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In this paper, the self-diffusion coefficients (SDC) of CH4/CO2/H2O in coal molecules under different ensemble conditions and the effects of temperature and pressure are calculated by grand canonical Monte Carlo and molecular dynamics (MD) methods. Results indicated that the self-diffusion coefficients of CH4 and CO2 gradually increase with the increasing temperature under the NPT ensemble. The SDC of H2O increases undulatory and it is higher than that of CH4 and CO2 at each temperature, where the diffusion activation energy followed the order of \begin{document}$E({{\mathrm{H}}_2{\mathrm{O}}})

Neutron spectroscopy uniquely and non‐destructively accesses diffusive dynamics in soft and biological matter, including for instance proteins in hydrated powders or in solution, and more generally dynamic properties of condensed matter on the molecular level. Given the limited neutron flux resulting in long counting times, it is important to optimize data acquisition for the specific question, in particular for time‐resolved (kinetic) studies. The required acquisition time was recently significantly reduced by measurements of discrete energy transfers rather than quasi‐continuous neutron scattering spectra on neutron backscattering spectrometers. Besides this reduction in acquisition times, smaller amounts of samples can be measured with better statistics, and most importantly, kinetically changing samples, such as aggregating or crystallizing samples, can be followed. However, given the small number of discrete energy transfers probed in this mode, established analysis frameworks for full spectra can break down. Presented here are new approaches to analyze measurements of diffusive dynamics recorded within fixed windows in energy transfer, and these are compared with the analysis of full spectra. The new approaches are tested by both modeled scattering functions and a comparative analysis of fixed energy window data and full spectra on well understood reference samples. This new approach can be employed successfully for kinetic studies of the dynamics focusing on the short‐time apparent center‐of‐mass diffusion. [ABSTRACT FROM AUTHOR]

The activation parameters for various iron structures were calculated by the analytical method based on the paired four-parameter Mie–Lennard-Jones interatomic interaction potential. Within the framework of a single method, all the activation processes parameters were calculated: Gibbs energy, enthalpy, entropy and volume for both the process of electroneutral vacancy formation and for the process of atom self-diffusion. The isobaric temperature dependences of the indicated activation parameters for BCC and FCC iron structures from T = 10 to 1810 K along two isobars: P = 0 and 10 GPa were calculated. It is shown that at the α–γ transition temperature (1184 K), the activation parameters decrease during the isobaric transition from the BCC to the FCC structure. At the γ–δ transition temperature (1667 K), the activation parameters increase during the transition from the FCC to the BCC structure. With increasing pressure, the jumps magnitude for the Gibbs energy and the enthalpy of the activation process increases, and for the entropy and volume of the activation process decreases. It is shown that, at low temperatures, due to quantum regularities, activation parameters strongly depend on temperature, and the entropy of activation processes in this region is negative. In the high temperature region, a good agreement has been obtained with the experimental estimates of activation parameters for different iron structures known from the literature. [ABSTRACT FROM AUTHOR]

Featured Application: The materials studied may be used in the radioactive waste vitrification process. Additionally, the proposed simulation method may be useful in optimizing glass composition and predicting the glass elements migration. Among the many possible applications of iron phosphate glasses, one of them is that they are promising materials in waste vitrification, particularly for radioactive waste. In vitrified form, waste elements should be permanently immobilized in a glass network as they are susceptible to harsh environmental conditions. The self-diffusion of the vitrified material species may limit the potential usefulness of the glasses. This paper presents the possibility of using molecular dynamics simulations to study this process and the substitution of SrO into an iron phosphate glass network. It was evidenced that the self-diffusion mechanism differed significantly depending on whether the glass was in a solid or liquid state. The proposed method also offered a relatively easy prediction of glass characteristic temperatures, such as transformation and flow. We also observed, and here describe, an aggregation process of the glass elements that may drive their crystallization. The obtained results are discussed in light of the experimental and theoretical structural feature literature data. [ABSTRACT FROM AUTHOR]

