Diffusion Coefficient Data Research Articles

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.

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.

Application of group method of data handling and gene expression programming to modeling molecular diffusivity of CO2 in heavy crudes

Successful enhancement of heavy oil and bitumen production using CO2-based enhanced oil recovery (EOR) techniques requires extensive knowledge about the diffusivity of CO2 in heavy crudes. In this work, two advanced correlative approaches, namely group method of data handling (GMDH) and gene expression programming (GEP), were utilized to establish simple-to-use mathematical correlations by applying a comprehensive dataset including 260 laboratory data of CO2 diffusion coefficient (DC) in heavy crudes and taking into account all the parameters affecting the accuracy of the models. Moreover, the response surface and contour plots were analyzed to obtain the desired response values and operating conditions. The GMDH correlation represented more reliable results with better statistical criteria including average absolute percentage error (AAPRE) values of 7.47%, 7.83%, and 7.54% for training, testing, and the total sets, respectively. Also, the results showed that the increase in pressure and/or temperature caused an increment in the amount of diffusivity of CO2 in heavy crudes; and the maximum amount of CO2 DC was obtained at the upper limit of these operational parameters. At a given temperature and pressure, it appears that the highest CO2 DC in heavy crudes was obtained when the CO2 mass fraction was less than 0.02. Furthermore, the Pearson and Spearman correlation coefficients were used to investigate linear and non-linear relationships between input variables and the responses of GMDH and GEP correlations. The mass fraction of CO2, temperature, pressure, and temperature_PVT had a direct relationship, and on the other hand, the viscosity and density of crudes had a reverse relationship with CO2 DC. Finally, the reliability of the data bank of CO2 DC in heavy crudes along with the high validity of GMDH and GEP correlations was verified by the leverage technique. Notably, no out-of-leverage data were identified, with only seven and five data points considered as suspected for GMDH and GEP models, respectively.

Toward the Improvement of the Short‐Loop Recycling of Dy‐Rich Nd–Fe–B Permanent Magnets: Experimental and Numerical Approaches

The method of short‐loop recycling of Nd–Fe–B magnets is implemented, with end‐of‐life (EoL) magnets used as a source of heavy rare earth (HRE). Partially recycled magnets are fabricated by co‐sintering HRE‐free powders obtained from strip casted alloys, blended with HRE‐rich powders obtained from EoL magnets. The impact of several process parameters (blending ratio, sintering cycle, and HRE‐rich recycled particle sizes) on the microstructure and magnetic properties is discussed. A coercivity gain up to 160 kA m−1 wt%−1 of Dy with respect to the HRE‐free magnets is reported, even though impurities are incorporated. Microstructural characterizations show a heterogeneous Dy localization in core–shell/anticore–shell structures, and thus a nonoptimal use of HRE. The experimental results are compared with finite element simulations of the Dy diffusion transport performed using existing data of bulk Dy diffusion coefficients. The simulation model consists of a network of square grains separated by a liquid phase, whose fraction is based on the ternary Nd–Fe–B phase diagram. Results show similarities with the observed microstructures, and point to the interest of reducing the Dy‐rich particle size with respect to the main powder. This study provides new insights into the Dy transport mechanisms at stake in an efficient short‐loop recycling of HRE.

Diffusivity of CO2 in H2O: A Review of Experimental Studies and Molecular Simulations in the Bulk and in Confinement.

An in-depth review of the available experimental and molecular simulation studies of CO2 diffusion in H2O, which is a central property in important industrial and environmental processes, such as carbon capture and storage, enhanced oil recovery, and in the food industry is presented. The cases of both bulk and confined systems are covered. The experimental and molecular simulation data gathered are analyzed, and simple and computationally efficient correlations are devised. These correlations are applicable to conditions from 273 K and 0.1 MPa up to 473 K and 45 MPa. The available experimental data for diffusion coefficients of CO2 in brines are also collected, and their dependency on temperature, pressure, and salinity is examined in detail. Other engineering models and correlations reported in literature are also presented. The review of the simulation studies focuses on the force field combinations, the data for diffusivities at low and high pressures, finite-size effects, and the correlations developed based on the Molecular Dynamics data. Regarding the confined systems, we review the main methods to measure and compute the diffusivity of confined CO2 and discuss the main natural and artificial confining media (i.e., smectites, calcites, silica, MOFs, and carbon materials). Detailed discussion is provided regarding the driving force for diffusion of CO2 and H2O under confinement, and on the role of effects such as H2O adsorption on hydrophilic confining media on the diffusivity of CO2. Finally, an outlook of future research paths for advancing the field of CO2 diffusivity in H2O at the bulk phase and in confinement is laid out.

