Applications of Molecular Modeling in Heterogeneous Catalysis Research
TL;DR: The application of molecular modeling in heterogeneous catalysis research as a complement to experimental studies has grown rapidly in recent years as mentioned in this paper, and a review summarizes methodologies for probing catalytic phenomena in terms of a hierarchical approach.
Abstract: The application of molecular modeling in heterogeneous catalysis research as a complement to experimental studies has grown rapidly in recent years. This review summarizes methodologies for probing catalytic phenomena in terms of a hierarchical approach. The elements of the hierarchy are different computational methods at different time and length scales that may be linked together to answer questions spanning from the atomic to the macroscopic. At the most detailed level of description, quantum chemical calculations are used to predict the energies, electronic structures, and spectroscopic properties of small arrangements of atoms and even periodic structures. Atomistic simulations, using systems of hundreds or thousands of molecules, can be used to predict macroscopic thermodynamic and transport properties, as well as preferred molecular geometries. At the longest time and length scales, continuum engineering modeling approaches such as microkinetic modeling are used to calculate reaction rates, reactant conversion, and product yields and selectivities, using model parameters predicted by the other levels of the hierarchy. We highlight some interesting recent results for each of these approaches, stress the need for integrating modeling at widely varying time and length scales, and discuss current challenges and areas for future development.
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TL;DR: Various spatial and temporal multiscale KMC methods, namely, the coarse-grained Monte Carlo (CGMC), the stochastic singular perturbation approximation, and the τ-leap methods are reviewed, introduced recently to overcome the disparity of length and time scales and the one-at-a time execution of events.
Abstract: The microscopic spatial kinetic Monte Carlo (KMC) method has been employed extensively in materials modeling. In this review paper, we focus on different traditional and multiscale KMC algorithms, challenges associated with their implementation, and methods developed to overcome these challenges. In the first part of the paper, we compare the implementation and computational cost of the null-event and rejection-free microscopic KMC algorithms. A firmer and more general foundation of the null-event KMC algorithm is presented. Statistical equivalence between the null-event and rejection-free KMC algorithms is also demonstrated. Implementation and efficiency of various search and update algorithms, which are at the heart of all spatial KMC simulations, are outlined and compared via numerical examples. In the second half of the paper, we review various spatial and temporal multiscale KMC methods, namely, the coarse-grained Monte Carlo (CGMC), the stochastic singular perturbation approximation, and the τ-leap methods, introduced recently to overcome the disparity of length and time scales and the one-at-a time execution of events. The concepts of the CGMC and the τ-leap methods, stochastic closures, multigrid methods, error associated with coarse-graining, a posteriori error estimates for generating spatially adaptive coarse-grained lattices, and computational speed-up upon coarse-graining are illustrated through simple examples from crystal growth, defect dynamics, adsorption–desorption, surface diffusion, and phase transitions.
428 citations
TL;DR: In this paper, the authors provide a perspective on multiscale modeling of catalytic reactions with emphasis on mechanism development and application to complex and emergent systems, and discuss the bond-order conservation method for thermochemistry and activation energy estimation.
313 citations
TL;DR: In this paper, the effect of functional, basis set, and cluster size on the intrinsic activation energy for cracking of C3-C6 alkanes was investigated, and the dependence of the apparent rate coefficient on the carbon number on the cracking rate was shown.
Abstract: The kinetics of alkane cracking in zeolites MFI and FAU have been simulated theoretically from first principles. The apparent rate coefficient for alkane cracking was described as the product of the number of alkane molecules per unit mass of zeolite that are close enough to a Bronsted-acid site to be in the reactant state for the cleavage of a specific C-C bond and the intrinsic rate coefficient for the cleavage of that bond. Adsorption thermodynamics were calculated by Monte Carlo simulation and the intrinsic rate coefficient for alkane cracking was determined from density functional theory calculations combined with absolute rate theory. The effects of functional, basis set, and cluster size on the intrinsic activation energy for alkane cracking were investigated. The dependence of the apparent rate coefficient on the carbon number for the cracking of C3-C6 alkanes on MFI and FAU determined by simulation agrees well with experimental observation, but the absolute values of the apparent rate coefficients are a factor of 10 to 100 smaller than those observed. This discrepancy is attributed to the use of a small T5 cluster representation of the Bronsted-acid site. Limited calculations for propane and butane cracking on MFI reveal that significantly better agreement between prediction and observation is achieved using a T23 cluster for both the apparent rate coefficient and the apparent activation energy. The apparent rate coefficients for alkane cracking are noticeably larger for MFI than FAU, in agreement with recent findings reported in the experimental literature.
74 citations
TL;DR: In this paper , macroporous-structured three-way catalyst (TWC) particles were synthesized via a template-assisted spray process followed by an additional heating process.
8 citations
TL;DR: In this article, a mini-review of high-field pulsed field gradient (PFG) NMR studies of gas and liquid diffusion in nanoporous materials is presented, which demonstrates the ability of high field PFG NMR to gain unique insights and differentiate between various types of diffusion.
Abstract: High magnetic fields (up to 17.6 T) in combination with large magnetic field gradients (up to 25 T/m) were successfully utilized in pulsed field gradient (PFG) NMR studies of gas and liquid diffusion in nanoporous materials. In this mini-review, we present selected examples of such studies demonstrating the ability of high field PFG NMR to gain unique insights and differentiate between various types of diffusion. These examples include identifying and explaining an anomalous relationship between molecular size and self-diffusivity of gases in a zeolitic imidazolate framework (ZIF), as well as revealing and explaining an influence of mixing different linkers in a ZIF on gas self-diffusion. Different types of normal and restricted self-diffusion were quantified in hybrid membranes formed by dispersing ZIF crystals in polymers. High field PFG NMR studies of such membranes allowed observing and explaining an influence of the ZIF crystal confinement in a polymer on intra-ZIF self-diffusion of gases. This technique also allowed measuring and understanding anomalous single-file diffusion (SFD) of mixed sorbates. Furthermore, the presented examples demonstrate a high potential of combining high field PFG NMR with single-crystal infrared microscopy (IRM) for obtaining greater physical insights into the studied diffusion processes.
5 citations
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TL;DR: The application of molecular modeling in heterogeneous catalysis research as a complement to experimental studies has grown rapidly in recent years as discussed by the authors, and a review summarizes methodologies for probing catalytic phenomena in terms of a hierarchical approach.
Abstract: The application of molecular modeling in heterogeneous catalysis research as a complement to experimental studies has grown rapidly in recent years. This review summarizes methodologies for probing catalytic phenomena in terms of a hierarchical approach. The elements of the hierarchy are different computational methods at different time and length scales that may be linked together to answer questions spanning from the atomic to the macroscopic. At the most detailed level of description, quantum chemical calculations are used to predict the energies, electronic structures, and spectroscopic properties of small arrangements of atoms and even periodic structures. Atomistic simulations, using systems of hundreds or thousands of molecules, can be used to predict macroscopic thermodynamic and transport properties, as well as preferred molecular geometries. At the longest time and length scales, continuum engineering modeling approaches such as microkinetic modeling are used to calculate reaction rates, reactant conversion, and product yields and selectivities, using model parameters predicted by the other levels of the hierarchy. We highlight some interesting recent results for each of these approaches, stress the need for integrating modeling at widely varying time and length scales, and discuss current challenges and areas for future development.
104 citations