This study aims to investigate a diffusive predator–prey system incorporating additional food for predators, prey refuge, fear effect, and its carry-over effects. For the temporal model, the well-posedness and persistence of the system have been discussed. We investigated the existence and the stability behavior of the various equilibria. Furthermore, we explored the bifurcations of codimension-1 including transcritical, saddle-node, and Hopf, concerning the crucial parameters. The system also presents codimension-2 bifurcations such as Bogdanov–Takens and cusp bifurcation along with the global homoclinic bifurcation. We observed the bubbling phenomena, which illustrate the fluctuations in the amplitudes of the periodic oscillations. For the spatiotemporal system, we established the non-negativity and boundedness of the solutions. We derived the conditions for the diffusion-driven instabilities in a confined region with Neumann boundary conditions. Extensive numerical simulations have been conducted to depict the various stationary patterns in Turing space. It is observed that incorporating cross-diffusion divides the bi-parametric plane into various sub-regions and dynamic patterns are analyzed in these different regions. The intricate spatiotemporal dynamics exhibited by prey–predator interactions are crucial for unraveling the intricacies within ecological systems. [ABSTRACT FROM AUTHOR]

In this work, a two-dimensional Coupled Map Lattice (CML) method is applied to a continuous Reaction–Diffusion (RD) SIRS epidemic model. The model involves a complex, nonlinear incidence rate and the spatially heterogeneous self- and cross-diffusion coefficients. The CML method applied here results in a space–time discrete counterpart of the model. The basic reproduction number is derived, and the local stability of the fixed points of the discrete model is established. The two typical bifurcations of codimension 1, such as the flip and the Neimark–Sacker (NS) bifurcations, are investigated by utilizing the center manifold theory and the normal form theorem. Furthermore, the codimension-2 fold–flip bifurcation about the endemic fixed point is discussed in detail. Turing instability criterion of the cross-diffusion epidemic model is established by utilizing the CML method under periodic boundary conditions. Finally, the numerical simulations clarify both the effectiveness of all theoretical findings and the effects of time step size and cross-diffusion on the spatiotemporal patterns. The main contribution of this work is the discovery of some interesting Turing and non-Turing patterns which may be induced by flip–Turing instability, NS–Turing instability or fold–flip–Turing instability. Concretely speaking, spiral patterns are observed near the flip bifurcation threshold value and ultimately evolve into an irregular defect pattern. Stripe pattern, labyrinth pattern and circular pattern are observed near the NS bifurcation threshold value. The disorderly interwoven ribbon pattern, mosaic pattern and some irregular oscillatory patterns are observed near the fold–flip bifurcation point. Our results greatly help in predicting the long-term behavior of the space–time discrete SIRS epidemic model under study. [ABSTRACT FROM AUTHOR]

The secondary consequences of predator species on prey species have substantial implications for population dynamics. A deeper comprehension of the dynamics between prey and predator can be achieved through the examination of indirect consequences. This work examines the dynamic behavior of a modified Holling-Tanner model. The interactions between the species are characterized by a functional response of the Beddington–DeAngelis type. Factors such as prey refuge, fear factor, disturbance intensity, and cross diffusion have been taken into account. The boundedness, feasibility of equilibrium points, their stability and restrictions for Hopf bifurcation of non-spatial model system are derived. The study explores the combined effects of prey refuge presence and fear factors on population dynamics. Furthermore, the investigation focuses on the stability of spatial self-diffusion and cross-diffusion model systems, as well as the specific conditions that lead to Turing instability. Ultimately, it has been shown that in the context of self-diffusion, a moderate level of fear promotes the survival of prey, whereas an excessive level of dread hinders the survival of prey. Concurrently, the mean density of prey exhibited a gradual decline as the refuge parameters increased. The spatial patterns of the population have also been investigated. As the mutual interference between prey populations intensifies, the spatial distribution of the prey population transitions from a clustered pattern to a combination of striped and clustered patterns, ultimately settling into a striped pattern. With the gradual growth of the half saturation constant, the prey population reached a state of uniform distribution. In the scenario of cross diffusion, when the prey is heavily impacted by the pursuit of predators, the fear effect, when appropriately used, did not have a significant impact on the survival of the prey. This work adds to the existing body of knowledge by revealing novel insights into the influence of indirect factors on the behavior of predator and prey populations.