Measurement of binary diffusion at elevated Knudsen numbers using laser absorption spectroscopy

Mass diffusion coefficients of gas mixtures have been measured for more than 100 years. However, the experimental data for the mass diffusion coefficient of gas mixtures in the rarefied gas regimes at Knudsen numbers (Kn) above 0.01 are few and remain uncertain due to the inherent precision limitations of the available state-of-the-art measurement techniques. The increased frequency of gas-wall collision, wall-friction, and surface-diffusion over the wall surface at Kn > 0.01 increases the uncertainty of the diffusive mass transport processes for internal gas flow in microcapillaries. Due to the growing interest in microfluidic applications at rarefied gas conditions, accurate diffusion coefficient measurements are needed to inform theoretical predictions and empirical relations in rarefied gas regimes. Thus, this article introduces a new experiment methodology consisting of a two-bulb (TB) diffusion configuration accompanied by a tunable diode laser absorption spectroscopy (TDLAS) detection technique that uses the measured time history of path-integrated absorbance to provide a non-intrusive, species-specific, in situ measurement of mass diffusion for a He–CO2 binary gas mixture at Kn > 0.01. To demonstrate the TB-TDLAS method's capability, the effective diffusion coefficient for a He–CO2 binary gas mixture was measured in the transition gas regime at Knudsen numbers relative to the tube radius in the range 0.1 < Kn < 5.4, and the results are compared against the Bosanquet empirical relation.

Evaluation of different equations of state and free-volume approaches for unified modeling of diffusion and thermodiffusion coefficients

This article is a development and testing of the previously suggested theoretical approach for simultaneous thermodynamic modeling of diffusion and thermodiffusion coefficients. The new theoretical framework allows for the calculation of transport properties with the aid of the concepts of penetration distances and emission functions, which are fully determined from thermodynamic equations that relate functions of state variables, that is, equations of state (EoS). Four underlying EoS were tested in this work, 3 different cubic EoS and PC-SAFT, with the aim of investigating the effect of the thermodynamic model on the description of experimental data. We also investigated the impact of different approaches to estimating the free volume, which is an essential part of the model. The results indicate that the application of the effective co-volume provides a superior representation of the diffusion and thermodiffusion coefficients, which should be included in the parameterization procedure for the selection of the unified model parameters. We evaluated the use of infinite dilution diffusion coefficient data and molecular dynamics simulation to validate model parameters, and discussed the possible ways to improve the model, including predicting diffusion data as a function of temperature.

Molecular Dynamics Simulation of Diffusion Behavior in Liquid Sn and Pb

This study aimed to clarify the effect of a unique structure with a “shoulder,” which represents a hump on the high wave vector side of the first peak of static structure factor, in liquid Sn (liq-Sn) on the self-diffusion behavior through molecular dynamics (MD) simulation. The MD simulations of liq-Sn at 573 K and liquid Pb (liq-Pb) at 773 K were performed for comparison. The former and latter were selected as element with and without shoulder structure and reliable self-diffusion coefficients in liquid have been measured in both elements. The calculated self-diffusion coefficients of liq-Sn and liq-Pb were reproduced as the same order of magnitude with the referred reliable data of diffusion coefficients, which were obtained by experiments on the ground. The microscopic diffusion behavior of liq-Sn is unlike that of the hard-sphere model because the atoms become sluggish in the range that corresponds to the shoulder appearing in the pair distribution function of liq-Sn as well as in the structure factor of liq-Sn based on the local atomic configurations and time-series analyses of individual atoms. Therefore, the velocity autocorrelation function (VACF) converges to zero more rapidly than that of liq-Pb, and it is reproduced by the hard-sphere model. However, the macroscopic diffusion behavior of liq-Sn expressed by the self-diffusion coefficient is the same as that of the hard-sphere model with the non-correlation of the VACF in the long time.

