Tracer Diffusion Coefficients Research Articles

Prediction of diffusion coefficients in aqueous systems by machine learning models

Currently there are no accurate models for the prediction of diffusion coefficients at infinite dilution in aqueous systems. Frequently, models that work well for polar solvents often perform worse in the case of water. At the same time, experimental data of tracer diffusion coefficients are scarce and can be impractical to measure when information on this important transport property is required. In this work, machine learning models were developed to predict the tracer diffusion coefficient of any solute in water at atmospheric pressure. Several approaches were carried out to construct the model, using different types of input parameters: pure component properties and theoretical molecular descriptors, such as atom counts, structural fragments and fingerprints, computed using different sources. A database of 126 systems (1192 data points) was used for training and the best model showed a global average absolute relative deviation (AARD) of 3.92%, with a maximum deviation of 24.27% on the test set. This model uses as inputs the temperature and 195 molecular descriptors computed using the RDKit cheminformatics package, which can be automatically calculated from a molecular identifier thus making the model very simple to use. In comparison, the well-known Wilke-Chang equation provided an AARD of 13.03% in the same test set, demonstrating the improved accuracy of the proposed solution. The models developed in this work are provided at github.com/EgiChem/ml-D12-water-app.

An investigation of self-interstitial diffusion in α-zirconium by an on-the-fly machine learning force field

The on-the-fly machine learning force field approach, based on the Gaussian approximation potential and Bayesian error estimation, was used to study the diffusion of self-interstitial atoms in α-zirconium. Ab initio molecular dynamics simulations of lattice vibration and interstitial diffusion at different temperatures were employed to develop the force field. The radial and angular descriptors of the potential were further optimized to achieve better agreement with first-principles results. Subsequent long-term diffusion simulations were performed to assess the diffusion behavior based on the obtained force field. Tracer diffusion coefficients and diffusion anisotropy were studied at temperatures of 600–1200 K, and the Bayesian errors were estimated throughout the diffusion simulations. The mean and maximum estimated Bayesian errors of atomic force were approximately twice as large as those observed during the learning period. The basal diffusion was greatly favored compared to the interstitial diffusion along the c-axis, consistent with previous simulations based on first-principles results and classical potentials. The accuracy and applicability of the current on-the-fly machine learning approach were critically evaluated.

An experimental estimation method of diffusion coefficients in ternary and multicomponent systems from a single diffusion profile

Until recently, it was textbook knowledge that the diffusion coefficients could not be estimated in a multi-component system following the widely practised diffusion couple method. The recently proposed constrained diffusion couple method largely solved the problems. The need to produce two intersecting diffusion paths in a multi-component space with very well-controlled compositions of the diffusion couple end members may be tricky in certain situations, depending on the complications of diffusion paths. In this study, we have shown the estimation of all types of diffusion coefficients from a single diffusion profile without neglecting Onsager's cross terms in concentrated ternary Ni-Co-Fe, Fe-rich quaternary Fe-Ni-Co-Cr and concentrated Ni-Co-Fe-Cr-Al quinary alloys. This is applicable in ternary and multicomponent component systems (n≥3) at a stable Kirkendall marker plane position. One can even estimate the impurity diffusion coefficients utilizing the composition profiles at the ends of the diffusion couples following the Hall method, which has been rarely practised in multicomponent systems until now. We have further demonstrated the importance of estimating the tracer and intrinsic diffusion coefficients in a concentrated or multi-principal element alloy in which interdiffusion coefficients can be vague and misleading for understanding the elements' diffusional interactions and relative mobilities. We have also shown the importance of considering the vacancy wind effect in concentrated alloys. The method proposed in this study will help to generate a mobility database with relative ease in various multicomponent systems important for various applications, which was considered impossible until recently.

First principles calculation of composition dependence tracer and interdiffusion with phase change in γ/γ′ superalloy: A case study of Ir/Ir3Nb

