Experimental Diffusion Coefficients Research Articles

Mathematical Analysis of Nonlinear Differential Equations in Polymer Coated Microelectrodes

A theoretical analysis is conducted on the electrochemical behaviour of micro disk electrodes coated with thin coatings of electroactive polymers. The main focus of efforts to characterize the planar diffusion chemical reaction within polymer-modified ultra-microelectrodes is the creation of a theoretical model that explicitly takes into account the potential for the polymer film to cover the inlaid micro disc support surface. Approximate formulae for the steady-state amperometric response and formulation of the boundary value problem are given. The impact of substrate concentration, mediator concentration and current responsiveness in the solution besides the polymer film is also investigated. Akbari-Ganji method (AGM) and differential transformation method (DTM), two adequate and widely available analytical methods, were utilized to determine the steady-state non-linear diffusion equation. The approximate analytical solution for the substrate concentration and mediator concentration and the current for the small experimental kinetic values and diffusion coefficients are presented. We additionally determine the problem’s numerical solution using the MATLAB tool. A satisfactory agreement can be seen when the numerical outcomes verify with the analytical findings.

Oxygen diffusion coefficient in the γ phase of a TiAl GE alloy determined by SIMS

First reliable experimental oxygen diffusion coefficient data have been obtained in a Ti48.3Al47.7Cr1.9Nb2.1 near-γ GE alloy through secondary ion mass spectrometry (SIMS) depth profiling measurements of 18O isotopes between 500 °C and 700 °C. The following expression of diffusion coefficient D has thus been derived: D(m2/s)=10−10.6±1∙exp(−107±10kJ.mol−1/RT). These data have been compared with theoretical calculations from literature, showing reasonable agreement concerning the activation energy, but significant discrepancy regarding the D values.

Measurement of Diffusion Coefficients and Assessment of Atomic Mobilities in HCP Mg-Ag-Sn Alloys

Reliable thermodynamic and kinetic databases are essential for designing and developing novel magnesium (Mg) alloys for elevated-temperature applications in the automotive and aerospace industries. This study investigated diffusion behaviors of HCP Mg-Ag-Sn alloys by four sets of three diffusion couples annealed at 450, 500, and 550 °C, respectively. Interdiffusion and impurity diffusion coefficients at the three annealing temperatures were extracted using the forward-simulation method. The determined diffusion coefficients, combined with prior results in the literature, were then used to assess atomic mobilities for the HCP phase of the Mg-Ag-Sn system. This assessment was conducted using the DICTRA and the TCMG5 thermodynamic database within the Thermo-Calc software. Comprehensive comparisons between calculated and experimental diffusion coefficients yielded an excellent agreement. The atomic mobilities were also further validated by appropriate predictions of concentration profiles and diffusion paths observed in independent diffusion couple experiments performed at 525 °C for 18 hrs. It has been found that the addition of Sn and Ag both increase the diffusivity of Ag in HCP Mg and Sn in HCP Mg in the stable temperature range of HCP Mg, respectively. This improved understanding of the kinetics in the Mg-Ag-Sn ternary system is essential for controlling diffusion-dependent properties such as coarsening and, therefore, the mechanical properties of Mg-Ag-Sn alloys at elevated temperatures.

Effect of non-isothermal adsorption model on gas diffusion in coal particle

Gas diffusion is of great importance for coalbed methane (CBM) recovery and CO2 storage in coal seam. Most of the existing models of gas diffusion in coal particles are derived under isothermal conditions, while the coupled effect between gas adsorption/desorption and temperature variation is often neglected. The effect of accurate non-isothermal adsorption model on gas diffusion simulation also needs further study. In this work, isothermal adsorption tests of CO2 in anthracite/bitumite particles at different temperatures are conducted. The fitting results of Langmuir/Freundlich adsorption models are analyzed and the optimal non-isothermal adsorption models for anthracite/bitumite are obtained respectively. Non-isothermal desorption-diffusion tests of CO2 in anthracite/bitumite particles are carried out and corresponding non-isothermal desorption-diffusion model is also proposed, based on which the effect of non-isothermal adsorption model on gas diffusion in coal is numerically analyzed comprehensively. The results show that the non-isothermal Langmuir/Freundlich adsorption models are optimal for anthracite/bitumite respectively. Based on the optimal adsorption models, simulated gas diffusion amounts agree well with the experimental results and consistent diffusion coefficients can be back calculated. For sub-optimal adsorption model with R2 > 0.9, its deviation from adsorption data would significantly affect the accuracy of gas desorption-diffusion simulation. Moreover, if ‘diffusion ratio’ is taken as evaluation index, the inaccurate diffusion amount caused by inaccurate adsorption model in numerical simulation may be ignored, and the diffusion coefficient determined by ‘diffusion ratio’ would deviate from the true value.

