Comment on âDatabase for CO2 Separation Performances of MOFs

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Comment on “Database for CO Separation Performances of MOFs Based on Computational Materials Screening” Pezhman Zarabadi-Poor, and Radek Marek ACS Appl. Mater. Interfaces, Just Accepted Manuscript • DOI: 10.1021/acsami.8b15684 • Publication Date (Web): 28 Mar 2019 Downloaded from http://pubs.acs.org on March 28, 2019

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ACS Applied Materials & Interfaces

Comment on “Database for CO2 Separation Performances of MOFs Based on Computational Materials Screening”

Pezhman Zarabadi-Poor*,†, Radek Marek *,†, ‡

†

CEITEC – Central European Institute of Technology, Masaryk University, Kamenice 5, CZ-

62500 Brno, Czechia ‡

Department of Chemistry, Faculty of Science, Masaryk University, Kamenice 5, CZ-62500

Brno, Czechia

* Email: P.Z.: [email protected] R.M.: [email protected]

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High-throughput computational screening has attained a unique position in predicting the capabilities of metal-organic frameworks (MOF) for the storage and separation of various gases.1 The top-performing MOFs for the storage of methane2 and oxygen3 and for the capture of chemical warfare agents4 have been identified, synthesized, and experimentally validated – saving the enormous amount of time that would be needed for experimental trials. Over the years, databases2,5–10 covering a wide range of physical, chemical, and topological aspects have been developed to take advantage of in-silico screening of MOF structures. Most recently, Moghadam et al.5 have reported a database that uses seven criteria to detect MOFs among the approximately one million crystal structures deposited at the Cambridge Crystallographic Data Centre (CCDC) – abbreviated as CSDMOF in this account. The last step in preparing crystal structures for computation deals with the removal of solvent molecules, which may be freely present in the structural networks or bound to the metal centers. Although the authors of CSDMOF provide a handy Python API script5 that can automate and ease the solvent-removal procedure, users are advised to carefully eliminate solvent molecules in order to obtain clean (solvent-free) structures. They recommend inspecting structures to ensure that the solventremoval procedure “does not significantly affect the framework integrity”.5 They also emphasize that because the geometry is not optimized after the cleaning prosses, “the assumption to automatically remove them [solvent molecules] is not always correct”. It is noteworthy that similar concerns were also highlighted in another MOF database, CoRE MOF, previously constructed from experimental structures.7 Several studies11–15 (including the primary focus of this account11) have attracted our attention because CSDMOF has been used to perform large-scale screening that discovered promising MOFs for a wide range of applications. The outcomes of the high-throughput studies are very useful for the in-silico design of new MOFs or the synthesis of promising materials


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that have been identified. However, our structural inspection of the outstanding structures in these five papers11–15 revealed interesting points that should be further analyzed and discussed. In the following sections, we demonstrate that if the Python API script is applied without heeding the advice given by Moghadam et al.5, the resulting structures may suffer from a lack of structural integrity, the presence or absence of mobile charge-compensating ions, or missing hydrogen atoms, and consequently may deliver implausible results and rankings. To demonstrate our scientific point of view concisely and concretely, we have selected a few structures exhibiting rather serious problems and we discuss them in this contribution. We express our views about the computational procedure and indicate possible steps where errors might occur. We believe that our analysis and discussion will be useful for other scientists working in this field of research. On the retention of structural integrity following in-silico removal of the solvent Our reinvestigation of the 30 structures ranked as the top performing MOFs for the separation of CO2/N2 and CO2/CH4 by Altintas, Keskin, and co-workers (AK)11 as well as ones present in their on-line database16 and discussed in the text, indicates that several of them lack structural integrity when subjected to removal of the “solvent”. The following four examples (CSD reference codes MIDXON17, VIHHIE18, SUFSUH0119, and AQEKUD20) demonstrate the need to scrutinize the top-ranked MOFs before recommending structures as promising. To validate and compare our data with those previously reported, we followed closely the published procedure11 to obtain the CIF files and then calculated the pore limiting diameter (PLD) and the largest cavity diameter (LCD) for each structure using Zeo++ (version 0.3).21 We also calculated relevant selectivity values for the systems. All of the results are summarized in Tables S1-S3 (for simulation details, see Supporting Information).