In this work, the composition dependent tracer and interdiffusion coefficient with phase change in γ/γ′ Ir/Ir3Nb superalloy are studied by means of first-principles calculation together with nudged elastic band, and quasi−harmonic thermodynamics. The formulae scattered in the literature for composition dependence tracer diffusion coefficient are summarized and executed using first principles calculation. Each term in the newly derived formulae, such as energy barrier, jump frequency, defect concentration, correlation, solvent enhancement factor, effective escape frequency, etc. is meticulously calculated. We find the composition dependent tracer diffusion coefficient of Nb in L12 γ′-Ir3Nb phase is contributed mainly from the antisite bridge rather than five-frequency model proposed in FCC γ-Ir dilute solid solution. The faster diffuser is Nb in γ-Ir, while Ir in γ′-Ir3Nb. Based on the tracer diffusion coefficient, the interdiffusion coefficient is obtained using Darken-Manning equation. The composition profile and phase boundary movement of γ/γ′ Ir/Ir3Nb superalloy are evaluated through an analytical solution of Matano-Boltzmann equations. The calculated diffusion coefficients and composition profile are in good agreement with experiments. Our findings not only serve as a successful example for the quantitative calculation of composition dependent tracer diffusion coefficient, but also shed lights on the physics behind the diffusion in intermetallics.

A kinetic model of diffusional phase transformations in ternary line compounds and determination of diffusion coefficients: Application to the Nb–Mo–Si system

The diffusional phase transformations in inhomogeneous multicomponent systems play an important role in affecting the material properties. Ternary line compounds, which are ternary phases with components that have both large and small solid solubility, are often observed in applications. They are different from solid solutions with variable composition ratios and stoichiometric compounds with fixed composition ratios. However, the existing models cannot quantitatively characterize the diffusional phase transformations in ternary line compounds. Therefore, by introducing the state equation related to the chemical potential and mole fraction, a kinetic model of diffusional phase transformations was established for the first time to describe the mole fraction evolution and phase growth in ternary line compounds. Furthermore, a method to determine the tracer diffusion coefficients of components related to the mole fraction and crystal phase structure in ternary line compounds was proposed, and applied to the diffusion of Nb-Mo-Si ternary system composed of the MoSi2 and Nb. During the high-temperature diffusion process of Nb-MoSi2, the silicide-poor phase (Mo, Nb)5Si3 is formed, which is a typical ternary line compound. Based on the diffusion experiments and inverse calculations, the tracer diffusion coefficients of components in ternary line compound (Mo, Nb)5Si3 were experimentally obtained. Moreover, ab-initio calculations of defect energetics clarified the microscopic diffusion mechanisms in the silicide-poor phase, and explained the reason why that the diffusion coefficient of Si decreases significantly with the increase of Nb mole fraction in ternary line compound (Mo, Nb)5Si3. The research provides valuable guidance for modeling and analyzing the diffusional phase transformation of multi-component systems.

Pore‐Scale Modeling of Water and Ion Diffusion in Partially Saturated Clays

AbstractAn accurate mechanistic understanding of solute diffusion in partially saturated clays is critical for assessing the safety of deep geological repositories for radioactive waste. In this study, a pore‐scale numerical framework is developed to simulate water and ion diffusion in partially saturated clays. First, the two‐phase Shan‐Chen Lattice Boltzmann method is employed to establish the liquid‐gas distribution in a reconstructed three‐dimensional pore geometry of a clay. An equivalent solute method is also developed and validated to improve the numerical stability of the solution at the liquid/gas interface corresponding to steep variations of the concentration and diffusion coefficient of the water tracer. By using a mobility‐distance relationship from molecular simulations, Fick's law is numerically solved to simulate water diffusion in nanopores, while the coupled Poisson‐Boltzmann‐Nernst‐Planck equations are solved to simulate ion diffusion under the influence of the electrical double layer (EDL). Our model reveals that the decrease of relative effective diffusion coefficients during the desaturation is more pronounced for ions than for water, due to the additional transport pathway of water tracers in the gas phase. The obtained effective diffusion coefficients of tritiated water and ions agree well with reported data from compacted sedimentary rocks. By comparing the local electric potential and the distribution of ion concentrations in single pores, the simulation results suggest that the EDL in unsaturated clays has a more complex influence on ion distribution than under fully water‐saturated conditions. This study provides critical insights into the coupled transport processes of solutes in partially saturated clays.

Diffusion simulation based on atomistic model and mobility determination via Kirkendall experiment for multi-component systems

Currently the multi-component diffusion kinetic databases, one of the key inputs for successful predictions of microstructural evolution, are by no means reliable since they are developed mostly by only seeking interdiffusion properties via diffusion-couple experiments but without considering the indispensable tracer or intrinsic diffusion coefficients. Estimating interdiffusion coefficients becomes challenging with the increasing number of components. In the present work, a mobility-extraction method is presented to directly determine atomic mobilities, which is in turn used to develop kinetic databases and then calculate all sorts of diffusion coefficients. It requires only one single-phase diffusion couple with Kirkendall markers to obtain the atomic mobilities in the marker position, with no limit on the number of components. This novel idea is realized on the basis of a new simulation scheme to solve diffusion equations in line with the atomistic model, which takes the Kirkendall effect into account intrinsically and efficiently.

