Using molecular dynamics to obtain Maxwell-Stefan diffusion coefficients in liquid systems

Ven-Lucassen, van de Imjj Irma; Vlugt, Tjh Thijs; Zanden, van der Ajj Ton; Kerkhof, Pjam Piet

doi:10.1080/00268979809482342

Cited by 37 publications

(34 citation statements)

References 10 publications

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“…Equation 4 is an average over all N i molecules of species i in the simulation volume, since all contribute to the self-diffusion coefficient. In a binary mixture, the MS diffusion coefficient − D i j can also be written in terms of the center of mass velocity [32],…”

Section: Diffusion Coefficientsmentioning

confidence: 99%

Prediction of Transport Properties of Liquid Ammonia and Its Binary Mixture with Methanol by Molecular Simulation

2012

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Section: Diffusion Coefficientsmentioning

confidence: 99%

Prediction of Transport Properties of Liquid Ammonia and Its Binary Mixture with Methanol by Molecular Simulation

2012

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“…The self-diffusivities decrease as its concentration increases because the ion-ion interaction becomes stronger at higher concentrations. One might think that the self-diffusivity measured by NMR might not be exactly the same as the values measured with traditional methods such as mutual diffusion measurement 18,19 or MD simulations; [25][26][27][28][29][30][31][32][33] however, the difference between NMR measurement and MD simulation was reported to be minimal. 34 The aim of this article is to provide a theoretical method to evaluate the transport properties from self-diffusivities and activity coefficients; therefore, more detailed discussion regarding the differences between the measured self-diffusivities in different methods is out of scope of the paper and will be the subject of subsequent studies.…”

Section: Experimental Values and Evaluation Of Transport Properties Omentioning

confidence: 99%

“…[25][26][27][28][29][30][31][32][33] To measure the self-diffusivity experimentally, some researchers have measured the mutual diffusion of two liquids of very nearly equal concentrations. 18,19 In addition, the nuclear magnetic resonance (NMR) method has been also widely used to measure the selfdiffusivity.…”

Section: Generalized-darken Relationmentioning

confidence: 99%

A Method for Estimating Transport Properties of Concentrated Electrolytes from Self-Diffusion Data

Kim

Srinivasan

2016

J. Electrochem. Soc.

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A theoretical method is introduced that calculates the electrolyte-transport properties using Onsager-Stefan-Maxwell (OSM) theory (concentrated-solution theory) and the generalized-Darken relation. OSM theory is used to relate binary diffusivities to the transport properties of the electrolyte, including transference number, ionic conductivity, and Fickian diffusivity. The generalized-Darken relation is proposed to calculate the binary diffusivities of multicomponent systems from self-diffusivities. Finally, an example is demonstrated to show the details of how this method can be used to estimate transport properties. The calculated properties were reasonably close to the previously reported experimental values. © The Author To develop a physics-based lithium-ion battery model or battery management systems, accurate estimation of electrolyte transport properties are essential. This is especially true as new high-energy cells are designed with thick electrodes wherein electrolyte transport dominates the end of discharge at high current densities.However, the experimental measurements of the electrolyte properties are not trivial because it requires well-controlled experimental apparatus to obtain accurate values. Depending on the technique used, the estimation of the transport properties can be very sensitive to both natural and induced convection when estimating the diffusion coefficient. In addition, solvent reduction; inevitable when using lithium metal electrodes in electrochemical techniques, results in side reactions, and gas formation, leading to convolution of the obtained data. To properly describe mass transport in a solution, n(n − 1)/2 transport properties are necessary for n chemically distinct species because the system has n(n − 1)/2 binary diffusivities (D ij ).2 In a general lithium-ion battery, the electrolyte includes a cation, an anion, and a solvent; therefore, three independent transport properties are required. The cation transference number relative to the solvent t 0 + , ionic conductivity κ, and Fickian diffusivity D serve to describe the mass transport of the electrolyte. 3,4 In this work, we introduced a novel method of evaluating the electrolyte-transport properties using the Onsager-Stefan-Maxwell (OSM) theory (concentrated-solution theory) 2-10 combined with the generalized-Darken relation. 11,12 This method provides a way to estimate transport properties with minimized experimental measurements. The key to this method is converting self-diffusivities to binary diffusivities of multicomponent systems using the generalized-Darken relation. After the conversion, OSM theory can be used to calculate the electrolyte transport properties from the binary diffusivities. This paper is intended to provide the details of this conversion and evaluate its accuracy. As an example, we demonstrate the applicability by calculating the three transport properties of LiPF 6 in PC, and show that the estimated properties compare favorably with published literature data. Onsager-Stefan-Maxwell (OSM) Theor...

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“…Simulations and experiments using binary fluids have shown quantitative agreement between MS diffusivities and those obtained by using Darken's equations (Fernandez et al, 2004). Furthermore, equilibrium molecular dynamics using the Green-Kubo relations have shown correct MS diffusivities in ternary systems of "colored" Lennard-Jones molecules (Van de Ven-Lucassen et al, 1998). Lastly, Kinetic Monte Carlo simulations show qualitative and quantitative agreement between the MS formulation and Onsager's linear law for ternary mixture diffusion through zeolites (Krishna and Paschek, 2002b).…”

Section: Introductionmentioning

confidence: 84%

“…Recent literature (Krishna and Baur, 2003;Krishna and Wesselingh, 1997;Taylor and Krishna, 1993;Van de Ven-Lucassen et al, 1998) describes the diffusive portion of Eq. (1) as the generalized MS diffusion equation for multicomponent systems,…”

Section: Introductionmentioning

confidence: 99%

Inversion of multicomponent diffusion equations

Matuszak

Donohue

2005

Chemical Engineering Science

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Using molecular dynamics to obtain Maxwell-Stefan diffusion coefficients in liquid systems

Cited by 37 publications

References 10 publications

Prediction of Transport Properties of Liquid Ammonia and Its Binary Mixture with Methanol by Molecular Simulation

Prediction of Transport Properties of Liquid Ammonia and Its Binary Mixture with Methanol by Molecular Simulation

A Method for Estimating Transport Properties of Concentrated Electrolytes from Self-Diffusion Data

Inversion of multicomponent diffusion equations

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