Critical Factors in Computational Characterization of Hydrogen

Subscriber access provided by UNIV OF DURHAM

C: Surfaces, Interfaces, Porous Materials, and Catalysis

Critical Factors in Computational Characterization of Hydrogen Storage in Metal-Organic Frameworks Jeffrey S. Camp, Vitalie Stavila, Mark D. Allendorf, David Prendergast, and Maciej Haranczyk J. Phys. Chem. C, Just Accepted Manuscript • DOI: 10.1021/acs.jpcc.8b04021 • Publication Date (Web): 26 Jul 2018 Downloaded from http://pubs.acs.org on July 27, 2018

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 38 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

The Journal of Physical Chemistry

Critical Factors in Computational Characterization of Hydrogen Storage in Metal-Organic Frameworks

Jeffrey Camp†, Vitalie Stavila‡, Mark Allendorf‡, David Prendergast†, and Maciej Haranczyk§,* †

The Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA ‡

§

Sandia National Laboratories, Livermore, California 94551, USA

Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA

*

Corresponding author. email: [email protected] 1

ACS Paragon Plus Environment

The Journal of Physical Chemistry 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

Abstract Inconsistencies in high-pressure H2 adsorption data and a lack of comparative experiment-theory studies have made it challenging to evaluate both new and existing MOFs in the context of hydrogen storage applications. In this work, we performed grand canonical Monte Carlo (GCMC) simulations in nearly 500 experimentally refined MOF structures to examine the variance in simulation results due to equation of state, H2 potential, and the effect of Density Functional Theory (DFT) structural optimization. We find that hydrogen capacity at 77 K and 100 bar, as well as hydrogen 100-to-5 bar deliverable capacity, is correlated more strongly with MOF pore volume than with MOF surface area (Chahine’s rule). The tested methodologies provide consistent rankings of materials. In addition, four prototypical metal–organic frameworks (MOF-74, CuBTC, ZIF-8 and MOF-5) with a range of surface areas, pore structures, and surface chemistries representative of promising adsorbents for hydrogen storage are evaluated in detail with both GCMC simulations and experimental measurements. Simulations with a 3-site classical potential for H2 agree best with our experimental data except in the case of MOF-5, in which H2 adsorption is best replicated with a 5-site potential. However, for the purpose of ranking materials, these two choices for H2 potential make little difference. More significantly, 100 bar loading estimates based on more accurate equations of state for the vaporliquid equilibrium yield the best comparisons with experiment.

2


Page 2 of 38

Page 3 of 38 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


1. Introduction Hydrogen-powered vehicles are now commercially available, but use costly fiber-reinforced tanks pressurized up to 70 MPa.1 The Department of Energy (DOE) 2020 capacity system targets for on-board hydrogen storage of 5.5 wt% and 40 g/L are physically impossible to reach using a 70 MPa pressurized tank.2 Inclusion of a high surface area sorbent within such tanks could allow comparable quantities of H2 to be stored at lower operating pressures, reducing system cost, increasing safety, and meeting DOE targets for gravimetric and volumetric density. Among the sorbent classes under consideration, metal-organic frameworks (MOFs) are among the most promising materials, as they display record-high surface areas and pore volumes. Efforts to synthesize new MOFs for hydrogen storage are mainly aimed at finding structures that increase the heat of adsorption to allow storage at ambient temperature, while not sacrificing volumetric capacity.3-4 Achieving this is a difficult challenge that has stymied improvements in storage capacity for decades. As an alternative, significant engineering effort has been dedicated to the design of on-board cryogenic tank systems to store H2 within adsorbents at 77 K, which allows for much higher hydrogen capacities per mass or volume of adsorbent.5-6 Given the overwhelming number of MOFs already synthesized,7 accurate methods to predict the performance of a given MOF for H2 storage before embarking on a synthetic campaign are essential. Excess H2 capacity in nanoporous carbons, on a gravimetric basis, has been shown to correlate strongly with surface area.8-9 Aggregated data from the literature demonstrate that H2 adsorption in the majority of MOFs follows a similar trend of about 1 wt% saturation uptake per 500 m2/g of surface area, known as Chahine’s rule.4 This correlation was used by Goldsmith et al. to model the total adsorption of H2 in over 4,000 crystallographically refined MOF structures from the Cambridge Structural Database.10 Their results demonstrate that a tradeoff exists 3