“Anomalous” diffusion in multi-layer silicide systems

The transition metal silicide coatings have excellent oxidation resistance. In the high-temperature oxidization environment, the “anomalous” diffusion phenomenon of the reverse concentration gradient occurs in the multilayer silicide coating structure, which has a significant impact on the coating degradation. This study is to explore the physical mechanism of “anomalous” diffusion phase transformation in the MoSi2–NbSi2 bilayer silicide coating on the Nb alloy substrate. Through vacuum annealing experiments, combined with micro-Raman spectroscopy and electron probe microanalysis measurements, the diffuisonal phase transformation of multilayer silicide coating in the oxygen-free environment at high temperatures was studied. By decoupling the oxidation and diffusion, the experiments indicate that high-temperature oxidation is not the dominant driving factor for the “anomalous” diffusion of atoms. The thermodynamic analysis reveals that the reduction in the nucleation barrier of the silicide-poor layer due to multicomponent solid solution and the non-uniform distribution of component chemical potential provide the driving force for the “anomalous” diffusion growth. Based on the diffusion kinetic modeling, the simulation of diffusion-controlled phase transformation in multilayer silicide coating was carried out, and the effect of tracer diffusion coefficients on the growth of the silicide-poor phase was analyzed. The research will have guiding significance for the recognition of failure mechanisms of silicide coating systems and performance improvement.

Active and passive microrheology with large tracers in hard colloids.

The dynamics of a tracer particle in a bath of quasi-hard colloidal spheres is studied by Langevin dynamics simulations and mode coupling theory (MCT); the tracer radius is varied from equal to up to seven times larger than the bath particles radius. In the simulations, two cases are considered: freely diffusing tracer (passive microrheology) and tracer pulled with a constant force (active microrheology). Both cases are connected by linear response theory for all tracer sizes. It links both the stationary and transient regimes of the pulled tracer (for low forces) with the equilibrium correlation functions; the velocity of the pulled tracer and its displacement are obtained from the velocity auto-correlation function and the mean squared displacement, respectively. The MCT calculations give insight into the physical mechanisms: At short times, the tracer rattles in its cage of neighbours, with the frequency increasing linearly with the tracer radius asymptotically. The long-time tracer diffusion coefficient from passive microrheology, which agrees with the inverse friction coefficient from the active case, arises from the transport of transverse momentum around the tracer. It can be described with the Brinkman equation for the transverse flow field obtained in extension of MCT, but cannot be recovered from the MCT kernel coupling to densities only. The dynamics of the bath particles is also studied; for the unforced tracer the dynamics is unaffected. When the tracer is pulled, the velocity field in the bath follows the prediction of the Brinkman model, but different from the case of a Newtonian fluid.

Estimation of diffusion coefficients in NiCoFeCrAl multi-principal element alloy following an inventive design strategy of diffusion couples

An inventive design strategy of producing the diffusion couples for intersecting the diffusion paths in multicomponent space is described in Ni-Co-Fe-Cr-Al multi-principal element alloy. This, for the first time, facilitates the estimation of the tracer, intrinsic, and interdiffusion coefficients of all the elements purely experimentally in this quinary system. This was not possible until now following any other experimental methods. The tracer diffusion coefficients estimated in this quinary system are compared with the impurity and tracer diffusion coefficients in pure Ni, and at (or near) equiatomic compositions of binary Ni-Co, ternary Ni-Co-Cr, and quaternary Ni-Co-Fe-Cr systems. The relative mobilities of the elements are found to follow the trend DNi*≤DCo*<DFe*≤DCr*<DAl* in all the systems. However, the tracer diffusion coefficients of the elements first decrease and then increase with the increasing order of the systems. The contribution of the vacancy wind effect on certain cross-intrinsic diffusion coefficients is found to be very significant and cannot be ignored. The influence of the vacancy wind effect on interdiffusion coefficients is less significant than the intrinsic diffusion coefficients since interdiffusion coefficients are the average of multiple intrinsic diffusion coefficients. This may lead to the wrong statement that the vacancy wind effects are negligible. We have further shown that describing the relative diffusion rates of the elements with main interdiffusion coefficients instead of the tracer diffusion coefficients can be misleading or confusing. Different elements as the dependent variables of interdiffusion coefficients indicate a very different or even opposite trend of relative diffusivities in this system.

