Molecular Diffusion Coefficient Research Articles

Mass transfer of solute in an oscillating flow in a two-dimensional channel

The effective diffusion of a solute in a rectangular two-dimensional channel is experimentally studied. We experimentally examine the effective diffusion of Rhodamine B dissolved in water oscillating in a rectangular Hele–Shaw cell. The concentration of Rhodamine B in water is measured by the intensity of its fluorescence emission. In particular, we consider two problems: (i) effective diffusion of solute in water oscillating in a two-dimensional rectangular channel (Hele–Shaw cell) and (ii) effective diffusion of solute in pores between monosized hard spheres randomly packed in a rectangular Hele–Shaw cell. It is revealed that the rate of solute mass transfer exceeds the molecular diffusion rate in both cases. It has been demonstrated that when water oscillates between parallel walls, diffusion is accelerated by Taylor dispersion with the effective diffusion coefficient Deff exceeding the molecular diffusion coefficient Dm by 1–2 orders of magnitude. The effective diffusion coefficient Deff depends only on the relative amplitude but not on the frequency of the fluid oscillations in the studied range of frequencies and amplitudes. When the fluid oscillates in the pores of the porous medium, solute transport is faster than in the case of Taylor dispersion. Here, the effective diffusion coefficient depends on both the frequency and amplitude of oscillations. The analysis shows that the experimental data obtained at various frequencies and amplitudes of oscillations are consistent with the relation Deff/Dm∼Pe2 (Pe is the Peclet number). We suggest that the enhanced solute mass transfer is associated with the time-averaged fluid flows that arise due to spatial heterogeneity of the amplitude of water oscillations in the pores between randomly packed hard spheres.

Convection-Enhanced Drug Delivery: Experimental and Analytical Studies of Infusion Behavior in an In Vitro Brain Surrogate.

Convection-enhanced drug delivery (CED) directly infuses drugs with a large molecular weight toward target cells as a therapeutic strategy for neurodegenerative diseases and brain cancers. Despite the success of many previous in vitro experiments on CED, challenges still remain. In particular, a theoretical predictive model is needed to form a basis for treatment planning, and developing such a model requires well-controlled injection tests that can rigorously capture the convective (advective) and diffusive transport of an infusate. For this purpose, we investigated the advection-diffusion transport of an infusate (bromophenol blue solution) in the brain surrogate (0.2% w/w agarose gel) at different injection rates, ranging from 0.25 to 4 μL/min, by closely monitoring changes in the color intensity, propagation distance, and injection pressures. One dimensional closed-form solution was examined with two variable sets, such as the mathematically calculated coefficient of molecular diffusion and average velocity, and the hydraulic dispersion coefficient and seepage velocity by the least squared method. As a result, the seepage velocity was greater than the average velocity to some extent, particularly for the later infusion times. The poroelastic deformation in the brain surrogate might lead to changes in porosity, and consequently, slight increases in the actual flow velocity as infusion continues. The limitation of efficiency of the single catheter was analyzed by dimensionless analysis. Lastly, this study suggests a simple but robust approach that can properly capture the convective (advective) and diffusive transport of an infusate in an in vitro brain surrogate via well-controlled injection tests.

Analysis of IVIM Perfusion Fraction Improves Detection of Pancreatic Ductal Adenocarcinoma.

The purpose of this study was to evaluate whether intravoxel incoherent motion (IVIM) parameters can enhance the diagnostic performance of MRI in differentiating normal pancreatic parenchyma from solid pancreatic adenocarcinomas. This study included 113 participants: 66 patients diagnosed with pancreatic adenocarcinoma and 47 healthy volunteers. An MRI was conducted at 1.5 T MR unit, using nine b-values. Postprocessing involved analyzing both conventional monoexponential apparent diffusion coefficient (ADC) and IVIM parameters (diffusion coefficient D-pure molecular diffusion coefficient, perfusion-dependent diffusion coefficient D*-pseudodiffusion coeffitient, and perfusion fraction coefficient (f)) across four different b-value selections. Significantly higher parameters were found in the control group when using high b-values for the pure diffusion analysis and all b-values for the monoexponential analysis. Conversely, in the study group, the parameters were affected by low b-values. Most parameters could differentiate between normal and cancerous tissue, with D* showing the highest diagnostic performance (AUC 98-100%). A marked decrease in perfusion in the patients with pancreatic cancer, indicated by the significant differences in the D* medians between groups, was found. In conclusion, standard ADC maps alone may not suffice for a definitive pancreatic cancer diagnosis, and incorporating IVIM into MRI protocols is recommended, as the reduced tissue perfusion detected by the IVIM parameters is a promising marker for pancreatic adenocarcinoma.

