Abstract:Molecular dynamics (MD) simulation is widely used to calculate transport properties of fluids.In this study, non-equilibrium molecular dynamics (NEMD) simulation was applied to calculate mutual diffusion coefficients from the molecular flux at a given concentration gradient. First, the applicability of spherical molecular model was investigated by calculating self-and tracer diffusion coefficients of methane and n-decane mixture by a equilibrium MD simulation. The simulated self-and tracer diffusion coefficien… Show more
“…A challenge in nonideal multicomponent liquid diffusion is that multicomponent diffusivity data are rarely available. The values of M–S diffusivities still rely on molecular dynamic simulations − and empirical relations, ,− such as the Darken-type equations , and the Vignes-type relations. ,, The Darken equation , is widely used to describe mutual diffusion coefficients in binary mixtures, considering both hydrodynamics and thermodynamics, cf. Section S1 in the Supporting Information.…”
The extensive use of antisolvent crystallization for poorly soluble chemicals is hindered by oiling-out. This study delves into solute diffusion kinetics upon antisolvent addition. We conducted time-dependent simulations on a hypothetical micrometric diffusion couple, utilizing chemical potential gradients as driving forces within the Maxwell−Stefan model. Our computations compared two types of interflux coupling: drags and thermodynamics. The thermodynamic force dominates solute diffusion behavior. Antisolvent influx elevates solute chemical potential. This energy wave drives the solute to focus toward the good solvent and leads to the competition between crystallization and oiling-out. Through microfluidics and simulations, characteristic times of oilingout and two sites of antisolvent-induced spinodal decomposition were identified. Diffusion trajectories on the phase diagram unveiled local thermodynamic conditions and impacts of mixing parameters. Initial antisolvent gradient dominates the strength of the focusing effect. Initial solute concentration acts as an offset in diffusion trajectories. Faster agitation in antisolvent and smaller droplets of solution both effectively enhance solute focusing. These findings are general, allowing mixing processes to be designed into metastable phase regions, with local compositions staying above the designed concentrations for prolonged durations. Elevated supersaturations and extended diffusion times offer favorable conditions for nucleation of metastable phases.
“…A challenge in nonideal multicomponent liquid diffusion is that multicomponent diffusivity data are rarely available. The values of M–S diffusivities still rely on molecular dynamic simulations − and empirical relations, ,− such as the Darken-type equations , and the Vignes-type relations. ,, The Darken equation , is widely used to describe mutual diffusion coefficients in binary mixtures, considering both hydrodynamics and thermodynamics, cf. Section S1 in the Supporting Information.…”
The extensive use of antisolvent crystallization for poorly soluble chemicals is hindered by oiling-out. This study delves into solute diffusion kinetics upon antisolvent addition. We conducted time-dependent simulations on a hypothetical micrometric diffusion couple, utilizing chemical potential gradients as driving forces within the Maxwell−Stefan model. Our computations compared two types of interflux coupling: drags and thermodynamics. The thermodynamic force dominates solute diffusion behavior. Antisolvent influx elevates solute chemical potential. This energy wave drives the solute to focus toward the good solvent and leads to the competition between crystallization and oiling-out. Through microfluidics and simulations, characteristic times of oilingout and two sites of antisolvent-induced spinodal decomposition were identified. Diffusion trajectories on the phase diagram unveiled local thermodynamic conditions and impacts of mixing parameters. Initial antisolvent gradient dominates the strength of the focusing effect. Initial solute concentration acts as an offset in diffusion trajectories. Faster agitation in antisolvent and smaller droplets of solution both effectively enhance solute focusing. These findings are general, allowing mixing processes to be designed into metastable phase regions, with local compositions staying above the designed concentrations for prolonged durations. Elevated supersaturations and extended diffusion times offer favorable conditions for nucleation of metastable phases.
“…Studies on mass transport in liquids by mutual diffusion are of fundamental importance for many applications in biology, chemistry, and chemical engineering. − Accurate measurement of mutual diffusion coefficients over wide ranges of pressure and temperature is necessary because of its importance in the design of extractors, reactors, separators, and so on . Fick’s law and Maxwell–Stefan (MS) theory are commonly used to describe mutual diffusion in mixtures .…”
Section: Introductionmentioning
confidence: 99%
“…Then, the thermodynamic factor is multiplied by the MS diffusion coefficient to evaluate Fick diffusion coefficient . The methods for the calculation of mutual diffusion coefficient from MD simulations have been reviewed by Liu et al Numerous equilibrium MD (EMD) simulations have been performed to evaluate mutual diffusion coefficients of binary and ternary systems; for examples, see references. − A few researchers have also performed nonequilibrium molecular dynamics (NEMD) simulations to determine the mutual diffusion coefficient of binary systems. ,− …”
Section: Introductionmentioning
confidence: 99%
“…1−3 Accurate measurement of mutual diffusion coefficients over wide ranges of pressure and temperature is necessary because of its importance in the design of extractors, reactors, separators, and so on. 4 Fick's law and Maxwell−Stefan (MS) theory are commonly used to describe mutual diffusion in mixtures. 5 Fick diffusivities (D 12 ) are readily accessed from experiments since they are defined in terms of measurable concentration gradients.…”
In a recent publication, a reverse nonequilibrium molecular dynamics (RNEMD) method was presented for computing the mutual diffusion coefficient of liquid mixtures. A concentration gradient and a subsequent mass flux are induced in the system by suitably exchanging molecules in different regions. The algorithm has been successfully tested on Lennard-Jones mixtures and molecular fluid mixtures with molecules having the same number of particles. In this work, a modification is made to the RNEMD method to determine the mutual diffusion coefficient of binary liquid mixtures with molecules having different sizes and masses. To migrate molecules of a different type, the splitting method has been used in this work. Investigation of the resulting steady-state mass fraction profile allows the evaluation of the mutual diffusion coefficient. For validation, the mutual diffusion coefficients of ethane-propane and ethane-pentane liquid mixtures at different compositions and temperatures have been obtained using this method. The mutual diffusion coefficients obtained from the RNEMD simulations are within the error bars of values obtained by equilibrium molecular dynamics for the identical model and conditions. The excess energy released due to the exchange of molecules is efficiently removed by strongly coupling a local thermostat in the region around the insertion point. There is no heating of the analysis region.
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