Concepts for estimating all types of diffusion coefficients of NiCoFeCr multi-principal element alloys using two dissimilar or a combination of ideal and non-ideal pseudo-ternary diffusion couples

The estimation of diffusion coefficients in multicomponent system is facilitated by strategically designing diffusion couples with constrained diffusion paths. We have demonstrated methods of estimating tracer diffusion coefficients following three different combinations of diffusion profiles: (i) By intersecting a pseudo-ternary diffusion path with a rectilinear pseudo-binary diffusion path, (ii) by considering a combination of two dissimilar pseudo-ternary diffusion paths, and (iii) considering a combination of ideal and non-ideal pseudo-ternary diffusion paths with uphill diffusion characteristics. Equation schemes required for such analyses depending on the type of diffusion profiles are explained in detail. This approach relies on the availability of reliable thermodynamic data for the estimation of the tracer diffusion coefficients. Following, as demonstrated, one can calculate the intrinsic and interdiffusion coefficients of all the elements for a conventional diffusion couple in which all the elements would produce the diffusion profiles.

Tracer diffusion coefficients in a moderately dense granular suspension: Stability analysis and thermal diffusion segregation

The diffusion transport coefficients of a binary granular suspension where one of the components is present in tracer concentration are determined from the (inelastic) Enskog kinetic equation. The effect of the interstitial gas on the solid particles is accounted for in the kinetic equation through two different terms: (i) a viscous drag force proportional to the particle velocity and (ii) stochastic Langevin-like term defined in terms of the background temperature. The transport coefficients are obtained as the solutions of a set of coupled linear integral equations recently derived for binary granular suspensions with arbitrary concentration [Gómez González et al., “Enskog kinetic theory for multicomponent granular suspensions,” Phys. Rev. E 101, 012904 (2020)]. To achieve analytical expressions for the diffusion coefficients, which can be sufficiently accurate for highly inelastic collisions and/or disparate values of the mass and diameter rations, the above integral equations are approximately solved by considering the so-called second Sonine approximation (two terms in the Sonine polynomial expansion of the distribution function). The theoretical results for the tracer diffusion coefficient D0 (coefficient connecting the mass flux with the gradient of density of tracer particles) are compared with those obtained by numerically solving the Enskog equation by means of the direct simulation Monte Carlo method. Although the first-Sonine approximation to D0 yields, in general, a good agreement with simulation results, we show that the second-Sonine approximation leads to an improvement over the first-Sonine correction, especially when the tracer particles are much lighter than the granular gas. The expressions derived here for the diffusion coefficients are also used for two different applications. First, the stability of the homogeneous steady state is discussed. Second, segregation induced by a thermal gradient is studied. As expected, the results show that the corresponding phase diagrams for segregation clearly differ from those found in previous works when the effect of gas phase on grains is neglected.

Dry Reforming of Methane over 5%Ni/Ce1-xTixO2 Catalysts Obtained via Synthesis in Supercritical Isopropanol.

A series of 5%Ni/Ce1-xTixO2 catalysts was prepared with nickel impregnation of mixed Ce-Ti oxides obtained via synthesis in supercritical isopropanol. All oxides have a cubic fluorite phase structure. Ti is incorporated into the fluorite structure. Small amounts of impurities of TiO2 or mixed Ce-Ti oxides appear with Ti introduction. Supported Ni is presented as the NiO or NiTiO3 perovskite phase. Ti introduction increases total samples reducibility and results in stronger interaction of supported Ni with the oxide support. The fraction of rapidly replaced oxygen and the average tracer diffusion coefficient also increase. The number of metallic nickel sites decreased with increasing Ti content. All catalysts except Ni-CeTi0.45 demonstrate close activity in tests of dry reforming of methane. The lower activity of Ni-CeTi0.45 can be connected to Ni decoration with species of the oxide support. The incorporation of Ti prevents detachment of Ni particles from the surface and their sintering during dry reforming of methane.