Temporal Evolution of Solute Dispersion in Three‐Dimensional Porous Rocks

AbstractWe study the temporal evolution of solute dispersion in three‐dimensional porous rocks of different heterogeneity and pore structure. To this end, we perform direct numerical simulations of pore‐scale flow and transport in a sand pack, which exhibits mild heterogeneity, and a Berea sandstone, which is characterized by strong heterogeneity as measured by the variance of the logarithm of the flow velocity. The impact of medium structure and pore‐scale mass transfer mechanisms is probed by effective and ensemble dispersion coefficients. The former is a measure for the typical width of a plume, while the latter for the deformation, that is, the spread of a mixing front. Both dispersion coefficients evolve from the molecular diffusion coefficients toward a common finite asymptotic value. Their behavior is governed by the interplay between diffusion, pore‐scale velocity fluctuations and medium structure, which determine the characteristic mass transfer time scales. We find distinctly different dispersion behaviors in the two media, which can be traced back to how particles sample pore‐scale velocity variability and how this depends on the medium structure. These are key elements for the upscaling of transport, mixing and reaction from the pore to the continuum scale.

Application of CFD Modelling for Pollutant Dispersion at an Urban Traffic Hotspot

Health factors concerning the well-being of the urban population urge us to better comprehend the impact of emissions in urban environments on the micro-scale. There is great necessity to depict and monitor pollutant concentrations with high precision in cities, by constructing an accurate and validated digital air quality network. This work concerns the development and application of a CFD model for the dispersion of particulate matter, CO, and NOx from traffic activity in a highly busy area of the city of Augsburg, Germany. Emissions were calculated based on traffic activity during September of 2018 with COPERT Street software version 2.4. The needed meteorological data for the simulations were taken from a sensor’s network and the resulting concentrations were compared and validated with high-precision air quality station indications. The model’s solver used the steady-state RANS approach to resolve the velocity field and the convection–diffusion equation to simulate the pollutant’s dispersion, each one modelled with different molecular diffusion coefficients. A sensitivity analysis was performed to decide the most efficient computational mesh to be used in the modelling. A velocity profile for the atmospheric boundary layer (ABL) was implemented into the inlet boundary of each simulation. The cases concerned applications on the street level in steady-state conditions for one hour. The results were evaluated based on CFD validation metrics for urban applications. This approach provides a comprehensive state-of-the-art 3D digital pollution network for the area, capable of assessing contamination levels at the street scale, providing information for pollution reduction techniques in urban areas, and combining with existing sensor networks for a more thorough portrait of air quality.

A pore-scale numerical framework for solute transport and dispersion in porous media

Pore-scale modeling plays a crucial role in understanding and upscaling solute transport behavior in porous media. Direct simulation offers the highest fidelity in resolving pore-scale fluid flow and mass transfer, nevertheless, with unacceptable computational costs for practical applications. Pore network models (PNM), on the other hand, provide an efficient alternative but with reduced accuracy in representing transport dynamics. In this study, we propose a new framework of pore network models that ensures both accuracy and efficiency, which reproduces the pore-scale shear dispersion effect by utilizing the pore-scale shear dispersion coefficient to calculate the diffusive mass exchange rate between network elements. The coefficient is determined based on the extension of Taylor-Aris theory that expands the classical Taylor-Aris theory to encompass the pre-asymptotic regime. Additionally, the framework adopts a physically representative pore network, where the conduit length and volume of network elements are determined based on local resistance equivalence. After verifying its accuracy and reliability, we conduct a series of numerical cases on tube networks, sphere packs, and sand packs. The breakthrough curves and concentration profiles obtained from our new model show good agreement with direct simulation results and experimental data, while the simulation outcomes of the models that rely on the molecular diffusion coefficient or Taylor dispersion coefficient for local mass exchange may exhibit significant errors. We finally demonstrate that the significance of pore-scale shear dispersion on solute transport weakens for tube networks with increasing degrees of geometrical disorder. The proposed model provides an accurate and efficient numerical framework for the study of solute transport and dispersion in porous media.