Nuclear magnetic resonance (NMR) is an established method to determine self‐diffusion coefficients in liquids with high precision. The development of benchtop NMR spectrometers makes the method accessible to a wider community. In most cases, 1H NMR spectroscopy is used to determine self‐diffusion coefficients due to its high sensitivity. However, especially when using benchtop NMR spectrometers for the investigation of complex mixtures, the signals in 1H NMR spectra can overlap, hindering the precise determination of self‐diffusion coefficients. In 13C NMR spectroscopy, the signals of different compounds are generally well resolved. However, the sensitivity of 13C NMR is significantly lower than that of 1H NMR spectroscopy leading to very long measurement times, which makes diffusion coefficient measurements based on 13C NMR practically infeasible with benchtop NMR spectrometers. To circumvent this problem, we have combined two known pulse sequences, one for polarization transfer from 1H to the 13C nuclei (PENDANT) and one for the measurement of diffusion coefficients (PFG). The new method (PENPFG) was used to measure the self‐diffusion coefficients of three pure solvents (acetonitrile, ethanol and 1‐propanol) as well as in all their binary mixtures and the ternary mixture at various compositions. For comparison, also measurements of the same systems were carried out with a standard PFG‐NMR routine on a high‐field NMR instrument. The results are in good agreement and show that PENPFG is a useful tool for the measurement of the absolute value of the self‐diffusion coefficients in complex liquid mixtures with benchtop NMR spectrometers. [ABSTRACT FROM AUTHOR]

Assessing the feasibility of porous formations for hydrogen geo-storage demands a comprehensive understanding of hydrogen (H 2) transport behavior in porous media at subsurface conditions. In this study, we employ molecular dynamics simulations to evaluate the effects of pressure (20–500 atm), pore size (2–20 nm), and surface composition on H 2 diffusion and interactions within organic and inorganic slit pores. Our analysis of H 2 density profiles and interaction energies reveals a distinct preference for H 2 molecules to adsorb more readily onto graphene surfaces than kaolinite surfaces. However, self-diffusion results demonstrate that H 2 molecules interact relatively weakly with both substrate types. Further insights are provided by velocity autocorrelation functions, emphasizing the occurrence of wall-mediated collisions as H 2 molecules diffuse along the pore surfaces, particularly within kaolinite. This highlights the significance of surface roughness in mitigating H 2 loss via diffusion in subsurface nanopores, given the small molecular size of H 2 and its limited interactions with both organic and inorganic materials. Furthermore, the results demonstrate that self-diffusion coefficients in both pore types increase with pore size and decrease with pressure. Notably, surface composition plays a critical role in low-pressure environments, with self-diffusion coefficients beginning to converge beyond a pressure of 100 atm. Self-diffusion coefficients also become less sensitive to slit aperture beyond a pressure of 50 atm. In high-pressure environments, hydrogen transport is governed by thermal collisions between gas molecules, leading to negligible property variations between pore types. These findings hold significance in the investigation of efficient H 2 storage within porous media and caprock formations. • H 2 molecules adsorb more readily onto graphene surfaces than kaolinite surfaces. • H 2 molecules interact relatively weakly with both graphene and kaolinite. • Surface roughness is a fundamental property governing potential H 2 loss. • H 2 self-diffusion generally increases with pore size and decreases with pressure. • Surface composition plays a critical role in H 2 transport at lower pressures. [ABSTRACT FROM AUTHOR]

Self-diffusion in a cyclohexane–methanol binary system was studied by the pulsed gradient spin-echo 1H NMR method at temperatures of 298 (in the region of limited miscibility) and 323 K (over entire composition of the mixed solvent). According to the data obtained, the concentration dependences of the self-diffusion coefficients of cyclohexane increase with methanol concentration. However, the concentration dependences of the self-diffusion coefficients of methanol have minima. At the same time, according to 1H NMR data, the chemical shift of OH protons in the methanol molecule decrease with increasing cyclohexane concentration and temperature, which indicates a decrease in the degree of methanol self-association in the system. The effect of molecular association on methanol self-diffusion in the binary system was evaluated using the Stokes–Einstein equation. The concentration dependences of the relative effective hydrodynamic radius of methanol were shown to have maxima. [ABSTRACT FROM AUTHOR]