Diffusion of hydrocarbons diluted in supercritical carbon dioxide

Mutual diffusion of six hydrocarbons (methane, ethane, isobutane, benzene, toluene or naphthalene) diluted in supercritical carbon dioxide ({hbox {CO}}_{2}) is studied by molecular dynamics simulation near the Widom line, i.e., in the temperature range from 290 to 345 K along the isobar 9 MPa. The {hbox {CO}}_{2} + aromatics mixtures are additionally sampled at 10 and 12 MPa and an experimental database with Fick diffusion coefficient data for those systems is provided. Taylor dispersion experiments of {hbox {CO}}_{2} with benzene, toluene, n-dodecane and 1,2,3,4-tetrahydronaphthalene are conducted along the p = 10 MPa isobar. Maxwell–Stefan and Fick diffusion coefficients are analyzed, together with the thermodynamic factor that relates them. It is found that the peculiar behavior of the Fick diffusion coefficient of some {hbox {CO}}_{2} mixtures in the extended critical region is a consequence of the thermodynamic factor minimum due to pronounced clustering on the molecular scale. Further, the strong dependence of the Fick diffusion coefficient on the molecular mass of the solute as well as the breakdown of the Stokes–Einstein relation near the Widom line are confirmed. Eleven correlations for the prediction of the Fick diffusion coefficient of {hbox {CO}}_{2} mixtures are assessed. An alternative two-step approach for the prediction of the infinite dilution Fick diffusion coefficient of supercritical {hbox {CO}}_{2} mixtures is proposed. It requires only the state point in terms of temperature and pressure (or density) as well as the molecular solute mass as input parameters. First, entropy scaling is applied to estimate the self-diffusion coefficient of {hbox {CO}}_{2}. Subsequently, this coefficient is used to determine the infinite dilution Fick diffusion coefficient of the mixture, based on the finding that these two diffusion coefficients exhibit a linear relationship, where the slope depends only on the molecular solute mass.

Reactive Force Field (ReaxFF) and Universal Force Field Molecular Dynamic Simulation of Solid Electrolyte Interphase Components in Lithium-Ion Batteries

Abstract Understanding solid electrolyte interphase (SEI) is essential for the diagnosis of lithium-ion batteries because many aspects of battery performance such as safety and efficiency depend on these characteristics. LiF, Li2O, and Li2CO3 are important inorganic components of SEI. This electrode–electrolyte surface forms during the battery’s first charging/discharging cycle, preventing electrons’ movement through the electrolyte and stabilizing the lithium-ion battery. However, the concern is inorganic SEI components cause rate limitation of lithium-ion diffusivity through the SEI layer. Lithium-ion diffusivity through the SEI layer depends on many factors such as temperature, the width of the SEI layer, and the concentration/density of the layer. Lithium-ion diffusivity dependence on temperature, at working temperatures of lithium-ion batteries was observed at temperatures from 250 K to 400 K and diffusion coefficient data at higher temperatures have also been observed. Lithium-ion diffusivity at varying concentration/density was also observed in this paper using the reactive force field (ReaxFF) molecular dynamic simulation. To improve the lithium-ion diffusivity, vacancy defects were created in the inorganic components of the SEI layer LiF, Li2O, and Li2CO3 and the diffusion coefficient was obtained using the ReaxFF molecular dynamic simulations. Another approach to improve the lithium-ion diffusivity is doping alkali metal ions such Na, Ca, K, and Mg in the inorganic components of SEI layers of LiF, Li2O, and Li2CO3 and simulated using the universal force field (UFF), and the diffusion coefficient was observed.

Measurements of the molecular diffusion coefficient of dimethyl ether (DME) in n-decane and DME-saturated liquid viscosity at T= (293.15 – 393.15) K and P= (0.345 – 2.76) MPa

We report a new data set on the molecular diffusion coefficient of dimethyl ether (DME) in n-decane and DME-saturated liquid viscosity at T = (293.15–393.15) K and P = (0.345–2.76) MPa. The viscosity measurements are modeled using the Pedersen correlation with an Absolute average relative deviation (AARD) of 4.7%. The molecular diffusion coefficient of DME in n-decane is measured using a constant pressure technique. The measured diffusion coefficient data are in the range of (1.5–8.9) × 10−9 m2/s. Diffusion coefficient data shows a non-monotonic behavior with respect to pressure. The diffusion coefficient measurements at different pressures are modeled with Arrhenius-type kinetics, and the activation energy and pre-exponential factor are estimated with an overall AARD of 3.38%. The activation energy and the pre-exponential factor showed non-monotonic behavior with respect to pressure. The diffusion data are also correlated with Siddiqi−Lucas and Hayduk-Minhas’ empirical correlations with AARDs of 7% and 6.2%, respectively. The swelling factor is also calculated for the diffusion process of the DME/ n-decane binary system.