between gravimetric H2 storage performance and volumetric performance for materials nominally exceeding the 2020 DOE targets in total adsorption capacity.10 More detailed insight into H2 storage performance (and complete isotherms) can be realized from atomistic simulations of the hydrogen adsorbed phase within the pores of a MOFs. The most widely used method is grand-canonical Monte Carlo (GCMC), which relies on a classical potential, or “force field”, to approximate the physisorptive interactions between H2 molecules and framework atoms.11 The predictive or explanatory value of GCMC simulations is predicated on the accuracy of this underlying force field. For some classes of MOFs, custom force fields have been fit to H2-MOF interaction energies derived from accurate electronic structure methods.12 Fitting new force fields is often regarded as necessary to accurately describe interactions between quadrupolar H2 molecules and coordinatively unsaturated (“open”) metal atoms with MOFs.13-14 However, fitting new force field parameters is computationally demanding and often improves certain physical descriptions, such as adsorption in the Henry’s regime, at the cost of less accurate description of the high-pressure regime relative to standard models.13 Transferrable (or “generic”) force fields for framework atoms such as Universal Force Field (UFF)15 continue to be used most frequently in simulations of the adsorption of H2 and other light gases within MOFs. Much analysis of the phenomenology of adsorption in MOFs has focused on identifying a set of GCMC input parameters that produce good agreement with experimental data. For example, Xiang et al. matched experimental data for H2 adsorption in UMCM-1 with GCMC simulations using existing potentials from the literature and then used further simulations to extrapolate isotherms to higher pressures.16 Similarly, the effect of catenation in the IRMOF series was investigated by matching simulations to experimental H2

4


Page 4 of 38

Page 5 of 38 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


adsorption data in MOF-5, and then applying the same force field to hypothetical interwoven and interpenetrated versions of the material.17 A risk of this approach is that any inaccuracy in the experimental data used as a basis for comparison can lead to selection of less accurate force field parameters, resulting in propagation of systematic errors in predictions of material performance. Several different hydrogen models, including united-atom18, three-site19, and five-site20 descriptions have been used to simulate H2 adsorption in MOFs. Recently, Andersson and Larsson showed how three framework potentials, used in concert with four different H2 models, can give rise to a wide range of simulation predictions in both the low- and high-pressure regimes of hydrogen adsorption in UiO-66 and UiO-67 MOFs.21 This is problematic, because large deviations relative to experiment and between the predictions of commonly used force fields reduces the overall value of GCMC simulations as a predictive tool. A further complication of performing GCMC is the selection of an appropriate crystallographic representation of a given MOF material. Differences between synthesis methods, crystal resolution temperatures, and crystal structure refinement procedures result in variations between crystal structures of the same MOF material reported by different researchers.22 Small differences between crystal structures have been shown to result in large differences in rare gas adsorption in CuBTC23 and methane adsorption in MIL-5324. In this work, we show how simulations of H2 adsorption at 77 K and high pressure (100 bar) vary with choice of GCMC input parameters for nearly 500 experimentally resolved MOF structures including several well-known candidate materials for H2 storage. The input factors considered include the choice of H2 potential, the crystallographic representation of each MOF structure, and the equation of state for the H2 vapor phase. These results have direct relevance to ongoing efforts to (1) screen thousands of MOF structures to determine top candidates for H2