Critical Review of Transport Properties of HCl, KOH, and NaOH in High Temperature Water and Correlations for Transport Properties of H3O+ and OH−

High-temperature tracer diffusion coefficients for H3O+ and OH− are important parameters in the modeling of diffusion-controlled reaction kinetics and mass transport processes under hydrothermal conditions, and these tracer diffusion coefficients are directly related to the ionic electrical conductivities in the limit of infinite dilution through the Nernst–Einstein relationship. The limiting conductivity of H3O+ and OH− in water is controlled by two separate mechanisms of ionic movement: (i) the bulk ionic diffusion and (ii) proton hopping, also known as “Grotthuss” mechanism and/or “prototropic transfer.” This work reports a critical assessment of the limiting electrical conductivity data (Λ°) for aqueous HCl, KOH, and NaOH measured above room temperature. The initial assessed dataset included temperatures from 273.15 K up to 873.15 K and water densities from 1000 kg m−3 down to 270 kg m−3 and was reduced down to a final critically evaluated dataset spanning temperatures between 273.15 and 678.15 K and densities between 346 and 1006 kg m−3. The results were used to derive values for the excess conductivity due to prototropic transfer, λE°, of H3O+ and OH− using correlations previously reported for aqueous KCl. Simple empirical correlations of water viscosity and density were derived for Λ°(HCl), Λ°(KOH), Λ°(NaOH), λE°(H3O+), and λE°(OH−). Tests using the λE°(OH−) correlation and a previously reported function for Λ°(NaCl) show that the NaOH data can be accurately reproduced to within the estimated uncertainties. The reported correlations provide a means to model more accurately the tracer diffusion coefficients for H3O+ and OH− to supercritical conditions.

Diffusion coefficients of bioactive compounds in sub/supercritical CO2 and CO2/ethanol mixtures from molecular dynamics simulations

A computational strategy based on molecular dynamics (MD) simulations is proposed for the prediction of tracer diffusion coefficients of bioactive compounds in CO2 (D12) and CO2 modified with ethanol (Dm,i), in both supercritical and subcritical regions. Three systems were used for its validation, namely, β-carotene and ibuprofen in supercritical CO2, and gallic acid in CO2 modified with 16 mol.% of ethanol. The MD diffusivities were assessed with experimental data, with average absolute relative deviations (AARD) between 3.82 % and 7.36 %, and average relative deviations (ARD) between −6.18 % and 5.75 %. The dependency of the diffusion coefficient on temperature, pressure, and Stoke-Einstein coordinate (T/μ) was also evaluated. All data followed the expected trends apart from gallic acid in CO2 modified with 16 mol.% of ethanol, for which the computed Dm,i showed a weak linear dependency with T/μ.The validated MD strategy was then employed to calculate diffusivities of eucalyptol in sub/supercritical CO2, and in sub/supercritical CO2 modified with 8 mol.% and 16 mol.% of ethanol. The computational strategy was re-evaluated upon comparison with experimental diffusivities of eucalyptol in sub/supercritical mixtures of CO2 with 8 mol.% ethanol. The expected dependencies on pressure, temperature, and Stoke-Einstein coordinate were obeyed, and it was also found that the diffusion coefficient decreased with increasing ethanol content. Four phenomenological models from the literature were adopted to represent MD data, with AARD values between 1.21 % and 4.40 %, suggesting they can be used for diffusivity estimations over wider ranges of operating conditions.

Influence of Ethanol Parametrization on Diffusion Coefficients Using OPLS-AA Force Field.

Molecular dynamics simulations employing the all-atom optimized potential for liquid simulations (OPLS-AA) force field were performed for determining self-diffusion coefficients (D11) of ethanol and tracer diffusion coefficients (D12) of solutes in ethanol at several temperature and pressure conditions. For simulations employing the original OPLS-AA diameter of ethanol's oxygen atom (σOH), calculated and experimental diffusivities of protic solutes differed by more than 25%. To correct this behavior, the σOH was reoptimized using the experimental D12 of quercetin and of gallic acid in liquid ethanol as benchmarks. A substantial improvement of the calculated diffusivities was found by changing σOH from its original value (0.312 nm) to 0.306 nm, with average absolute relative deviations (AARD) of 3.71% and 4.59% for quercetin and gallic acid, respectively. The new σOH value was further tested by computing D12 of ibuprofen and butan-1-ol in liquid ethanol with AARDs of 1.55% and 4.81%, respectively. A significant improvement was also obtained for the D11 of ethanol with AARD = 3.51%. It was also demonstrated that in the case of diffusion coefficients of non-polar solutes in ethanol, the original σOH=0.312 nm should be used for better agreement with experiment. If equilibrium properties such as enthalpy of vaporization and density are estimated, the original diameter should be once again adopted.

A general expression for the statistical error in a diffusion coefficient obtained from a solid-state molecular-dynamics simulation.