Local structures and undercooling ability of Zr–Ti melts

We developed an accurate model of Zr–Ti melts for classical molecular-dynamics simulations via regauging the existing embedded-atom method (EAM) potential, using particularly the diffusion coefficient data obtained from quasielastic neutron scattering. This EAM potential well reproduces the properties of the melts observed in experiments, including mass density, transport coefficients, melting temperatures, and static structure factors. The latter are also obtained from ab initio simulations. Using the developed EAM potentials, we analyzed the short-range order of the liquids and found a chemically preferred formation of Zr–Zr and Zr–Ti nearest neighbor pairs. When decreasing the temperature the number of icosahedral-like aggregates increases on the expense of more crystal-like structures. This is most pronounced at intermediate alloy compositions. At intermediate compositions also the lowest thermodynamic driving force for crystallization is found, resulting in the largest undercooling ability of the alloys.

Thermophysical properties of the energy carrier methanol under the influence of dissolved hydrogen

The present experimental work focuses on revealing the influence of hydrogen (H2) on the interfacial tension, viscosity, density, and thermal diffusivity of the liquid phase of the energy carrier methanol under saturation conditions, which has been only fragmentarily investigated so far, and on providing corresponding H2 solubility and Fick diffusion coefficient data. For this, conventional methods, dynamic light scattering from the liquid bulk and from the liquid-gas interface as well as Raman spectroscopy were used at temperatures up to 393 K and pressures up to 8 MPa. The results show that with H2 under saturation conditions, the viscosity and density of liquid methanol are nearly pressure-independent, whereas the interfacial tension is reduced by about 6% at 8 MPa. The latter effect is temperature-independent despite the increasing H2 concentration with increasing temperature, which may be associated with a counteracting influence of temperature on a presumed surface enrichment of H2.

Electrochemistry and Mass Transport of Ytterbium(III) in Bis(trifluoromethylsulfonyl)imide-Based Room-Temperature Ionic Liquids: Effects of Temperature, Viscosity, and Electrode Materials

Cyclic staircase voltammetry, rotating disk electrode voltammetry, controlled potential coulometry, and electrochemical impedance spectroscopy were used to probe the electrochemistry and mass transport of Yb3+ in the six room temperature ionic liquids based on the bis(trifluoromethylsulfonyl)imide (Tf2N−) anion with, 1-(1-butyl)−3-methylimidazolium (BuMeIm+), 1-(1-butyl)−1-methylpyrrolidinium (BuMePyro+), 1-(1-butyl)pyridinium (BuPy+), 1-butyltrimethylammonium (BuMe3N+), 1-ethyl-3-methylimidazolium (EtMeIm+), and tri(1-butyl)methylammonium (Bu3MeN+) cations. These investigations were carried out at glassy carbon as well as polycrystalline gold, platinum, and tungsten electrodes. The heterogeneous electron transfer rate of the quasireversible Yb3+/2+ redox couple was found to depend strongly on the electrode materials with the fastest rate observed at gold and the slowest rate found at tungsten, but was independent of the physicochemical properties of the various ionic liquids, in particular, the absolute viscosity. However, the mass transport of Yb3+ was dependent on the viscosity, and the temperature dependence of the diffusion coefficients was well represented by a Vogel-Tammann-Fulcher type expression for glass-forming ionic liquids. Analysis of the diffusion coefficient data with the Stokes-Einstein equation indicated that the solvodynamic radius of the diffusing Yb3+ was constant and independent of the structure and properties of the ionic liquid cations. The solvodynamic radius of Yb3+ was estimated from the “stick model” for the Stokes-Einstein equation. Application of the Random Closest Packing (RCP) model for spheres in consideration of the solvodynamic radius of the diffusing Yb3+ and the ionic radii of Yb3+ and Tf2N−, indicated that the former must diffuse in association with ∼5–6 of the anions.