MIDXON. In the original paper,17 Welk at al. reported this compound (Figure 1a) as [Cu(NC5H5)4VOF4][Cu(NC5H5)4(H2O)VOF4]·H2O with PLD and LCD values of 1.11 and 2.30 Å, respectively. AK11 identify this structure as one of the best for the CO2/CH4 separation. However, their reported PLD (6.51 Å) and LCD (7.74 Å) parameters correspond to the structure shown in Figure 1b, obtained by removing the pyridine and water ligands. This “solvent”-free structure, obtained by using the Python API script to MIDXON, clearly does not resemble any chemically meaningful system. As an alternative approach, we cleaned the structure by removing only the water molecules and calculated the PLD and LCD to be 1.17 and 2.85 Å, respectively. Concludingly and in our opinion, this correct form of MIDXON should have been eliminated after scrutinizing in the final step of evaluation.

Figure 1. a) Structure of the original MIDXON (PLD: 1.11 Å, LCD: 2.30 Å)5, b) Structure of MIDXON (PLD: 6.51 Å, LCD: 7.74 Å) obtained by using the Python API script to remove the “solvent”. (color code: Cu: dark orange, N: light violet, C: dark grey, F: light green, V: light grey, O: red, H: white). VIHHIE. This structure has been mentioned as an MOF with a high level of performance for CO2/CH4 separation11 and also reported separately in other publication by the


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same group as the most promising membrane for CO2/N2 separation.12 Margraf et. al.,18 introduced VIHHIE as a mixed-valence compound with the formula [Li(THF)4]Cu2Br4, comprised of infinite chains of anionic [Cu2Br4]- units separated by [Li(THF)4]+ cations (Figure 2a). We found that the Python API script treated the THF molecules coordinated to Li+ (highlighted in blue in Figure 2b) as free solvent and removed them from the structure. The resultant “cleaned” VIHHIE contains only unbound Li cations in the spatial void between the Cu2Br4- chains (Figure 2c). An important question is how the mobile charge-compensating Li cations would behave in realistic simulations if there were no THF moiety to serve as a spatial barrier to cation-anion attraction. As the coordination chain carries a negative charge, Li cations would leave their positions in the original THF-containing system and migrate toward their electronic opposites. To check the presumed rearrangement of the system upon removal of THF, we optimized the geometry of this structure using the Forcite module of Materials Studio22 (for details, see Supporting Information) and found, as expected, that the Li cations moved toward the anionic [Cu2Br4]- chains (Figure 2d).

Figure 2. a) Structure of VIHHIE ([Li(THF)4]Cu2Br4) as deposited into CSD, b) Structure of VIHHIE ([Li(THF)4]Cu2Br4) as deposited in the CSD with all of the THF molecules that are coordinated to Li+ highlighted in blue, c) “Cleaned” VIHHIE obtained from the CSD structure 5 ACS Paragon Plus Environment


by removing the “solvent” using the Python API script, d) “Cleaned” VIHHIE structure with optimized geometry. (Color code: Li: violet, Cu: dark orange, Br: orange, C: grey, O: red, H: white). SUFSUH01. This compound has been reported19 as catena(bis(μ4-L-glutamato)octaaqua-di-erbium tetraperchlorate trihydrate), containing protonated amine groups on the glutamate moiety and perchlorate counter anions. Clearly, both the original structure and that with the “solvent” removed (shown in Figures 3a and 3b, respectively) are missing hydrogen atoms from their structures as well as mobile charge-compensating anions. The issue of missing hydrogen atoms was also noticed in the CoRE MOF database, where Chung et al.7 automatically added hydrogens to 63 of structures they identified. Although the developers of CSDMOF were seeking to provide a versatile tool for generating the most recent MOF database and, therefore, did not correct these problems with the structure, they did supply a resource datasheet23 which contains relevant information and should be used. SUFSUH01 can be used for computer simulations only after adding the hydrogen atoms and perchlorate ions and optimizing their positions. We used an automatic simple procedure in the program Mercury to add the missing hydrogen atoms (Figure 3c and Figure S1) just to check the resulting pore diameters (Figure 3c), but we did not repeat the gas-adsorption simulation on this H-added SUFSUH01 as it is still missing the perchlorate counter ions.


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Figure 3. a) Structure of the original SUFSUH01 (PLD: 3.45 Å, LCD: 4.87 Å), b) Structure of SUFSUH01 (PLD: 5.31 Å, LCD: 6.67 Å) obtained from CSDMOF by using the Python API script to remove the “solvent”,5 and c) Structure of SUFSUH01 with hydrogens added (PLD: 5.01 Å, LCD: 6.54 Å). (Color code: Er: green, N: light violet, C: dark grey, O: red, H: white). AQEKUD. According to AK,11 this is also one of the top-performing structures for CO2/CH4 separation. The originally reported structure and what remains after the Python API script has been used to remove “solvent” are shown in Figure 4a and 4b, respectively. The original structure contains bound molecules of water and dimethyl sulfoxide which are removed by the cleaning process. The original publication reported AQEKUD20 as a coordination polymer the structural integrity of which relies on hydrogen bonds between the coordinated water molecules and squarates24 and would thus be devastated by the removal of H2O molecules.