Analysis of the mean squared displacement of species , , as a function of simulation time constitutes a powerful method for extracting, from a molecular-dynamics (MD) simulation, the tracer diffusion coefficient, . The statistical error in is seldom considered, and when it is done, the error is generally underestimated. In this study, we examined the statistics of curves generated by solid-state diffusion by means of kinetic Monte Carlo sampling. Our results indicate that the statistical error in depends, in a strongly interrelated way, on the simulation time, the cell size, and the number of relevant point defects in the simulation cell. Reducing our results to one key quantity-the number of particles that have jumped at least once-we derive a closed-form expression for the relative uncertainty in . We confirm the accuracy of our expression through comparisons with self-generated MD diffusion data. With the expression, we formulate a set of simple rules that encourage the efficient use of computational resources for MD simulations.

Using LAMMPS to shed light on Haven’s ratio: Calculation of Haven’s ratio in alkali silicate glasses using molecular dynamics

Haven and Verkerk studied the diffusion of ions in ionic conductive glasses with and without an external electric field to better understand the mechanisms behind ionic conductivity. In their work, they introduced the concept now known as Haven’s ratio (HR), which is defined as the ratio of the tracer diffusion coefficient (Dself) of ions to the diffusion coefficient from steady-state ionic conductivity (Dσ), calculated by the Nernst–Einstein equation. Dσ can be challenging to obtain experimentally because the number of charge carriers has to be implied, a subject still under discussion in the literature. Molecular dynamics (MD) allows for direct measurement of the mean squared displacement (r2) of diffusing cations, which can be used to calculate D, avoiding the definition of a charge carrier. Using MD, the authors have calculated the r2 of three alkali ions (Li, Na, and K) at different temperatures and concentrations in silicate glass, with and without the influence of an electric field. Results found for HR generally fell close to 0.6 at lower concentrations (x = 0.1) and close to 0.3 at higher concentrations (x = 0.2 and 0.3), comparable to the literature, implying that the electric field introduces new mechanisms for the diffusion of ions and that MD can be a powerful tool to study ionic diffusion in glasses under external electric fields.

Effect of the thermodynamic factor on the intrinsic and tracer diffusivities in binary mixtures.

One of the Darken equationsgives a relationship between the intrinsic and the tracer diffusion coefficients, D_{A} and D_{A}^{*}, of species A in a solid binary mixture. In its original formulation, the equationreads D_{A}=D_{A}^{*}Γ, with Γ the thermodynamic factor. The question addressed in this paper is how D_{A} and D_{A}^{*} depend separately on Γ. Using a recent result for transition probabilities in terms of the excess chemical potential [M. Di Muro and M. Hoyuelos, Phys. Rev. E 104, 044104 (2021)2470-004510.1103/PhysRevE.104.044104], it is shown that the intrinsic diffusivity does not depend on Γ. This approach simplifies a previous theoretical analysis that reaches the same result. Experimental results of diffusion in Ni-Pd and Fe-Pd alloys [M. J. H. van Dal et al., Acta Mater. 48, 385 (2000)1359-645410.1016/S1359-6454(99)00375-4] are used to check the theory. Numerical simulations of Ni-Pd were performed to show that the migration energy is the main factor responsible for the increase in diffusivity at intermediate concentrations.

Diffusivities of ketones and aldehydes in liquid ethanol by molecular dynamics simulations

The tracer diffusion coefficients of six ketones (propanone, butanone, pentan-2-one, pentan-3-one, hexan-2-one, hexan-3-one) and six aldehydes (methanal, ethanal, propanal, butanal, pentanal and hexanal) in liquid ethanol were computed by classical molecular dynamics (MD) simulations over 303.15–333.15 K and 1–150 bar. The calculated tracer diffusion coefficients, D12MD, compared very satisfactorily with experimental data from the literature, with average absolute relative deviations (AARD) between 9.48 % and 12.18 % for ketones, and between 6.30 % and 9.11 % for aldehydes. The trends of D12MD with solute size and temperature were accurately simulated in all cases, while the weaker influence of pressure was not rigorously reached in all cases when jumping from 1 to 75 bar and then to 150 bar. Furthermore, a temperature-based correction to D12MD was introduced, which decreased the AARD values of ketones to the range 1.52–5.16 % and aldehydes to 2.94–3.45 %. The analyses of the spatial distribution functions and coordination numbers show that ethanol has more affinity with ketones than with aldehydes, though such affinity difference is not always translated to the computed D12MD of ketone-aldehyde isomers. Nevertheless, the experimental diffusivities of both families of compounds are only ca. 7 % different, hence within the uncertainties associated with the calculated results.