Efficient Monte Carlo Simulations of Gas Molecules Inside Porous Materials.

Monte Carlo (MC) simulations are commonly used to obtain adsorption properties of gas molecules inside porous materials. In this work, we discuss various optimization strategies that lead to faster MC simulations with CO2 gas molecules inside host zeolite structures used as a test system. The reciprocal space contribution of the gas-gas Ewald summation and both the direct and the reciprocal gas-host potential energy interactions are stored inside energy grids to reduce the wall time in the MC simulations. Additional speedup can be obtained by selectively calling the routine that computes the gas-gas Ewald summation, which does not impact the accuracy of the zeolite's adsorption characteristics. We utilize two-level density-biased sampling technique in the grand canonical Monte Carlo (GCMC) algorithm to restrict CO2 insertion moves into low-energy regions within the zeolite materials to accelerate convergence. Finally, we make use of the graphics processing units (GPUs) hardware to conduct multiple MC simulations in parallel via judiciously mapping the GPU threads to available workload. As a result, we can obtain a CO2 adsorption isotherm curve with 14 pressure values (up to 10 atm) for a zeolite structure within a minute of total compute wall time.

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

[2]  Rajamani Krishna,et al.  Using molecular simulations for screening of zeolites for separation of CO2/CH4 mixtures , 2007 .

[3]  B. Smit,et al.  Alcohol solubility in a lipid bilayer: Efficient grand-canonical simulation of an interfacially active molecule. , 2010, The Journal of chemical physics.

[4]  Berend Smit,et al.  Molecular simulations of zeolites: adsorption, diffusion, and shape selectivity. , 2008, Chemical reviews.

[5]  E Beerdsen,et al.  Force field parametrization through fitting on inflection points in isotherms. , 2004, Physical review letters.

[6]  David S. Sholl,et al.  Screening metal-organic framework materials for membrane-based methane/carbon dioxide separations , 2007 .

[7]  R. Rosenfeld Nature , 2009, Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery.

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

[9]  Berend Smit,et al.  Towards a molecular understanding of shape selectivity , 2008, Nature.

[10]  Rajamani Krishna,et al.  In silico screening of zeolite membranes for CO2 capture , 2010 .

[11]  J. Board,et al.  Ewald summation techniques in perspective: a survey , 1996 .

[12]  Maciej Haranczyk,et al.  Algorithms and tools for high-throughput geometry-based analysis of crystalline porous materials , 2012 .

[13]  Peter W. Milonni,et al.  Quantum optics: A shift on a chip , 2009, Nature.

[14]  David Olson,et al.  Atlas of Zeolite Framework Types , 2007 .

[15]  Kenji Sumida,et al.  Carbon dioxide capture in metal-organic frameworks. , 2012, Chemical reviews.

[16]  Oliver Rübel,et al.  High-Throughput Characterization of Porous Materials Using Graphics Processing Units. , 2012, Journal of chemical theory and computation.

[17]  Christian Holm,et al.  How to mesh up Ewald sums. I. A theoretical and numerical comparison of various particle mesh routines , 1998 .

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

[19]  Michael W Deem,et al.  A database of new zeolite-like materials. , 2011, Physical chemistry chemical physics : PCCP.

[20]  Berend Smit,et al.  Molecular Monte Carlo Simulations Using Graphics Processing Units: To Waste Recycle or Not? , 2011, Journal of chemical theory and computation.

[21]  Berend Smit,et al.  Understanding molecular simulation: from algorithms to applications , 1996 .

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