Application of machine learning to study the effective diffusion coefficient of Re(VII) in compacted bentonite

Machine learning was used to predict the effective diffusion coefficient of radionuclides in compacted bentonites to reduce the cost of experimental methods. Through-diffusion experiments were conducted to determine the effective diffusion coefficient of Re(VII), which was used as a surrogate for 99Tc(VII), in compacted Anji bentonite. Five parameters (the external surface area, the ionic strength, the mass ratio of montmorillonite, the compacted dry density, and the accessible porosity) that affect the effective diffusion coefficient were calculated by a multi-porosity model to generate data for the analysis of the machine learning models to overcome the limited experimental data. The effective diffusion coefficient was predicted using two popular machine learning models, the Light Gradient Boosting Machine and Artificial Neural Network models, where the former exhibited higher sensitivity and accuracy in the prediction than the latter. The performance of the machine learning models was validated by comparing the experimental effective diffusion coefficients between this study and previous studies. The present work revealed that the machine learning method can be a powerful tool and may offer a new means of studying the effective diffusion coefficient.

Epitaxial fluorapatite vein in Northwest Africa 998 host apatite: Clues on the geochemistry of late hydrothermal fluids on Mars

AbstractSecondary minerals in martian nakhlites provide a powerful tool for investigating the nature, composition, and duration of aqueous activity in the martian crust. Northwest Africa (NWA) 998 crystallized early from the nakhlite magmatic source and has evidence of minimal signatures of the late hydrothermal alteration event that altered the nakhlites. Using FIB‐TEM techniques to study a cumulus apatite grain in NWA 998, we report the first evidence of a submicron‐scale vein consisting of fluorapatite and an SiO2‐rich phase. Fluorapatite grew epitaxially on the walls of an opened cleavage plane of host F‐bearing chlorapatite and the SiO2‐rich phase filled the center of the vein. The presence of nanoporosity and nanometer‐scale amorphous material and the sharp interface between the vein and the host apatite indicate the vein represents a coupled dissolution–reprecipitation process that generated apatite of a different composition that was more stable with the fluid. Using experimental data and diffusion coefficients of Cl in apatite from the literature, we conclude that the vein was caused by a low temperature (~300°C), slightly acidic, F‐, Si‐rich, aqueous fluid that acted as a closed system. Based on the characteristics of the vein (formation by rapid injection of fluid) and the fluid (composition, temperature, pH), and the lack of terrestrial weathering products in our SEM and TEM images, we infer that the vein is pre‐terrestrial in origin. Our observations support the hypothesis that the heat source triggering a hydrothermal system was a low‐shock velocity impact and rule out a magmatic origin. Finally, the vein could have formed from a late‐stage fluid different from that reported in other nakhlites, but formation during the same magmatic event by, for example, a less evolved fluid might also be plausible.

Machine Learning Predictions of Simulated Self-Diffusion Coefficients for Bulk and Confined Pure Liquids.

Diffusion properties of bulk fluids have been predicted using empirical expressions and machine learning (ML) models, suggesting that predictions of diffusion also should be possible for fluids in confined environments. The ability to quickly and accurately predict diffusion in porous materials would enable new discoveries and spur development in relevant technologies such as separations, catalysis, batteries, and subsurface applications. In this work, we apply artificial neural network (ANN) models to predict the simulated self-diffusion coefficients of real liquids in both bulk and pore environments. The training data sets were generated from molecular dynamics (MD) simulations of Lennard-Jones particles representing a diverse set of 14 molecules ranging from ammonia to dodecane over a range of liquid pressures and temperatures. Planar, cylindrical, and hexagonal pore models consisted of walls composed of carbon atoms. Our simple model for these liquids was primarily used to generate ANN training data, but the simulated self-diffusion coefficients of bulk liquids show excellent agreement with experimental diffusion coefficients. ANN models based on simple descriptors accurately reproduced the MD diffusion data for both bulk and confined liquids, including the trend of increased mobility in large pores relative to the corresponding bulk liquid.

Experimental and Modeling Studies of Local and Nanoscale para-Cresol Behavior: A Comparison of Classical Force Fields.