Figure 4. a) Structure of the original AQEKUD (PLD: 0.90 Å, LCD: 2.13 Å), b) Structure of AQEKUD (PLD: 4.21 Å, LCD: 4.87 Å) obtained from CSDMOF by using the Python script to remove “solvent”.5 (Color code: Mn: violet, N: light violet, C: dark grey, S: yellow, O: red, H: white). On the treatment of MOFs with mobile charge-compensating ions Investigating MOF structures that contain CCIs is a challenging task and requires extraordinarily careful computer simulations. For example, EQeq,25,26 the charge-calculation method used by AK,11 depends on the positions of the atoms. On the one hand, restricting the mobile charge-compensating ions to their original positions in the crystal could result in unrealistic structural models. On the other, any random translations generated during the simulations invalidate the precomputed partial atomic charges, which must then be recalculated for the particular configuration at every Monte Carlo (MC) step. Because of the importance of this problem, the structures containing mobile charge-compensating ions are specifically identified in the CoRE MOF database. Nazarian et al.8 did not even consider including this type of structures in the supplementary CoRE MOF database with high-quality partial charges. To make a very rough estimate of the effect of treating unbound counterions dynamically in the calculations, we performed Grand Canonical MC (GCMC) simulations on ICORAV27, as an 8 ACS Paragon Plus Environment

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example, and allowed all of the counterions (Cl- in this MOF, Figure S2) to change their positions by translation or random translation MC moves. Note that the selectivity of CO2 toward N2 obtained by this approach amounts to 226, which is less than half the previously reported values (540.3611,16 and 574.9412)11,12 obtained by static treatment with the chloride ions at fixed crystallographic positions. Clearly, MOFs containing mobile chargecompensating ions must be treated carefully in computational simulations. Influence of scrutinizing the structures on the rankings of top-performing MOFs To demonstrate the impact of the structural model on the results of molecular simulations, we provide reported and newly calculated gas-separation data for QUQQUP.28 According to the original article28 and to the best of our knowledge, pyridine–pyridine π contacts play an important role in retaining the structural integrity within QUQQUP. However, using the Python API script to remove the “solvent” eliminates these pyridine moieties and affects the structural integrity of the resultant structure (Figure S3a). To overcome this problem, we generated a new structure by removing only the unbound methanol (Figure S3b) and then performed adsorption calculations for various binary gas mixtures as summarized in Table 1. Table 1. Calculated separation factors for QUQQUP using the previously reported and newly corrected structures Reported previously11,13 This work PLD 4.78 4.10 LCD b 5.16 4.69 𝑆𝐶𝑂2/𝑁2c 13.43 37.82 𝐴𝑃𝑆𝐶𝑂2/𝑁2d 12.44 55.87 𝑅𝐶𝑂2/𝑁2e 90.14 77.89 c 𝑆𝐶𝑂2/𝐶𝐻4 4.72 4.59 𝐴𝑃𝑆𝐶𝑂2/𝐶𝐻4d 14.78 6.83 𝑅𝐶𝑂2/𝐶𝐻4e 90.13 58.77 𝑆𝐶𝐻4/𝐻2c 22.72 123.27 𝐴𝑃𝑆𝐶𝐻4/𝐻2d 120.81 212.44 𝑅𝐶𝐻4/𝐻2e 87.17 51.78 a Pore Limiting Diameter (PLD in Å), b Largest Cavity Diameter (LCD in Å), c Adsorption selectivity (S), d Adsorbent Performance Score (APS), e Regenerability Factor (R). (Detailed definition can be found in Ref. 11) a



The differences between the results reported for the new structure and those previously reported for the old one are clearly significant and would alter the rankings remarkably (except for CO2/CH4). QUQQUP was previously ranked 12th for CH4/H2 separation13 but it exhibits the highest selectivity and APS values when the newly corrected structure is used. CONCLUDING REMARKS The established criteria5 for identifying MOF vs non-MOF structures among what will soon be one million CSD entries and for applying scripts to remove “solvent” are very useful and effective. However, as Moghadam et al.5 advise, the procedure for removing “solvent” should be checked carefully for possible faults that could result in systems suffering from a loss of structural integrity or other deficiencies. Therefore, careful structural analysis is still needed to validate and scrutinize the final set of top MOF candidates, as demonstrated in this account. This procedure must include discarding all structures that lack structural integrity after “solvent” has been removed, reliable treatment of the coordinated “solvent” molecules, and justified treatment of the charge-compensating ions. In our opinion, the abovementioned types of structures should be removed from the list of promising materials because their numerical data are not conclusive. ACKNOWLEDGMENTS The authors would like to thank the funding received from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Actions and cofinancing by the South Moravian Region under agreement No. 665860. This article reflects only the authors' view and the EU is not responsible for any use that may be made of the information it contains. This work was carried out in part under the project CEITEC 2020 (LQ1601) with financial support from the Ministry of Education, Youth, and Sports of the Czech Republic under the National Sustainability Program II. Computational resources were