Detailed analysis of the effective and intra-particle diffusion coefficient of proteins at elevated pressure in columns packed with wide-pore core-shell particles

To determine the efficiency that can be obtained in a packed-bed liquid-chromatography column for a particular analyte, a correct determination of the molecular and effective diffusion coefficients (Dm and Deff) of the analyte is required. The latter is usually obtained via peak parking experiments wherein the flow is stopped. As a result, the column pressure rapidly dissipates and the measurement is essentially conducted at ambient pressure. This is problematic for analytes whose retention depends on pressure, such as proteins and potentially other large (dipolar) molecules. In that case, a conventional peak parking experiment is expected to lead to large errors in Deff. To obtain a better estimate ofDeff, the present study reports on the use of a set-up enabling peak parking measurements under pressurized conditions. This approach allowed us to report, for the first time, Deff for proteins at elevated pressure under retained conditions. First, Deff was determined at a (average) pressure of about 105 bar for a set of proteins with varying size, namely: bradykinin, insulin, lysozyme, β-lactoglobulin, and carbonic anhydrase in a column packed with 400 Å core-shell particles. The obtained data were then compared to those of several small analytes: acetophenone, propiophenone, benzophenone, valerophenone, and hexanophenone. A clear trend between Deff and analyte size was observed. The set-up was then used to determine Deff of bradykinin and lysozyme at variable (average) pressures ranging from 28 bar to 430 bar. These experiments showed a decrease in intra-particle and surface diffusion with pressure, which was larger for lysozyme than bradykinin. The data show that pressurized peak parking experiments are vital to correctly determine Deff when the analyte retention varies significantly with pressure.

A Semi-Analytical Model of Contaminant Transport in Barrier Systems with Arbitrary Numbers of Layers

In regions with sanitary landfills, unsuitable liner designs can result in significant soil and groundwater contamination, leading to substantial environmental remediation costs. Addressing this challenge, we propose a semi-analytical model for solute transport that uses the advection–dispersion–reaction equation in a multi-layered liner system. A distinctive feature of our model is its ability to account for infiltration velocity, arbitrary numbers of layers, thin layers such as geomembranes, and mass flow. We validated our model against existing published models and applied it to a case study of a real sanitary landfill in the capital of Brazil. Through parametric analyses, we simulated contaminant transport across various layers, including the geomembrane (GM), geosynthetic clay liner (GCL), soil liner (SL), and compacted clay liner (CCL). The analyses showed the importance of choosing the most appropriate construction system based on the location and availability of materials. Considering toluene contamination, a GM molecular diffusion coefficient (DGM) greater than 10−13 m2 s−1 exhibited similar efficiency when compared with CCL (60 cm thick). In addition, the results showed that the liner system may have the same efficiency in changing SL (60 cm thick) for a GCL (1 cm thick).

Effect of Food Viscosity on Drug Dissolution.

The purpose of the present study was to investigate the effect of food viscosity on the dissolution rate of a drug. There are two types of viscosity, macroviscosity and microviscosity. Macroviscosity affects the diffusion layer thickness, whereas microviscosity affects the molecular diffusion coefficient. The mass transfer coefficient (kc) in the intrinsic dissolution rate (IDR) depends on the viscosity (η) as kc ∝ ηa (a is an exponent on η). In theory, for rotating flow over a disk, if a thickener increases only macroviscosity, a = -1/6, and if it increases both macroviscosity and microviscosity equally, a = -7/6. Benzocaine was used as a model drug. Hydroxypropyl cellulose (HPC) and methylcellulose (MC) were employed as control thickeners that increase only macroviscosity. Sucrose was employed as a control thickener for both macroviscosity and microviscosity. The FDA breakfast homogenate (BFH) was diluted with distilled water or 1mM HCl with/without pepsin digestion. The IDR value was measured by the paddle-over-disk method. The η value of 30% BFH distilled water was 209mPa∙s, about 300 times higher than distilled water. It was further increased by HCl (430mPa∙s), and reduced by pepsin digestion (35mPa∙s). The kc value was little affected by BFH (a = 0.00 to -0.09), slightly less than those in HPC (a = -0.19) and MC (a = -0.21). Sucrose decreased the kc value more significantly (a = -0.70). The IDR and kc values of benzocaine were little affected by BFH, suggesting that BFH increased only macroviscosity.