The dynamics of bulk liquid para-cresol from 340-390 K was probed using a tandem quasielastic neutron scattering (QENS) and molecular dynamics (MD) approach, due to its relevance as a simple model component of lignin pyrolysis oil. QENS experiments observed both translational jump diffusion and isotropic rotation, with diffusion coefficients ranging from 10.1 to 28.6 × 10-10 m2s-1 and rotational rates from 5.7 to 9.2 × 1010 s-1. The associated activation energies were 22.7 ± 0.6 and 10.1 ± 1.2 kJmol-1 for the two different dynamics. MD simulations applying two different force field models (OPLS3 and OPLS2005) gave values close to the experimental diffusion coefficients and rotational rates obtained upon calculating the incoherent dynamic structure factor from the simulations over the same time scale probed by the QENS spectrometer. The simulations gave resulting jump diffusion coefficients that were slower by factors of 2.0 and 3.8 and rates of rotation that were slower by factors of 1.2 and 1.6. Comparing the two force field sets, the OPLS3 model showed slower rates of dynamics likely due to a higher molecular polarity, leading to greater quantities and strengths of hydrogen bonding.

Binary Diffusion Coefficients for Short Chain Alcohols in Supercritical Carbon Dioxide—Experimental and Predictive Correlations

Experimental binary diffusion coefficients for short-chain alcohols in supercritical carbon dioxide were measured using the Taylor dispersion technique in a temperature range of 306.15 K to 331.15 K and along the 10.5 MPa isobar. The obtained diffusion coefficients were in the order of 10-8 m2 s-1. The dependence of D on temperature and solvent density was examined together with the influence of molecular size. Some classic correlation models based on the hydrodynamic and free volume theory were used to estimate the diffusion coefficients in supercritical carbon dioxide. Predicted values were generally overestimated in comparison with experimental ones and correlations were shown to be valid only in high-density regions.

Predicting the chloride diffusion coefficient and surface electrical resistivity of concrete using statistical regression-based models and its application in chloride-induced corrosion service life prediction of RC structures

The chloride diffusion coefficient and surface electrical resistivity (SER) are two most important characteristics of concrete durability. This study aims to develop prediction models of the rapid chloride migration tests (RCMT) and SER results according to the concrete mix properties and their correlation. The proposed models can be employed in the designing phase for service life prediction and in the construction phase to control the quality of the concrete. In this paper, the results of the RCMT and surface electrical resistivity (SER) test (Wenner method) of concrete specimens at the reference age (28 days) were collected, and statistical models were prepared to predict the RCMT and SER based on the concrete mix properties. Furthermore, the correlation of the RCMT results and SER results is shown, which can be practical in using surface electrical tests as an alternative for RCMT, due to its simplicity in the design and quality control phase. In order to validate the model and compare its precision against other prediction models, a dataset of RCMT resulting from other studies was gathered. Then, the prediction performance of different models was compared with each other. It was observed that the model proposed in this study makes more precise predictions in chloride diffusion coefficient than the models proposed by other authors. Finally, the predicted and experimental chloride diffusion coefficients along with the service lives of RC structures with different concrete cover and chloride diffusivity were estimated using a full probabilistic model. The results indicated that the calculated corrosion initiation probability using the predicted and experimental chloride diffusion coefficient was almost similar, demonstrating the applicability of the predicted chloride diffusion coefficient in service life prediction.

On the occurrence of very low intra-particle diffusion rates in zwitterionic hydrophilic interaction liquid chromatography polymer columns

Intra-particle diffusion is investigated in particle-packed and monolithic zwitterionic hydrophilic interaction liquid chromatography (HILIC) polymer columns. For this purpose, plate heights are first measured over a broad range of velocities for polar compounds with zone retention factors between k″ = 2 and 10 on all column types, multiplied with the corresponding velocity, and extrapolated to zero velocity. The thus obtained B-term coefficients are additionally verified via peak parking experiments and indicate a very low degree of longitudinal diffusion in all columns, that moreover seems to be independent of the zone retention factor. This is in contrast to earlier observations on reversed-phase liquid chromatography columns and bare silica HILIC columns. To obtain more insight into the reasons for these low levels of longitudinal diffusion, the experimentally obtained effective diffusion coefficients are modeled to equations derived from the effective medium theory, such as the models developed by Torquato and Jefrey & Hashin. It is, however, demonstrated that these models fail to adequately describe effective diffusion in the studied zwitterionic HILIC columns, due to the low degree of intraparticle diffusion in these stationary phases. Fitting the experimental effective diffusion coefficients to the two limiting cases of the effective medium theory, i.e., the pure parallel-connection and pure serial-connection case, it is observed that to stay within these limits, intraparticle diffusion must be extremely low, i.e., Dpz/Dm ≤ 0.01, indicating that the diffusion inside the pores is at least 100 times smaller than the bulk diffusion coefficient. There are several possible explanations for these low intraparticle diffusion coefficients, such as a strongly hindered diffusion in the polymer matrix, extremely low surface diffusion rates in the aqueous layer adsorbed onto the stationary phase and/or the occurrence of slow localized adsorption events.