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provided by CESNET LM2015042, CERIT Scientific Cloud LM2015085, and the IT4Innovations National Supercomputing Center LM2015070, as provided under the program “Large Infrastructures for Research, Experimental Development and Innovations” by the Ministry of Education, Youth and Sports.

ASSOCIATED CONTENT Supporting Information Supporting information is available free of charge on the website at DOI: XXXXXX. Computational details, additional figures and tables (PDF).

AUTHOR INFORMATION Corresponding Authors * Emails: P.Z.: [email protected]; R.M.: [email protected]

ORCID Pezhman Zarabadi-Poor: 0000-0002-6377-7592 Radek Marek: 0000-0002-3668-3523

Notes The authors declare no competing financial interest.



REFERENCES (1)

Colón, Y. J.; Snurr, R. Q. High-Throughput Computational Screening of Metal–Organic Frameworks. Chem. Soc. Rev. 2014, 43, 5735–5749.

(2)

Wilmer, C. E.; Leaf, M.; Lee, C. Y.; Farha, O. K.; Hauser, B. G.; Hupp, J. T.; Snurr, R. Q. Large-Scale Screening of Hypothetical Metal–Organic Frameworks. Nat. Chem. 2012, 4, 83–89.

(3)

Moghadam, P. Z.; Islamoglu, T.; Goswami, S.; Exley, J.; Fantham, M.; Kaminski, C. F.; Snurr, R. Q.; Farha, O. K.; Fairen-Jimenez, D. Computer-Aided Discovery of a Metal– Organic Framework with Superior Oxygen Uptake. Nat. Commun. 2018, 9, 1378.

(4)

Matito-Martos, I.; Moghadam, P. Z.; Li, A.; Colombo, V.; Navarro, J. A. R.; Calero, S.; Fairen-Jimenez, D. Discovery of an Optimal Porous Crystalline Material for the Capture of Chemical Warfare Agents. Chem. Mater. 2018, 30, 4571–4579.

(5)

Moghadam, P. Z.; Li, A.; Wiggin, S. B.; Tao, A.; Maloney, A. G. P.; Wood, P. A.; Ward, S. C.; Fairen-Jimenez, D. Development of a Cambridge Structural Database Subset: A Collection of Metal–Organic Frameworks for Past, Present, and Future. Chem. Mater. 2017, 29, 2618–2625.

(6)

Colón, Y. J.; Gómez-Gualdrón, D. A.; Snurr, R. Q. Topologically Guided, Automated Construction of Metal–Organic Frameworks and Their Evaluation for Energy-Related Applications. Cryst. Growth Des. 2017, 17, 5801–5810.

(7)

Chung, Y. G.; Camp, J.; Haranczyk, M.; Sikora, B. J.; Bury, W.; Krungleviciute, V.; Yildirim, T.; Farha, O. K.; Sholl, D. S.; Snurr, R. Q. Computation-Ready, Experimental Metal-Organic Frameworks: A Tool to Enable High-Throughput Screening of Nanoporous Crystals. Chem. Mater. 2014, 26, 6185–6192.


Page 12 of 15

Page 13 of 15 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(8)

Nazarian, D.; Camp, J. S.; Sholl, D. S. A Comprehensive Set of High-Quality Point Charges for Simulations of Metal–Organic Frameworks. Chem. Mater. 2016, 28, 785– 793.

(9)

Nazarian, D.; Camp, J. S.; Chung, Y. G.; Snurr, R. Q.; Sholl, D. S. Large-Scale Refinement of Metal−Organic Framework Structures Using Density Functional Theory. Chem. Mater. 2017, 29, 2521–2528.