Numerical simulation can provide detailed understanding of mass transport within complex structures. For this purpose, numerical tools are required that can resolve the complex morphology and consider the contribution of both convection and diffusion. Solving the Navier–Stokes equations alone, however, neglects self-diffusion. This influences the simulated displacement distribution of flow especially in porous media at low Péclet numbers (Pe < 16) and in near-wall regions where diffusion is the dominant mechanism. To address this problem, this study uses μCT-based computational fluid dynamics (CFD) simulations in OpenFOAM coupled with the random-walk particle tracking (PT) module disTrackFoam and cross-validated experimentally using pulsed-field gradient (PFG) nuclear magnetic resonance (NMR) measurements of gas flow within open-cell foams (OCFs). The results of the multi-scale simulations—with a resolution of 130–190 µm—and experimental PFG NMR data are compared in terms of diffusion propagators, which are microscopic displacement distributions of gas flows in OCFs during certain observation times. Four different flow rates with Péclet numbers in the range of 0.7–16 are studied in the laminar flow regime within 10 and 20 PPI OCFs, and axial dispersion coefficients were calculated. Cross-validation of PFG NMR measurements and CFD-PT simulations revealed a very good matching with integral differences below 0.04%, underpinning the capability of both complementary methods for multi-scale transport analysis. [ABSTRACT FROM AUTHOR]

This study investigated the effect of polyols erythritol, d-mannitol, and maltitol on the volatility of aroma compounds γ-butyrolactone, 3-methyl-1-butanol, and 2-phenylethanol in aqueous solution. Headspace solid-phase microextraction/gas chromatography and diffusion-ordered nuclear magnetic resonance techniques were used to obtain information on aroma–food matrix interaction. Results demonstrated that adding polyols at final low concentrations of 5% or 10% (w/w) to an aqueous solution of 2-phenylethanol reduced the release of vapor-phase aromas, except in the case of 3-methyl-1-butanol, which was not affected by the presence of polyols in the liquid matrix. Polyols also reduced the diffusion coefficients of all three aroma compounds, probably due to friction between the molecules. At low polyol concentrations, aroma compound volatility and diffusion coefficient values were altered compared to those of aromas released from pure water. This observation is related to the physicochemical properties of the aroma compounds. These insights may help guide the use of the combination of aroma compounds and polyols in the formulation of sugar-free and reduced-sugar beverages. Chemical compounds: γ-butyrolactone (PubChem CID: 7302), 3-methyl-1-butanol (PubChem CID: 31260), 2-phenylethanol (PubChem CID: 6054), erythritol (PubChem CID: 222285), d-mannitol (PubChem CID: 6251), maltitol (PubChem CID: 493591).

Abstract Background Characterizing cancer molecular subtypes is crucial for improving prognosis and individualized treatment. Integrative analysis of multi-omics data has become an important approach for disease subtyping, yielding better understanding of the complex biology. Current multi-omics integration tools and methods for cancer subtyping often suffer challenges of high computational efficiency as well as the problem of weight assignment on data types. Results Here, we present an efficient multi-omics integration via weighted affinity and self-diffusion (MOSD) to dissect cancer heterogeneity. MOSD first construct local scaling affinity on each data type and then integrate all affinities by weighted linear combination, followed by the self-diffusion to further improve the patients’ similarities for the downstream clustering analysis. To demonstrate the effectiveness and usefulness for cancer subtyping, we apply MOSD across ten cancer types with three measurements (Gene expression, DNA methylation, miRNA). Conclusions Our approach exhibits more significant differences in patient survival and computationally efficient benchmarking against several state-of-art integration methods and the identified molecular subtypes reveal strongly biological interpretability. The code as well as its implementation are available in GitHub: https://github.com/DXCODEE/MOSD .