Diffusion behaviors of HF in molten LiF-BeF2 and LiF-NaF-KF eutectics studied by FPMD simulations and electrochemical techniques

The hydrofluorination reaction has proven to be a very effective approach to remove impurities in the preparation and usage of molten LiF-BeF 2 (Flibe) and LiF-NaF-KF (Flinak) eutectic salts, however, the diffusion behaviors of HF in two molten fluorides are incompletely understood. Here we design two systems, HF+Flibe and HF+Flinak, to reveal the diffusion properties and local structures as well as their correlations by first principles molecular dynamics (FPMD) simulations and electrochemical methods . It is shown that the strong interaction between Be 2+ and F – in molten Flibe reduces their diffusivities while providing more space for Li + migration. The diffusion coefficient of H + in molten Flinak is higher than that in molten Flibe determined by the fast exchange of H + between two F anions, and the larger diffusivity of F – in molten Flinak is related to the irregular movement of free F anions. Besides, the quasi-gaseous transport behavior of HF in two molten fluorides is proposed in this study according to the stable H-F bonds. Moreover, the experimental diffusion coefficient of HF in molten Flinak estimated by the method of convolution linear sweep voltammetry is consistent with our simulation value, and the larger diffusivity is well explained by the higher stretching vibration frequency between H + and F – in molten Flinak. Finally, the ionic diffusion coefficients are descripted by the first sharp diffraction peaks of structure factors, the nearest neighbor peaks of radial distribution functions , and the major bond angels of angular distribution functions, and it is speculated from these FPMD simulations that the peak position has a higher weight on diffusion coefficient. Overall, in-depth understandings of the structure-property relationships of HF+Flibe and HF+Flinak systems provide insights into the molten salt purification technology and the daily operation of molten salt reactors .

Ternary diffusion in aqueous sodium salicylate + sodium dodecyl sulfate solutions

A Taylor dispersion method has been used to measure ternary mutual diffusion coefficients (D11, D22, D12 and D21) in aqueous sodium salicylate (NaSal) (component 1) + sodium dodecyl sulfate (NaDS) (component 2) solutions at 25.00 °C and concentrations up to 0.050 mol dm−3. In general, the data show that diffusion of NaDS drives co-current flow of NaSal, and that diffusion of NaSal drives also co-current flows of NaDS. The experimental ternary diffusion coefficients are compared with Nernst-Planck coefficients allowing a better interpretation of the electrostatic mechanism for the coupled diffusion of NaSal and SDS. From these equations, at compositions below the critical micelle concentration (cmc) of NaDS, small positive values of D12 and D21 are obtained resulting from fully dissociation of NaDS; however, at compositions above the cmc, the coupled diffusion of NaSal and NaDS becomes significant, as indicated by the experimental and predicted large positive cross-diffusion coefficients, D21. There is a good agreement between our data and those predicted by the Nernst-Planck equations for NaDS concentrations below and above the cmc.

Atomic transport properties of silicon melt at high temperature

Atomic transport properties, in particular, the self-diffusion and shear viscosity of silicon melt at high temperatures near the melting point are studied employing classical molecular dynamics simulations based on multiple empirical interatomic potentials. We find that the diffusion and viscosity coefficients of silicon melt predicted by the empirical potentials follow the Stokes-Einstein (SE) relation although both of which deviate from the experimental values. The discrepancy between the calculated and experimental diffusion coefficients are analyzed using the SE relation. We demonstrate that the discrepancy is partially attributed to the underestimation of the self-diffusion coefficients by the empirical potentials. Further, we analyze the microstructure of the melt based on several topological techniques and confirm that the (over) underestimation of the (viscosity) diffusion coefficients is caused by the overemphasis of the covalent bonding in the silicon melt.