Artificial neural networks in predicting of the gas molecular diffusion coefficient

The diffusion coefficient is one of the most important parameters for designing two-phase operations between liquid and gas phases in refineries and petrochemical industries, as well as for the gas injection process in oil fields to enhance oil production. Accurate knowledge of this parameter is essential for the prediction of the dissolution rate of the gas phase into the liquid phase. Ideally, this parameter should be obtained experimentally. Given that setting up laboratory equipment and conducting experiments can be costly and time-consuming, mathematical modeling is used as an alternative. In some cases, this data is not either available or reliable, which poses a challenge for designs. Hence, empirically derived correlations are used to predict molecular diffusion coefficients. However, the success of empirical models depends mainly on the range of data at which they were originally developed. Empirical models are not comprehensive for applying to the other data. Recent studies demonstrated that the alternative approach to modeling complex processes and identifying the effective parameters is the artificial neural network (ANN), a suitable prediction method. This study presents a new model developed to predict the molecular diffusion coefficient of methane in crude oil. The model is developed using 172 data points collected from recent literature. Out of the total laboratory data, 90% (155 data points) were used for training the desired neural network, while 10% (17 data points) were reserved for testing and evaluating the performance of the network. The multi-layer perceptron (MLP) neural network architecture with back-propagation (BP) training algorithm was used successfully for the prediction of diffusion coefficients of methane in crude oil. The developed model is compared with the empirical data, which shows the developed model predicts the methane molecular diffusion coefficient in crude oil with an average absolute error of 4.18%.

Operando characterisation of the products of Fischer-Tropsch synthesis in a fixed-bed reactor studied by magnetic resonance

Operando measurement of catalyst performance presents many difficulties as it is necessary to obtain measurements at reaction temperature and pressure and also at relevant length scales of multiple pellets to replicate the pellet-scale mass transport. Non-invasive measurement under such conditions is challenging. In this study we have developed an NMR/MRI compatible reactor that is of industrially-relevant scale and can operate at typical conditions for Fischer-Tropsch synthesis (FTS). The pilot-scale fixed-bed reactor (20 mm i.d.) used for FTS is operated at 220 °C and 37 bar and is packed with 1 wt % Ru/TiO2 catalyst pellets. Multiple magnetic resonance techniques have been developed and applied to achieve quantitative characterisation of product species including hydrocarbons, water, oxygenates and branched alkanes in pores. In addition to spatially-resolved measurements of molecular diffusion coefficients of the product species from which the carbon chain length of the saturated hydrocarbons can be determined, preliminary estimates of the relative amount of oxygenate and water species and branched saturated hydrocarbons present within the pore space of the catalyst are also determined using non spatially-resolved two-dimensional 1H T1-chemical shift and two-dimensional 1H double quantum filtered correlated spectroscopy (DQF-COSY), respectively. The concentrations of water and oxygenates detected inside the pores of catalyst pellets decrease when the feed H2/CO ratio decreases. The amount and extent of branching of saturated hydrocarbon species is observed to be higher than for the effluent wax product, most likely due to the effect of mass transfer limitation within the reactor. This work demonstrates that a toolbox of operando magnetic resonance techniques is available to characterise different product species of FTS from within catalyst pellets. The information provided by these techniques can give insight into how both catalyst and reactor can be optimised.