(10) Li, S.; Chung, Y. G.; Simon, C. M.; Snurr, R. Q. High-Throughput Computational Screening of Multivariate Metal–Organic Frameworks (MTV-MOFs) for CO2 Capture. J. Phys. Chem. Lett. 2017, 8, 6135–6141. (11) Altintas, C.; Avci, G.; Daglar, H.; Nemati Vesali Azar, A.; Velioglu, S.; Erucar, I.; Keskin, S. Database for CO2 Separation Performances of MOFs Based on Computational Materials Screening. ACS Appl. Mater. Interfaces 2018, 10, 17257– 17268. (12) Daglar, H.; Keskin, S. Computational Screening of Metal–Organic Frameworks for Membrane-Based CO2/N2/H2O Separations: Best Materials for Flue Gas Separation. J. Phys. Chem. C 2018, 122, 17347–17357. (13) Altintas, C.; Erucar, I.; Keskin, S. High-Throughput Computational Screening of the Metal Organic Framework Database for CH4/H2 Separations. ACS Appl. Mater. Interfaces 2018, 10, 3668–3679. (14) Avci, G.; Velioglu, S.; Keskin, S. High-Throughput Screening of MOF Adsorbents and Membranes for H2 Purification and CO2 Capture. ACS Appl. Mater. Interfaces 2018, 10, 33693–33706. (15) Altintas, C.; Avci, G.; Daglar, H.; Gulcay, E.; Erucar, I.; Keskin, S. Computer Simulations of 4240 MOF Membranes for H2/CH4 Separations: Insights into Structure– Performance Relations. J. Mater. Chem. A 2018, 6, 5836–5847.



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(16) COSMOS – ERC 2017 Starting Grant. https://cosmoserc.ku.edu.tr (accessed December 15, 2018). (17) Welk, M. E.; Stern, C. L.; Poeppelmeier, K. R.; Norquist, A. J. Effects of Reaction Gel Dehydration

on

the

Synthesis

of

Cu(NC5H5)4VOF4

and

[Cu(NC5H5)4VOF4][Cu(NC5H5)4(H2O)VOF4]·H2O. Cryst. Growth Des. 2007, 7, 956–961. (18) Margraf, G.; Bolte, M.; Wagner, M.; Lerner, H.-W. Synthesis and Crystal Structure of [Li(THF)4]Cu2Br4. J. Chem. Crystallogr. 2007, 37, 503–506. (19) Lin, W. Z.; Ji, N. C.; Hai, H. N.; Zuan, N. J. Zhongguo Xitu Xuebao 1994, No. 12, 1–3. (20) Şerb, M.-D.; Speldrich, M.; Lueken, H.; Englert, U. Isomorphous Catena Transition Metal Squarates [MII(C4O4)(Dmso)2(OH2)2] (M = Co, Mn) and Magnetic Investigation into Their Solid Solution M = CoxMn1–X. Z. Für Anorg. Allg. Chem. 2011, 637, 536–542. (21) Willems, T. F.; Rycroft, C. H.; Kazi, M.; Meza, J. C.; Haranczyk, M. Algorithms and Tools for High-Throughput Geometry-Based Analysis of Crystalline Porous Materials. Microporous Mesoporous Mater. 2012, 149, 134–141. (22) Dassault Systèmes BIOVIA, Materials Studio 2017; San Diego: Dassault Systèmes. (23) CSD

MOF

subset,

https://sites.google.com/view/csdmofsubset/home

(accessed

December 15, 2018). (24) Yaghi, O. M.; Li, G.; Groy, T. L. Conversion of Hydrogen-Bonded Manganese(II) and Zinc(II) Squarate (C4O42–) Molecules, Chains and Sheets to Three-Dimensional Cage Networks. J. Chem. Soc. Dalton Trans. 1995, 0, 727–732.


Page 15 of 15 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(25) Wilmer, C. E.; Snurr, R. Q. Towards Rapid Computational Screening of Metal-Organic Frameworks for Carbon Dioxide Capture: Calculation of Framework Charges via Charge Equilibration. Chem. Eng. J. 2011, 171, 775–781. (26) Wilmer, C. E.; Kim, K. C.; Snurr, R. Q. An Extended Charge Equilibration Method. J. Phys. Chem. Lett. 2012, 3, 2506–2511. (27) Sun, Y.; Jiang, B.; Cui, T.; Xiong, G.; Smet, P. F.; Ding, F.; Gao, E.; Lv, T.; Eeckhout, K. V. den; Poelman, D.; et al. Solvothermal Synthesis, Crystal Structure, and Properties of Lanthanide-Organic Frameworks Based on Thiophene-2,5-Dicarboxylic Acid. Dalton Trans. 2011, 40, 11581–11590. (28) Abrahams, B. F.; Elliott, R. W.; Hudson, T. A.; Robson, R. A New Class of Easily Generated TCNQ2−-Based Coordination Polymers. Cryst. Growth Des. 2010, 10, 2860– 2862.


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