Atomistic Molecular Dynamics Simulations of Carbon Dioxide Diffusivity in n-Hexane, n-Decane, n-Hexadecane, Cyclohexane, and Squalane

Moultos, Othonas A.; Tsimpanogiannis, Ioannis N.; Panagiotopoulos, Athanassios Z.; Trusler, J. P. Martin; Economou, Ioannis G.

doi:10.1021/acs.jpcb.6b04651

Cited by 61 publications

(64 citation statements)

References 73 publications

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“…Intra-molecular interactions within graphene flakes were described by the AIREBO potential 65 . For 1-octanol and cyclohexane two recently developed models were used that are based on the Opls forcefield [66][67][68] . These two models were specifically refined on reproducing thermodynamic properties such as the bulk density.…”

Section: Methodsmentioning

confidence: 99%

Liquids relax and unify strain in graphene

et al. 2020

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Solid substrates often induce non-uniform strain and doping in graphene monolayer, therefore altering the intrinsic properties of graphene, reducing its charge carrier mobilities and, consequently, the overall electrical performance. Here, we exploit confocal Raman spectroscopy to study graphene directly free-floating on the surface of water, and show that liquid supports relief the preexisting strain, have negligible doping effect and restore the uniformity of the properties throughout the graphene sheet. Such an effect originates from the structural adaptability and flexibility, lesser contamination and weaker intermolecular bonding of liquids compared to solid supports, independently of the chemical nature of the liquid. Moreover, we demonstrate that water provides a platform to study and distinguish chemical defects from substrate-induced defects, in the particular case of hydrogenated graphene. Liquid supports, thus, are advantageous over solid supports for a range of applications, particularly for monitoring changes in the graphene structure upon chemical modification.

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Section: Methodsmentioning

confidence: 99%

Liquids relax and unify strain in graphene

et al. 2020

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“…water, carbon dioxide, hydrocarbons, ionic liquids, deep eutectic solvents, and biomolecules [48,[75][76][77][78][79][80][81][82][83][84][85]. Many studies have focused on the computation of self-diffusivities in mixtures [86][87][88][89]. EMD has also been widely used to predict collective diffusivity in binary, ternary, and multicomponent mixtures [30,[49][50][51][52]61,[90][91][92][93][94][95][96][97][98].…”

Section: Introductionmentioning

confidence: 99%

Finite-size effects of diffusion coefficients computed from molecular dynamics: a review of what we have learned so far

Celebi

Jamali

Bardow

et al. 2020

Molecular Simulation

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108

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The number of molecules used in a typical Molecular Dynamics (MD) simulations is orders of magnitude lower than in the thermodynamic limit. It is therefore essential to correct diffusivities computed from Molecular Dynamics simulations for finite-size effects. We present a comprehensive review on finitesize effects of diffusion coefficients by considering self-, Maxwell-Stefan, and Fick diffusion coefficients in pure liquids, as well as binary, ternary, and quaternary mixtures. All finite-size corrections, both analytical and empirical, are discussed in detail. The finite-size effects of rotational and confined diffusion are also briefly discussed.

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“… 14 , 15 Alternatively, the shear viscosity can be computed via equilibrium or nonequilibrium molecular dynamics (MD) simulations. 7 , 8 , 16 − 24 In nonequilibrium MD (NEMD), the viscosity is calculated from the response of the system to an external shear field. 18 , 25 − 29 Although NEMD is computationally efficient at large external fields, 17 , 30 the computed viscosity can depend on the applied shear rate.…”

Section: Introductionmentioning

confidence: 99%

Shear Viscosity Computed from the Finite-Size Effects of Self-Diffusivity in Equilibrium Molecular Dynamics

Jamali

Hartkamp

Bardas

et al. 2018

J. Chem. Theory Comput.

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A method is proposed for calculating the shear viscosity of a liquid from finite-size effects of self-diffusion coefficients in Molecular Dynamics simulations. This method uses the difference in the self-diffusivities, computed from at least two system sizes, and an analytic equation to calculate the shear viscosity. To enable the efficient use of this method, a set of guidelines is developed. The most efficient number of system sizes is two and the large system is at least four times the small system. The number of independent simulations for each system size should be assigned in such a way that 50%–70% of the total available computational resources are allocated to the large system. We verified the method for 250 binary and 26 ternary Lennard-Jones systems, pure water, and an ionic liquid ([Bmim][Tf2N]). The computed shear viscosities are in good agreement with viscosities obtained from equilibrium Molecular Dynamics simulations for all liquid systems far from the critical point. Our results indicate that the proposed method is suitable for multicomponent mixtures and highly viscous liquids. This may enable the systematic screening of the viscosities of ionic liquids and deep eutectic solvents.

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Atomistic Molecular Dynamics Simulations of Carbon Dioxide Diffusivity in n-Hexane, n-Decane, n-Hexadecane, Cyclohexane, and Squalane

Cited by 61 publications

References 73 publications

Liquids relax and unify strain in graphene

Liquids relax and unify strain in graphene

Finite-size effects of diffusion coefficients computed from molecular dynamics: a review of what we have learned so far

Shear Viscosity Computed from the Finite-Size Effects of Self-Diffusivity in Equilibrium Molecular Dynamics

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