Molecular simulation and wetting study on the mechanism and capability of hydrophilic surfactants used as spray dust suppressants for dust reduction in coal mines

Coal dust prevention and control has always been a practical problem that needs to be solved urgently in coal mines. Based on spray technology, it has a good application prospect to achieve effective deposition of coal dust by adding surfactants. In this work, the wetting mechanism of three anionic surfactants at the water coal interface was found out from the molecular micro level and macro level through wetting angle test, sedimentation experiment, interfacial tension experiment and molecular dynamics simulation analysis. The results show that the electrostatic potential extremes of sodium sec alkyl sulfonate, sodium fatty acid methyl ester sulfonate and sodium a-alkenylsulfonate are 0.2399 a. u., 0.2430 a. u. And 0.2387 a. u. Respectively, which are greater than the electrostatic potential extremes of water 0.09157 a. u. It can be judged that the head groups of the three surfactants can produce hydrophilicity. The radial distribution function between the S atom and the O atom in the water in the hydrophilic group of the three surfactants has the same overall change trend, forming an obvious first peak and a weak second peak, with molecular diffusion coefficients of 4.633, 11.10, and 14.13 Å2/ps, respectively. The smaller diffusion coefficients correlated with stronger adsorption, which was consistent with contact angle measurements and a relative concentration analysis. The research results can provide reference for efficient evaluation of the wettability of surfactants.

Field-of-view optimized and constrained undistorted single-shot study of intravoxel incoherent motion and diffusion-weighted imaging of the uterus during the menstrual cycle: a prospective study.

This study aimed to compare the variability of the uterus during the menses phase (MP), follicular phase (FP), and luteal phase (LP) of the menstrual cycle using intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI). This prospective study was conducted at the Guangdong Provincial Hospital of Traditional Chinese Medicine between January 2022 and January 2023. Women of childbearing age (18-45 years) with appropriate progesterone levels were included in this study. Conventional magnetic resonance imaging and IVIM-DWI scans were performed during the MP, FP, and LP. The differences in IVIM-DWI-derived parameters between these phases were then compared, and the overlap was quantitatively described. The apparent diffusion coefficient (ADC) and pure molecular diffusion coefficient (D) values from the endometrium, uterine junctional zone (UJZ), and myometrium indicated statistical differences between the MP and FP and the MP and LP (ADC: endometrium, both P < 0.001; UJZ, P = 0.008 and P < 0.001, respectively; myometrium, P = 0.033 and P = 0.006, respectively; D: endometrium, both P < 0.001; UJZ, P = 0.008 and P = 0.006, respectively; myometrium, P = 0.041 and P = 0.045, respectively). The perfusion-related diffusion coefficient (D*) values from the myometrium indicated statistical differences between the FP and MP and the FP and LP (D*: myometrium, P = 0.049 and P = 0.009, respectively). The overlapping endometrium ratios between the MP and FP or LP were lower than 50% in the ADC and D values (ADC: overlapping of MP and FP: 33.33%, overlapping of MP and LP: 23.33%; D: overlapping of MP and FP: 40.00%, overlapping of MP and LP: 43.33%). The ADC and IVIM-derived parameters indicated differences in the uterus in diverse phases of the menstrual cycle, especially in the endometrium in relation to ADC and D values.

Does Bi-Exponential Fitting Perform Better than Mono-Exponential Fitting in IVIM-DWI? An Assessment of Renal Pathological Injury of IgA Nephropathy.

Chronic kidney disease has become one of the world's major public health problems, immunoglobulin A (IgA) nephropathy is a common pathological type of CKD. Delaying the progression of IgA nephropathy has currently become the main clinical treatment strategy, precise evaluation of renal pathological injury during follow-up of patients with IgA nephropathy is important. Therefore, it is imperative to develop an accurate and non-invasive imaging technique for effective follow-up of renal pathological injury in patients with IgA nephropathy. To investigate the clinical value of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in assessing renal pathological injury in patients with immunoglobulin A (IgA) nephropathy compared with a mono-exponential model. Altogether, 80 patients with IgA nephropathy were divided into the mild (41 cases) andmoderate-severe (m-s) renal injury groups (39 cases) according to pathology scores, and 20 healthy volunteers were recruited as controls. All participants underwent IVIM-DWI of the kidneys, and renal parenchymal apparent diffusion coefficient (ADC), pure molecular diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) values were measured. One-way analysis of variance, receiver operating characteristic (ROC) curve analysis, and Pearson correlation analysis were performed for all the DWI-derived parameters. The DWI-derived parameters of the m-s renal injury group were significantly lower than those of the mild renal injury and control groups (P < 0.01). The ROC analysis revealed that f had the largest area under the ROC curve for differentiation between the m-s and mild renal injury groups and between the m-s renal injury and control groups. The f had the largest correlation coefficient with renal pathology scores (r=-0.81), followed by the D* (-0.69), ADC (-0.54), and D values (-0.53), respectively (all P<0.01). IVIM-DWI demonstrated better diagnostic performance than the mono-exponential model in assessing renal pathological injury in patients with IgA nephropathy.

