -17.73 4.86 Experimental 2.19 - -25.51 - Table 6: Comparison between BP86/6-31+G* with and without constraining the MOF structure results and experimental values. A second factor that can be evaluated is the fact that DFT methods do not describe properly the dispersion interactions and they must be corrected to improve its evaluation. Experimental data can not give information of this component because the tilt angle of the water can not be estimated. One can take advantage of benchmark calculations to estimate the importance of dispersion interactions in the description of solvent-MOF systems. MP2 approach is quite often used as a benchmark for the cluster models of MOF ([52]-[54]) and it is our election in this study. Aug-cc-pVDZ, which was developed as previously commented for post-HF methods, is decided to be employed. The structure of the cluster model was constrained to the experimental one to evaluate the interaction with water molecules. The optimized structure of the HKUST-1 cluster model + 2 water molecules constraining the MOF structure for MP2/Aug-cc-pVDZ is presented in figure 14. The optimized results are collected in table 7. It can be seen that the tilt angle d Cu −Ow −Hw increased when optimizations are carried out with MP2. Besides, CP-corrected interaction energy and Cu −Ow distance resemble the experimental values. A better description of the water- 22 3.3 Experimental HKUST-1 was prepared by direct precipitation method in a solution phase at room temperature. Fig 17 shows PXRD patterns of the as-prepared samples as long with the theoretical peaks of xray diffraction for HKUST-1. All the theoretical diffraction peaks from pure phase of HKUST-1 can be indexed in sample 1 although other crystalline phases are present. Sample 2 (KBr) and 3 (TEA) do not present diffraction peaks from pure phase of HKUST-1, meaning that HKUST-1 has not been obtained. The addition of a modulator (either KBr or TEA) in room temperature synthesis does not give rise to the desired crystalline phase. An amorphous phase is also present in sample 3 (TEA). Figure 17: PXRD patterns of theoretical HKUST-1 and samples prepared. The adsorption capacity of the samples has been studied by the analysis of N2isotherms at 77K (see figure 18). Sample 1 shows a characteristic type I sorption isotherm, which is typical for microporous materials. Sample 2 does not present porous behavior. Sample 3 (TEA) isotherm is of type II which corresponds to mesoporous material. Sample 1 presents the highest adsorption capacity followed by sample 3 and sample 2 respectively. 29 Figure 18: Adsorption isotherms of N2for the samples prepared. The BET surface area of these samples are shown in table 14. Sample 1, where HKUST-1 is present, has the highest surface area. Nevertheless, its estimated specific surface area is lower than reported values (Peng et. al [55] obtained a value of 1850 m2/g for the BET surface area of HKUST-1 while Moosavi et al. [56] achieve a value of 2045 m2/g). This can be explained due to the presence of additional phases that decrease the adsorbent capacity of the sample 1. Sample Specific surface area (m2/g) 1 640 2 (KBr) 16 3 (TEA) 120 Table 14: Brunauer-Emmett-Teller (BET) surface area calculated for each sample. The aim of controlling the morphology and the crystal size by adding modulators in the synthesis at room temperature was not successful. At this moment, it is necessary to point out that solvothermal methods would have been our first choice but the reactors were not available during the completion of this work. 30 4 Conclusions Regarding the theoretical study, several conclusion can be obtained: •The small model of HKUST-1 is not stable at HF level even when accommodating the two water molecules. •BP86 gives a first description of the system although it greatly underestimates interaction energy as compared with the experimental one. •The inclusion of polarization and diffuse basis sets leads to an improvement of the results. The difference between including them on all atoms (6-31++G**) or just on heavy atoms (6-31+G*) was not significant, so basis set 6-31+G* was selected to continue our study in order to maintain an agreement between accuracy and computational cost. •Three different starting positions were considered for describing HKUST-1-water interaction. Position 1 and 3 led to the same optimized structure, that is, a situation where the water interacts simultaneously with the copper atoms and the carboxylate groups. Position 2 resulted in a less stable minimum that can be described as an intermediate situation where one water molecule interacts with the Cu and the carboxylate groups and the other only interacts with the carboxylate groups. Therefore, position 1 was taken as the starting point for our study. •The consideration of different functionals and basis sets indicate that the inclusion of dispersive corrections is mandatory to describe MOF-solvent interaction at DFT level. Aug-cc-pVDZ and Def2SVPP showed to improve the results compared to 6-31+G*. Besides, BP86-GD3(BJ) and M06 gave rise to better results than BP86. •At DFT level, Def2SVPP basis set presents the largest BSSE, followed by 6-31+G* and Aug-cc-pVDZ. BSSE obtained for MP2/Aug-cc-pVDZ is larger than the DFT estimations, as expected for a comparison between ab initio and DFT methods. •M06/Def2SVPP is the best combination method/basis set for accurately describing our system, precisely optimizing the structure and properly calculating energies at the same time. 31 •The comparison between the small and big model indicated that our results are size consistent. •The different stability of HKUST-1 in water and ethanol can not be explained in terms of interaction energy but a study about the different topology of the solvent molecules could give insight into the behavior with each solvent. With respect to experimental results, it can be concluded that: •HKUST-1 can be obtained by using a procedure at room temperature. 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