Evaluation of CO2 absorption and stripping process for primary and secondary amines

ABSTRACT An effective approach for lowering CO2 emissions from industrial processes is the absorption method of CO2 capture. Because of the high energy required to break the bond of the carbamate ions during the stripping process, the intramolecular interaction (repulsive interaction) of Ncarbamate-Ccarbamate was discovered to be the main interaction. Therefore, the purpose of this study is to examine the amine-CO2 bond strength for various carbamate molecules during the regeneration process using molecular dynamic modelling, as well as to explore the diffusion coefficient of various amines. The results of interaction intensity show that in comparison to other studied amines for inter – and intra-molecular interactions N, N, N′, N′-tetramethylpropane-1,3-diamine (TMPAD), N-dimethylcyclohexanamine (DMCA) and 4-diethylamino-2-butanol (DEAB) were easy to break. It shows that the TMPAD has the highest repulsive interaction; consequently, it needs the lowest energy to break the carbamate ion in the stripping process as compared to MEA. The order of regeneration energy required to break the bond for Ncarbamate-Ccarbamate in various selected amines from higher to lower is MEA > 2MAE > PZ > 2DMAE > 2EAE > AMP > 1DMA2P > MCA > DMCA > DEAB > TMPAD. The diffusion coefficient data for various blends reveal that the 2MAE-DEAB blend has the highest rate of diffusion when compared to other blends (2MAE-1DMA2P and 2MAE-TMPAD).

Local null controllability of a quasi-linear system and related numerical experiments

This paper concerns the null control of quasi-linear parabolic systems where the diffusion coefficient depends on the gradient of the state variable. In our main theoretical result, with some assumptions on the regularity and growth of the diffusion coefficient and regular initial data, we prove that local null controllability holds. To this purpose, we consider the null controllability problem for the linearized system, we deduce new estimates on the control and the state and, then, we apply a Local Inversion Theorem. We also formulate an iterative algorithm of the quasi-Newton kind for the computation of a null control and an associated state. We apply this method to some numerical approximations of the problem and illustrate the results with several experiments.

Heterogeneity evaluation of multi-high b-value apparent diffusion coefficient on cerebral ischemia in MCAO rat.

To assess brain damage in a rat model of cerebral ischemia based on apparent diffusion coefficient (ADC) data obtained from multi-high b-values and evaluate the relationship between Aquaporin 4 (AQP4) expression and ADC. Thirty eight male Sprague-Dawley rats were randomized into two groups: (1) sham controls (n = 6) and (2) cerebral ischemia (successful model, n = 19). All rats underwent diffusion-weighted imaging (DWI) with both standard b-values and multi-high b-values (2,500-4,500 s/mm2) using a 3.0-T device. Standard ADC (ADCst) maps and multi-high b-value ADCs (ADCmh) were calculated, respectively. Aquaporin 4 expression was quantified using Western blot. Relative values of ADCst and ADCmh, AQP4 expression were compared between the sham group and the ischemia group. Correlations between ADC values and AQP4 expression were evaluated. At 0.5 h after suture insertion, the value of ADCmh on the lesion was obviously decreased, and there was no difference in lesion volume when compared with ADCst. After reperfusion, besides similar regions where ADCst values decreased, we also found additional large values on ADCmh within the cortex of the ipsilateral side or surrounding the lesion. The lesion evolution of the large value on ADCmh was quite different from other indicators. But the total ADCmh values were still significantly associated with ADCst. The AQP4 protein expression level was appreciably increased after middle cerebral artery occlusion (MCAO), but there was no correlation between AQP4 expression either with ADCmh or ADCst. We found the large values on ADCmh during the progression of cerebral infarction is varied, but there was no correlation between ADCmh values and AQP4 expression. ADCmh may indicate the heterogeneity of ischemia lesions, but the underlying pathological basis should be further explored.

Molecular dynamics simulation of corrosion and its inhibition: comparison of structural stability of Fe/FeNi/FeNiCr/FeNiCrTi steels under high-temperature liquid lead