A molecular simulation study on transport properties of FAMEs in high-pressure conditions

Transport property prediction of fatty acid methyl esters (FAMEs) is essential to its utilisation as biodiesel and biolubricant which can work under high-pressure conditions. Equilibrium molecular simulation is performed to study the viscosity, diffusivity, density and molecular structure dynamics at conditions up to 300 MPa. Among the transport properties, convergence of the viscosity needs a sufficiently large number of independent replications of the simulation. The system size effect on diffusion coefficient should be taken into consideration in fitting the Stokes-Einstein relation. The capability of three different force fields on predicting transport properties is evaluated in terms of the united-atom molecular model and all-atom molecular model. The solidification of FAMEs under high pressure occurs with parallel molecular alignment. The spatial inhomogeneity results in the breakdown of Stokes-Einstein relation. A hybrid effective hydrodynamic radius is established on the linear relation between experimental viscosity and diffusion coefficient in molecular simulation. This provides a predictive method to estimate viscosity from molecular diffusion coefficient over a broad range of conditions provided that Stokes-Einstein relation applies.

Recommendations for simplified yet robust assessments of atomic mobilities and diffusion coefficients of ternary and multicomponent solid solutions

This study extends a 1-parameter Z-Z-Z binary diffusion coefficient model to ternary and multicomponent systems. The cross-binary and ternary interaction parameters in atomic mobility (diffusion coefficient) assessments were systematically tested on 4 ternary solid solutions: fcc Ag-Au-Cu, fcc Co-Fe-Ni, fcc Cu-Fe-Ni, and bcc Nb-Ti-V. A simple combination of the Z-Z-Z binary model parameters without any additional fitting parameters already provides impressive predictions of the ternary diffusion coefficients when the 3 cross-binary parameters are set to be the corresponding binary Z-Z-Z model interaction parameters, leading to a robust Z-Z-ternary diffusion model. Employment of 3 independent cross-binary fitting parameters leads to an even better binary and cross-binary parameters only (BCBPO) model. Recommendations are rendered based upon the amount of available experimental ternary diffusion coefficients. These recommendations will substantially reduce the number of fitting parameters and improve the robustness of the resultant atomic mobility and diffusion coefficient databases for computational materials design.

Dissecting Monomer-Dimer Equilibrium of an RNase P Protein Provides Insight Into the Synergistic Flexibility of 5' Leader Pre-tRNA Recognition.

Ribonuclease P (RNase P) is a universal RNA-protein endonuclease that catalyzes 5’ precursor-tRNA (ptRNA) processing. The RNase P RNA plays the catalytic role in ptRNA processing; however, the RNase P protein is required for catalysis in vivo and interacts with the 5’ leader sequence. A single P RNA and a P protein form the functional RNase P holoenzyme yet dimeric forms of bacterial RNase P can interact with non-tRNA substrates and influence bacterial cell growth. Oligomeric forms of the P protein can also occur in vitro and occlude the 5’ leader ptRNA binding interface, presenting a challenge in accurately defining the substrate recognition properties. To overcome this, concentration and temperature dependent NMR studies were performed on a thermostable RNase P protein from Thermatoga maritima. NMR relaxation (R1, R2), heteronuclear NOE, and diffusion ordered spectroscopy (DOSY) experiments were analyzed, identifying a monomeric species through the determination of the diffusion coefficients (D) and rotational correlation times (τc). Experimental diffusion coefficients and τc values for the predominant monomer (2.17 ± 0.36 * 10−10 m2/s, τ c = 5.3 ns) or dimer (1.87 ± 0.40* 10−10 m2/s, τ c = 9.7 ns) protein assemblies at 45°C correlate well with calculated diffusion coefficients derived from the crystallographic P protein structure (PDB 1NZ0). The identification of a monomeric P protein conformer from relaxation data and chemical shift information enabled us to gain novel insight into the structure of the P protein, highlighting a lack of structural convergence of the N-terminus (residues 1–14) in solution. We propose that the N-terminus of the bacterial P protein is partially disordered and adopts a stable conformation in the presence of RNA. In addition, we have determined the location of the 5’ leader RNA in solution and measured the affinity of the 5’ leader RNA–P protein interaction. We show that the monomer P protein interacts with RNA at the 5’ leader binding cleft that was previously identified using X-ray crystallography. Data support a model where N-terminal protein flexibility is stabilized by holoenzyme formation and helps to accommodate the 5’ leader region of ptRNA. Taken together, local structural changes of the P protein and the 5’ leader RNA provide a means to obtain optimal substrate alignment and activation of the RNase P holoenzyme.

