Generic parameters of trajectory-extending kinetic Monte Carlo for calculating diffusion coefficients

Tien, Wu Jhao; Chiu, Chi Cheng

doi:10.1063/1.5035553

Cited by 3 publications

(3 citation statements)

References 38 publications

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“…Based on the penetrant positions, the primary simulation box is divided into subcells (of the same size and shape) and the probability matrix of jumps between subcells is extracted. The method is of low computational cost, requiring, however, proper adjustments of the parameters related to the sampling interval τ and subcell grid size [167]. It has been applied for the study of CO 2 [38] and other small penetrants [37] in fluorinated glassy polymers, leading to predictions in reasonable agreement with experimental measurements.…”

Section: Coarse-graining and Multiscale Approaches In Sorption Andmentioning

confidence: 99%

Molecular Modeling Investigations of Sorption and Diffusion of Small Molecules in Glassy Polymers

Vergadou

Theodorou

2019

Membranes

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With a wide range of applications, from energy and environmental engineering, such as in gas separations and water purification, to biomedical engineering and packaging, glassy polymeric materials remain in the core of novel membrane and state-of the art barrier technologies. This review focuses on molecular simulation methodologies implemented for the study of sorption and diffusion of small molecules in dense glassy polymeric systems. Basic concepts are introduced and systematic methods for the generation of realistic polymer configurations are briefly presented. Challenges related to the long length and time scale phenomena that govern the permeation process in the glassy polymer matrix are described and molecular simulation approaches developed to address the multiscale problem at hand are discussed.

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Section: Coarse-graining and Multiscale Approaches In Sorption Andmentioning

confidence: 99%

Molecular Modeling Investigations of Sorption and Diffusion of Small Molecules in Glassy Polymers

Vergadou

Theodorou

2019

Membranes

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“…The optimal values of τ MD and d grid combinations first need to be determined for obtaining the correct MSD from the TEKMC simulation. Different techniques can be used to obtain the time interval between two successive kMC steps, τ kMC . We follow the procedure prescribed by Neyertz et al, where τ kMC = τ MD (=τ).…”

Section: Methodsmentioning

confidence: 99%

“…Different techniques can be used to obtain the time interval between two successive kMC steps, τ kMC . 43 We follow the procedure prescribed by Neyertz et al, where τ kMC = τ MD (=τ). Figure 2 illustrates the values of MSD obtained from all-atom MD and TEKMC simulations for CO 2 , CH 4 , and N 2 at 20 bar pressure.…”

Section: The Journal Of Physical Chemistry Bmentioning

confidence: 99%

Trajectory-Extending Kinetic Monte Carlo Simulations to Evaluate Pure and Gas Mixture Diffusivities through a Dense Polymeric Membrane

Dasgupta,

K. S.,

Ayappa

et al. 2023

J. Phys. Chem. B

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With renewed interest in CO 2 separations, carbon molecular sieving (CMS) membrane performance evaluation requires diffusion coefficients as inputs to have a reliable estimate of the permeability. An optimal material is desired to have both high selectivity and permeability. Gases diffusing through dense CMS and polymeric membranes experience extended subdiffusive regimes, which hinders reliable extraction of diffusion coefficients from mean squared displacement data. We improve the sampling of the diffusive landscape by implementing the trajectory-extending kinetic Monte Carlo (TEKMC) technique to efficiently extend molecular dynamics (MD) trajectories from ns to μs time scales. The obtained self-diffusion coefficient of pure CO 2 in CMS membranes derived from a 6FDA/BPDA-DAM precursor polymer melt is found to linearly increase from 0.8−1.3 × 10 −6 cm 2 s −1 in the pressure range of 1−20 bar, which supports previous experimental findings. We also extended the TEKMC algorithm to evaluate the mixture diffusivities in binary mixtures to determine the permselectivity of CO 2 in CH 4 and N 2 mixtures. The mixture diffusion coefficient of CO 2 ranges from 1.3−7 × 10 −6 cm 2 s −1 in the binary mixture CO 2 /CH 4 , which is significantly higher than the pure gas diffusion coefficient. Robeson plot comparisons show that the permselectivity obtained from pure gas diffusion data is significantly lower than that predicted using mixture diffusivity data. Specifically, in the case of the CO 2 /N 2 mixture, we find that using mixture diffusivities led to permselectivities lying above the Robeson limit highlighting the importance of using mixture diffusivity data for an accurate evaluation of the membrane performance. Combined with gas solubilities obtained from grand canonical Monte Carlo (GCMC) simulations, our work shows that simulations with the TEKMC method can be used to reliably evaluate the performance of materials for gas separations.

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Evolution of structural topology of forming nanocrystalline silicon film by atomic-scale-mechanism-driven model based on realistic network

2018

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To establish a description of realistic structural evolution of a growth film, we propose a local definite continuous-random-network (CRN) structure combined with a kinetic Monte Carlo (KMC) method based on an atomic-scale mechanism from first-principles density-functional-theory computations and molecular-dynamics computations. The proposed CRN-KMC method elucidates the evolution of elaborate topological structure and the transformation from amorphous phase to nanocrystalline phase of Si films, which is essentially attributed to the atomic interactive behavior of film growth. The method further predicts the realistic structural networks of a growing film at various temperatures based on various atomic-scale mechanisms competing with each other, mechanisms that not only essentially drive the radical from physisorption to chemisorption with the film surface, but also decidedly influence the film-surface chemical composition. In particular, we find the evolution of topological structure’s critical dependence on the compositions of the film surface and H-induced crystallization mechanism, which provide the important information for the strategy for determining optimized deposition conditions for local crystal formation. The results of the evolution of the structural network indicate that the structure of film is similar the CRN model’s representation at relative lower temperature, and is in full agreement with the inhomogeneous crystalline model at relative higher temperature without an abrupt phase change from polycrystalline to amorphous. Our CRN-KMC realistic structure model has significance for exploring the relation of various atomic-scale mechanisms to the phase transformation of growing films.

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Generic parameters of trajectory-extending kinetic Monte Carlo for calculating diffusion coefficients

Cited by 3 publications

References 38 publications

Molecular Modeling Investigations of Sorption and Diffusion of Small Molecules in Glassy Polymers

Molecular Modeling Investigations of Sorption and Diffusion of Small Molecules in Glassy Polymers

Trajectory-Extending Kinetic Monte Carlo Simulations to Evaluate Pure and Gas Mixture Diffusivities through a Dense Polymeric Membrane

Evolution of structural topology of forming nanocrystalline silicon film by atomic-scale-mechanism-driven model based on realistic network

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