The liquid lead used in fast nuclear reactor has been known to be able to cause a significant damage to the steels. Therefore, finding new materials with high corrosion resistance is the goal of much research current days. Likewise, developing a way to prevent corrosion is also the goal of designers of nuclear reactors. In the present study, we studied materials: Fe, FeNi, FeNiCr, and FeNiCrTi (a type of SS 316L austenite steel), comparing their structural stability when interacted with molten liquid lead at 750 °C. The performance of each steel is compared under high-temperature molten lead coolant, checking the structure's stability to see the material resistance to corrosion attack of liquid lead. The corrosion can also be seen from the data of iron diffusion coefficient. The larger of the iron diffusion coefficient can be associated with larger corrosion because there is a high solubility of iron atoms from the steel surface to the molten lead. The popular way to prevent more corrosion is by injecting oxygen into the lead coolant. This current work uses the molecular dynamics method to simulate the corrosion and inhibition phenomena. The research aims to compare the performance of Fe, FeNi, FeNiCr, and FeNiCrTi under liquid lead at a temperature of 750. The diffusion coefficient of iron of material will be calculated to describe quantitatively the corrosion level of those structural materials and the corrosion inhibition by oxygen injection. The study has produced important results that adding Ni, Cr, Ti into a pure iron crystal to build alloy steel will make the material stronger, structurally compact, and more resistant to corrosion. For specific composition of steels, from weaker to stronger that resist from corrosion attack, it is possible to make ordering: Fe<<FeNi<FeNiCr<FeNiCrTi. The composition of FeNiCrTi steel in this work is Fe(75)Ni(10.57)Cr(14.05)Ti(0.40). The high corrosion of FeNiCrTi in the liquid lead is effectively reduced by injecting 0.0112 wt % oxygen into lead coolant as a limit value for maximum corrosion inhibition

Diagnostic performance of mono-exponential DWI versus diffusion kurtosis imaging in breast lesions: A meta-analysis.

This meta-analysis aimed to explore the diagnostic value of diffusion kurtosis imaging (DKI) compared to mono-exponential diffusion weighted imaging (DWI) in the diagnosis of breast cancer. A systematic electronic literature search (up to September 2020) was conducted for published English-language studies comparing the diagnostic values of DKI and DWI for the detection of breast cancer. The data of mean kurtosis (MK), mean diffusivity (MD), and apparent diffusion coefficient (ADC) were extracted to construct 2 × 2 contingency tables. The pooled sensitivities, specificities, and areas under the receiver operating characteristic curve (AUCs) were compared between DKI and DWI in the diagnosis of breast cancer. Eight studies were finally included, with a total of 771 patients in the same population. Pooled sensitivities were 82.0% [95% confidence interval (95% CI), 78.2-85.3%] for ADC, 87.3% (95% CI, 83.9-90.1%) for MK, and 83.9% (95% CI, 80.2-87.1%) for MD. Pooled specificities were 81.1% (95% CI, 76.7-84.9%) for ADC, 85.1% (95% CI, 81.1-88.5%) for MK, and 83.2% (95% CI, 79.0-86.8%) for MD. According to the summary receiver operator characteristic curve analyses, the AUCwas 0.901 for ADC, 0.930 for MK, and 0.918 for MD (ADC vs MK, P = .353; ADC vs MD, P = .611). No notable publication bias was found, while significant heterogeneity was observed. Although DKI is feasible for identifying breast cancer, MD and MK offer similar diagnostic performance to ADC values. Thus, we recommend that DKI should not be included in the routine evaluation of breast lesions now.

Diffusion Coefficients in Systems Related to Reservoir Fluids: Available Data and Evaluation of Correlations

Molecular diffusion determines the time to reach local equilibrium in a reservoir. It can be a main production mechanism in scenarios such as production from fractured reservoirs or tight formation. However, there is a lack of high-pressure diffusion coefficients for reservoir fluids and its related systems. Many correlations exist, but there is no consensus on their accuracy for these systems. We provide a systematic review of the available data for systems related to reservoir fluids, as well as a comprehensive comparison of five commonly used correlations for hydrocarbon mixtures, including the extended Sigmund, Riazi-Whitson, Leahy-Dios-Firoozabadi, Wilke–Chang, and the Hayduk–Minhas correlations. We collected extensive data of diffusion coefficients in binary mixtures related to petroleum fluids and established a database of over 80 binaries and 1600 data points. We also collected the data for gas diffusion in different oils and reservoir fluids, but the data in high-pressure live oils are extremely scarce. The five correlations were evaluated using the binary database, and a few selected correlations using the oil database. None of the correlations show consistent and dominant superiority for all the binary mixtures, although some are better for particular groups/regions. For oils and reservoir fluids, the composition information is often incomplete. Only a few sets allow a comparison between different correlations. Although some trends can be identified from the correlation evaluation, no conclusive recommendation is made for a particular model, due to the data scarcity. The findings underscore the need for more accurate measurement and modeling of gas diffusion in mixtures that are more representative of reservoir fluids at high pressures.