Probing gas adsorption in MOFs using an efficient ab initio widom insertion Monte Carlo method

We propose a novel biased Widom insertion method that can efficiently compute the Henry coefficient, KH, of gas molecules inside porous materials exhibiting strong adsorption sites by employing purely DFT calculations. This is achieved by partitioning the simulation volume into strongly and weakly adsorbing regions and selectively biasing the Widom insertion moves into the former region. We show that only few thousands of single point energy calculations are necessary to achieve accurate statistics compared to many hundreds of thousands or millions of such calculations in conventional random insertions. The methodology is used to compute the Henry coefficient for CO2, N2, CH4, and C2H2 in M‐MOF‐74(M = Zn and Mg), yielding good agreement with published experimental data. Our results demonstrate that the DFT binding energy and the heat of adsorption are not accurate enough indicators to rank the guest adsorption properties at the Henry regime. © 2016 Wiley Periodicals, Inc.

[1]  C. Wilmer,et al.  Large-scale screening of hypothetical metal-organic frameworks. , 2012, Nature chemistry.

[2]  C. Morrison,et al.  Improving Predictions of Gas Adsorption in Metal–Organic Frameworks with Coordinatively Unsaturated Metal Sites: Model Potentials, ab initio Parameterization, and GCMC Simulations , 2012 .

[3]  J. Ilja Siepmann,et al.  Vapor–liquid equilibria of mixtures containing alkanes, carbon dioxide, and nitrogen , 2001 .

[4]  R. Krishna,et al.  A computational study of CO2, N2, and CH4 adsorption in zeolites , 2007 .

[5]  Tom K Woo,et al.  Electrostatic Potential Derived Atomic Charges for Periodic Systems Using a Modified Error Functional. , 2009, Journal of chemical theory and computation.

[6]  W. Goddard,et al.  UFF, a full periodic table force field for molecular mechanics and molecular dynamics simulations , 1992 .

[7]  Edward J. Maginn,et al.  A biased grand canonical Monte Carlo method for simulating adsorption using all-atom and branched united atom models , 1999 .

[8]  Stefano de Gironcoli,et al.  QUANTUM ESPRESSO: a modular and open-source software project for quantum simulations of materials , 2009, Journal of physics. Condensed matter : an Institute of Physics journal.

[9]  Gérard Férey,et al.  Porous metal-organic-framework nanoscale carriers as a potential platform for drug delivery and imaging. , 2010, Nature materials.

[10]  B. Smit,et al.  CO2 capture by metal-organic frameworks with van der Waals density functionals. , 2012, The journal of physical chemistry. A.

[11]  S. L. Mayo,et al.  DREIDING: A generic force field for molecular simulations , 1990 .

[12]  Alexis T. Bell,et al.  Sorption Thermodynamics, Siting, and Conformation of Long n-Alkanes in Silicalite As Predicted by Configurational-Bias Monte Carlo Integration , 1995 .

[13]  Michael W. Deem,et al.  Toward a Database of Hypothetical Zeolite Structures , 2006 .

[14]  Omar K Farha,et al.  Metal-organic framework materials as chemical sensors. , 2012, Chemical reviews.

[15]  L. Valenzano,et al.  Heats of adsorption of CO and CO2 in metal-organic frameworks: Quantum mechanical study of CPO-27-M (M = Mg, Ni, Zn) , 2011 .

[16]  Li-Chiang Lin,et al.  Force-Field Development from Electronic Structure Calculations with Periodic Boundary Conditions: Applications to Gaseous Adsorption and Transport in Metal-Organic Frameworks. , 2014, Journal of chemical theory and computation.

[17]  Wei Zhou,et al.  High-capacity methane storage in metal-organic frameworks M2(dhtp): the important role of open metal sites. , 2009, Journal of the American Chemical Society.

[18]  Rajamani Krishna,et al.  Metal-organic frameworks as adsorbents for hydrogen purification and precombustion carbon dioxide capture. , 2011, Journal of the American Chemical Society.

[19]  D. Sholl,et al.  Prediction of CO2 Adsorption Properties in Zeolites Using Force Fields Derived from Periodic Dispersion-Corrected DFT Calculations , 2012 .

[20]  Jesse G. McDaniel,et al.  Ab Initio, Physically Motivated Force Fields for CO2 Adsorption in Zeolitic Imidazolate Frameworks , 2012 .

[21]  Kyuho Lee,et al.  Higher-accuracy van der Waals density functional , 2010, 1003.5255.

[22]  Sergey N. Maximoff,et al.  Ab initio carbon capture in open-site metal-organic frameworks. , 2012, Nature chemistry.

[23]  B. Smit,et al.  Toward a Materials Genome Approach for ionic liquids: synthesis guided by ab initio property maps. , 2014, The journal of physical chemistry. B.

[24]  Michael O'Keeffe,et al.  Hydrogen Storage in Microporous Metal-Organic Frameworks , 2003, Science.

[25]  Maciej Haranczyk,et al.  Computation-Ready, Experimental Metal–Organic Frameworks: A Tool To Enable High-Throughput Screening of Nanoporous Crystals , 2014 .

[26]  Maciej Haranczyk,et al.  In silico design of porous polymer networks: high-throughput screening for methane storage materials. , 2014, Journal of the American Chemical Society.

[27]  Abhoyjit S Bhown,et al.  In silico screening of carbon-capture materials. , 2012, Nature materials.

[28]  Kenji Sumida,et al.  Evaluating metal–organic frameworks for post-combustion carbon dioxide capture via temperature swing adsorption , 2011 .

[29]  Richard Blom,et al.  Application of metal–organic frameworks with coordinatively unsaturated metal sites in storage and separation of methane and carbon dioxide , 2009 .

[30]  Rajamani Krishna,et al.  Monte Carlo simulations in zeolites , 2001 .