Novel high-precision wax molecular diffusion coefficient correlation based on the diffusion laboratory apparatus coupled with differential scanning calorimeter

Wax molecular diffusion coefficient is a crucial factor determining the wax deposition rate of waxy crude oil, but the calculation accuracy of the traditional Hayduk-Minhas and Wilke-Chang relations is unclear. The Couette wax deposition experiments of Changqing crude oil under different operating conditions (oil temperature, wall temperature, rotation speed and deposition duration) were carry out and find the traditional Hayduk-Minhas relationship will underestimate the wax molecular diffusion coefficient. To increase the calculation accuracy of wax molecular diffusion coefficient, a newly-developed diffusion laboratory apparatus coupled with the Differential Scanning Calorimeter (DSC) were utilized to evaluate the diffusion coefficient of C16, C18, C20, C22, C24 in n-alkane solutions at different temperatures (10, 15, 20, 25, 30,35, and 40 °C). Based on the experimental results, a novel high-precision correlation was put forward and the calculated results are in good agreement with the experimental results, the average relative error is within 3.0 %. The applied solvent of the n-alkane solutions is mineral oil and it has a complex composition. Therefore, the developed correlation can be used to evaluate the wax molecular diffusion coefficient in the real crude oil. The application of the new relationship will lead to more accurate wax deposition calculations.

Analysis of the Distribution and Influencing Factors of Diffusion Coefficient Model Parameters Based on Molecular Dynamics Simulations.

The establishment of mathematical models to predict the diffusion coefficients of gas and liquid systems have important theoretical significance and practical value. In this work, based on the previously proposed diffusion coefficient model DLV, the distribution and influencing factors of the model parameters characteristic length (L) and diffusion velocity (V) were further investigated using molecular dynamics simulations. The statistical analysis of L and V for 10 gas systems and 10 liquid systems was presented in the paper. New distribution functions were established to describe the probability distributions of molecular motion L and V. The mean values of the correlation coefficients were 0.98 and 0.99, respectively. Meanwhile, the effects of molecular molar mass and system temperature on the molecular diffusion coefficients were discussed. The results show that the effect of molecular molar mass on the diffusion coefficient mainly affects the molecular motion L, and the effect of system temperature on the diffusion coefficient mainly affects V. For the gas system, the average relative deviation of DLV and DMSD is 10.73% and that of DLV and experimental value is 12.63%; for the solution system, the average relative deviation of DLV and DMSD is 12.93% and that of DLV and experimental value is 18.86%, which indicates the accuracy of the new model results. The new model reveals the potential mechanism of molecular motion and provides a theoretical basis for further study of the diffusion process.

Using Ultrahigh b -Value Diffusion-Weighted Imaging to Noninvasively Assess Renal Fibrosis in a Rabbit Model of Renal Artery Stenosis.

This study aimed to investigate the feasibility of diffusion-weighted imaging with ultrahigh b values ( ub DWI) for the evaluation of renal fibrosis (RF) induced by renal artery stenosis (RAS) in a rabbit model. Thirty-two rabbits underwent left RAS operation, whereas 8 rabbits received sham surgery. All rabbits underwent ub DWI ( b = 0-4500 s/mm 2 ). The standard apparent diffusion coefficient (ADC st ), molecular diffusion coefficient ( D ), perfusion fraction ( f ), perfusion-related diffusion coefficient ( D *) and ultrahigh apparent diffusion coefficient (ADC uh ) were longitudinally assessed before operation and at weeks 2, 4, and 6 after operation. The degree of interstitial fibrosis and the expression of aquaporin (AQP) 1 and AQP2 were determined through pathological examination. In the stenotic kidney, the ADC st , D , f , and ADC uh values of the renal parenchyma significantly decreased compared with those at baseline (all P < 0.05), whereas the D * values significantly increased after RAS induction ( P < 0.05). The ADC st , D , D *, and f were weakly to moderately correlated with interstitial fibrosis as well as with the expression of AQP1 and AQP2. Furthermore, the ADC uh negatively correlated with interstitial fibrosis ( ρ = -0.782, P < 0.001) and positively correlated with AQP1 and AQP2 expression ( ρ = 0.794, P < 0.001, and ρ = 0.789, P < 0.001, respectively). Diffusion-weighted imaging with ultrahigh b values shows the potential for noninvasive assessment of the progression of RF in rabbits with unilateral RAS. The ADC uh derived from ub DWI could reflect the expression of AQPs in RF.