A full-atom multiscale modelling for sodium chloride diffusion in anion exchange membranes

A novel full-atom multiscale method, combining different computational approaches and aimed to describe diffusion of multiple ions in anion exchange membranes (AEM), is presented. The method is used to evaluate diffusion of chloride and sodium ions in polysulfone tetramethylammonium (PSU-TMA) membranes, with particular attention to the co-ion diffusion. The hydration of the PSU-TMA is computed as a function of the membrane ionic exchange capacity via Density Functional Theory (DFT) and used for carrying out molecular dynamics simulations (MD). An upgraded DFT-based approach is proposed to obtain the atoms’ charges used in the force field for the MD simulations. Three approaches have been adopted to evaluate the chloride self-diffusion coefficients, the first based on the Mean Square Displacement, while the others use two analytical models: Mackie-Meares and Yasuda-Lamaze-Ikenberry. For membranes with ideal selectivity, the computed chloride diffusion coefficients result in good agreement with literature values, highlighting the critical role of the water content on the diffusion of ions as the water uptake decreases. The full-atom modelling allows to reproduce the transition from normal to anomalous diffusion when decreasing the water volume fraction as expected experimentally. Moreover, to simulate real conditions, counter-ion and co-ion concentrations inside the AEM have been determined using the Donnan-Manning model. In this case, four approaches have been tested to balance the excess of charge obtained from the DFT calculations, finding, for one of them, a good agreement between theoretical and experimental diffusion coefficients. Finally, the calculation of fundamental quantities, necessary for the modelling of the sodium chloride diffusion, without resorting to adjustable parameters represents the guideline of the proposed methodology.

A simple yet general model of binary diffusion coefficients emerged from a comprehensive assessment of 18 binary systems

This study is the most comprehensive test to date aiming at defining the optimal number of fitting parameters for a reliable mathematical description of the diffusion behavior of a binary solid solution. Our systematic test of 18 diverse binary systems has yielded a surprisingly simple model with only one fitting parameter/constant which can be evaluated from experimental diffusion data. The rest of the quantities in the model are the self-diffusion and impurity (dilute) diffusion coefficients of the pure elements and the thermodynamic factor which can be computed from a CALPHAD thermodynamic assessment of the pertinent binary system. The 1-parameter Z-Z-Z model has been demonstrated to be very reliable and robust since the 18 binary systems tested in this study include very asymmetrical systems such as Co-Pd and Fe-Pd as well as Nb-Ti whose experimental diffusion coefficient data cover ~9 orders of magnitude and over a temperature range spanning ~1200°C (from ~800°C to ~2000°C). The Z-Z-Z model allows both tracer and intrinsic diffusion coefficients to be reliably computed for any composition at any temperature after the sole constant is evaluated from the interdiffusion or all experimental diffusion data. Extension of such a simple and robust model from binary to ternary and higher order systems will lead to a substantial reduction of fitting parameters and an enhancement of the reliability of future multicomponent diffusion (atomic mobility) databases for simulation of kinetic processes in materials.

Unveiling Carbon Dioxide and Ethanol Diffusion in Carbonated Water-Ethanol Mixtures by Molecular Dynamics Simulations.

The diffusion of carbon dioxide (CO) and ethanol (EtOH) is a fundamental transport process behind the formation and growth of CO bubbles in sparkling beverages and the release of organoleptic compounds at the liquid free surface. In the present study, CO and EtOH diffusion coefficients are computed from molecular dynamics (MD) simulations and compared with experimental values derived from the Stokes-Einstein (SE) relation on the basis of viscometry experiments and hydrodynamic radii deduced from former nuclear magnetic resonance (NMR) measurements. These diffusion coefficients steadily increase with temperature and decrease as the concentration of ethanol rises. The agreement between theory and experiment is suitable for CO. Theoretical EtOH diffusion coefficients tend to overestimate slightly experimental values, although the agreement can be improved by changing the hydrodynamic radius used to evaluate experimental diffusion coefficients. This apparent disagreement should not rely on limitations of the MD simulations nor on the approximations made to evaluate theoretical diffusion coefficients. Improvement of the molecular models, as well as additional NMR measurements on sparkling beverages at several temperatures and ethanol concentrations, would help solve this issue.