5



storage and (2) identify GCMC inputs which reliably reproduce and/or predict H2 isotherms in broad classes of MOFs. Towards the materials screening effort, we demonstrate that the predicted ranking of materials performance using popular 3-site and 5-site potentials for H2 are consistent. Our calculations reveal that MOF pore volume is a better predictor of overall H2 capacity at 100 bar than the Chahine rule correlation with MOF surface area. In addition, the relationship between H2 loading and pore volume explains the variation in predicted performance between experimental and DFT optimized versions of the same MOF structure. To evaluate how well different GCMC inputs reproduce experimental adsorption data, we measured H2 isotherms up to 100 bar at 77 K for MOF-5, CuBTC, ZIF-8, and Mg-MOF-74. Our optimized synthesis and activation protocols for MOF-5 and CuBTC yield gravimetric H2 capacities exceeding existing reports in the literature. Simulations with two different H2 potentials are found to be in good agreement with these experiments, contingent on judicious choice of equation of state for the H2 vapor phase. We show that combining two different equations of state with two different H2 potentials leads to GCMC predictions of H2 excess adsorption at 100 bar that vary by up to 20%. We anticipate that the sensitivity analysis detailed here will guide efforts to characterize candidate MOF materials for H2 storage applications using GCMC simulations. 2. Methods 2.1. GCMC simulations of H2 adsorption MOF structures: MOF structures were taken from a subset25 of the Computation-Ready Experimental MOF (CoRE MOF) database24 that have a corresponding version of each experimental MOF structure that was structurally optimized with a periodic PBE-D3 density functional theory calculation. CoRE MOF structures are experimentally refined MOF structures harvested from the Cambridge Structural Database (CSD)22 that have been prepared for atomistic

6


Page 6 of 38

Page 7 of 38 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


simulations by removing solvent molecules within the nanopores and selecting a single representation of any partially occupied or disordered atoms.24 Each of the 472 MOF structures in the subset used here were previously assigned Density Derived Electrostatic and Chemical (DDEC) point charges.26 This published set of structures does not include a copy of Mg-MOF74. Crystal structures for Mg-MOF-74 were adopted from the first version of the CoRE MOF database24 (CSD refcode: VOGTIV27) and a report from Lee et al.28. Geometric surface areas, occupiable pore volumes and largest cavity diameters were computed for each MOF structure using Zeo++29-31, while helium void fractions were determined using RASPA 2.032. Force fields: The 3-site Darkrim-Levesque19 and 5-site Belof-Stern-Space (BSS)20 potentials were used to model dispersive interactions between H2 molecules. The quadratic Feynman-Hibbs correction33 to the Lennard-Jones potential was used for the Darkrim-Levesque models (denoted DL/FH), while it was omitted for the BSS model. Dispersive interactions within MOFs were computed by combining UFF parameters15 for MOF framework atoms with the respective H2 potential using standard mixing rules to a cutoff distance of 13 Å. Coulombic interactions were directly computed between H2 molecules and MOFs (using DDEC charges on framework atoms34) to a distance of 13 Å and a long-range Ewald correction was used thereafter. All force field parameters are listed in the Supporting Information. Equations of state: The Peng-Robinson equation of state35 is implemented in RASPA 2.0 and was used without modification. Parameters for the BACK equation of state for H2 were adopted from the MPMC code.36 The fugacity coefficients for the BACK equation of state were determined by numerical integration of the compressibility factor. Explicit expressions for the fugacity and compressibility factor of H2 at 77 K were adopted directly from Zhou.37 Conversion

7



Page 8 of 38

between excess and absolute adsorption was performed using helium void fractions computed using Widom insertions38 in RASPA 2.0. GCMC simulation details: All GCMC simulations were performed using RASPA 2.0. The Zhou correlation was used to determine the fugacity and compressibility factor of H2, except where otherwise noted. MOF framework supercells were constructed to satisfy the minimum image convention. Each simulation consisted of 2,500 equilibration cycles followed by 2,500 production cycles, where each cycle consists of on average N moves (N = number of adsorbates within the system). Insertions, deletions, translations, and rotations were performed with equal probability. The loading of H2 was calculated in each structure at pressures of 100 bar and 5 bar, while full isotherms were additionally calculated for the MOF-5, CuBTC, ZIF-8, and Mg-MOF 74 structures within the set. All H2 loadings are reported in units of weight %: g H g H

× 100 , g MOF

except where otherwise noted. 2.2. Experimental methods MOF synthesis and activation: Initial optimizations of the synthesis conditions were achieved at small scale (

Critical Factors in Computational Characterization of Hydrogen

Recommend Documents