Intravoxel incoherent motion predicts positive surgical margins and Gleason score upgrading after radical prostatectomy for prostate cancer.

Whether Intravoxel incoherent motion (IVIM) can be used as a predictive tool of positive surgical margins (PSMs) and Gleason score (GS) upgrading in prostate cancer (PCa) patients after radical prostatectomy (RP) still remains unclear. The aim of this study is to explore the ability of IVIM and clinical characteristics to predict PSMs and GS upgrading. A total of 106 PCa patients after RP who underwent pelvic mpMRI (multiparametric Magnetic Resonance Imaging) between January 2016 and December 2021 and met the requirements were retrospectively included in our study. IVIM parameters were obtained using GE Functool post-processing software. Logistic regression models were fitted to confirm the predictive risk factor of PSMs and GS upgrading. The area under the curve and fourfold contingency table were used to evaluate the diagnostic efficacy of IVIM and clinical parameters. Multivariate logistic regression analyses revealed that percent of positive cores, apparent diffusion coefficient and molecular diffusion coefficient (D) were independent predictors of PSMs (Odds Ratio (OR) were 6.07, 3.62 and 3.16, respectively), Biopsy GS and pseudodiffusion coefficient (D*) were independent predictors of GS upgrading (OR were 0.563 and 7.15, respectively). The fourfold contingency table suggested that combined diagnosis increased the ability of predicting PSMs but had no advantage in predicting GS upgrading except the sensitivity from 57.14 to 91.43%. IVIM showed good performance in predicting PSMs and GS upgrading. Combining IVIM and clinical factors enhanced the performance of predicting PSMs, which may contribute to clinical diagnosis and treatment.

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.

Effect of High-Temperature Paraffin Impregnation on the Properties of the Amorphous Cellulose Region Based on Molecular Dynamics Simulation

A paraffin–cellulose composite model was created using Materials Studio software, establishing a cellulose chain with a polymerization degree of 20 and paraffin molecules. A theoretical foundation for the research of wood heat treatment was established by explaining the changes in macroscopic qualities, such as mechanical properties, water absorption, etc., from a microscopic point of view. The model tended to a stable state with lower energy through geometric optimization and kinetic relaxation. The dynamics simulation was run based on this condition at a total of five different temperatures: 100 °C, 150 °C, 170 °C, 190 °C, and 210 °C. The energy balance, paraffin molecular diffusion coefficients, cell parameters and densities, hydrogen bonding numbers and mechanical parameters of the paraffin–cellulose composite model were analyzed. The results demonstrated that the paraffin diffusion range increased with temperature, and the paraffin diffusion coefficient was greatest at 210 °C, which also resulted in the maximum cell volume, the lowest density, and the lowest water absorption at this temperature. On the other hand, the paraffin–cellulose hybrid model had the most hydrogen bonds and the most stable system at 100 °C. The mechanical properties of the amorphous cellulose region of wood are influenced by temperature. According to the calculation of Lamé constants, with the system’s temperature rise, Young’s modulus (E) and shear modulus (G) were maximum at 100 °C, indicating the wood’s optimal toughness and plasticity. Poisson’s ratio and K/G values were largest at 210 °C, indicating the optimal toughness and plasticity of wood. The thermal modification of wood under different conditions can not only retain its natural advantages, but also improve its own performance, expand the application range of wood, and increase the utilization rate of wood. Therefore, the appropriate temperature and other conditions can be selected according to the actual needs of the wood heat treatment, which has significant practical significance for the study of wood heat treatment.