A chemically homogeneous structure models were established for the multi-principal alloy CoCrFeMnNi and the quaternary CrFeMnNi, CoFeMnNi, CoCrMnNi, CoCrFeNi, and CoCrFeMn alloys, and calculations were performed based on vacancy diffusion mechanism using lattice dynamics and molecular dynamics methods for the self-diffusion of each component atom. By calculating four thermodynamic parameters, namely, vacancy formation energy, atomic migration energy, formation entropy, and effective frequency at the transition state, the self-diffusion properties of each component atom were obtained. The formation energy, migration energy, and formation entropy of each component in different alloys were relatively close. The Arrhenius form of diffusion for each component in the quinary alloy showed that the results modified by experimental values using molecular dynamics were close to the measured values within a given temperature range. Directly substituting the thermodynamic parameters yielded results with some deviation from the measured values, with Mn and Cr exhibiting greater deviations. By substituting experimental values for formation energies, the result for Mn was close to the measured value, while the deviation of Cr data was still relatively large. This might be due to the error in the potential describing the formation energy and effective frequency. Calculating the thermodynamic parameters for quaternary alloys allowed the diffusion Arrhenius form to be obtained. The diffusion coefficient of Mn was much higher than that of other elements, while that of Cr was at a lower level, and the diffusion coefficients of Fe, Co, and Ni were close. In multi-principal alloy systems, there are interactions between the components that affect diffusion behavior, and the degree of influence varies depending on the component type. It seems that Co, Cr, and Mn tend to promote self-diffusion, while Fe and Ni tend to hinder diffusion in these alloys. [ABSTRACT FROM AUTHOR]

A vibrational model of transport properties of dense fluids assumes that solid-like oscillations of atoms around their temporary equilibrium positions dominate the dynamical picture. The temporary equilibrium positions of atoms do not form any regular structure and are not fixed, unlike in solids. Instead, they are allowed to diffuse and this is why liquids can flow. However, this diffusive motion is characterized by much longer time scales compared to those of solid-like oscillations. Although this general picture is not particularly new, only in a recent series of works it has been possible to construct a coherent and internally consistent quantitative description of transport properties such as self-diffusion, shear viscosity, and thermal conductivity. Moreover, the magnitudes of these transport coefficients have been related to the properties of collective excitations in dense fluids. Importantly, the model is simple and no free parameters are involved. Recent achievements are summarized in this overview. Application of the vibrational model to various single-component model systems such as plasma-related Coulomb and screened Coulomb (Yukawa) fluids, the Lennard-Jones fluid, and the hard-sphere fluid is considered in detail. Applications to real liquids are also briefly discussed. Overall, good to excellent agreement with available numerical and experimental data is demonstrated. Conditions of applicability of the vibrational model and a related question concerning the location of the gas–liquid dynamical crossover are discussed. [ABSTRACT FROM AUTHOR]

Background: Characterizing cancer molecular subtypes is crucial for improving prognosis and individualized treatment. Integrative analysis of multi-omics data has become an important approach for disease subtyping, yielding better understanding of the complex biology. Current multi-omics integration tools and methods for cancer subtyping often suffer challenges of high computational efficiency as well as the problem of weight assignment on data types. Results: Here, we present an efficient multi-omics integration via weighted affinity and self-diffusion (MOSD) to dissect cancer heterogeneity. MOSD first construct local scaling affinity on each data type and then integrate all affinities by weighted linear combination, followed by the self-diffusion to further improve the patients' similarities for the downstream clustering analysis. To demonstrate the effectiveness and usefulness for cancer subtyping, we apply MOSD across ten cancer types with three measurements (Gene expression, DNA methylation, miRNA). Conclusions: Our approach exhibits more significant differences in patient survival and computationally efficient benchmarking against several state-of-art integration methods and the identified molecular subtypes reveal strongly biological interpretability. The code as well as its implementation are available in GitHub: https://github.com/DXCODEE/MOSD. [ABSTRACT FROM AUTHOR]

Methods for modifying surface and near-surface layers of materials and coatings by ion beams have prospects for application in many fields of science and technology. The method of high-intensity implantation by high-power density ion beams with submillisecond duration involves significant pulsed heating of the near-surface layer of irradiated target, followed by its rapid cooling. This occurs due to heat removal into the material due to thermal conductivity and repetitively pulsed radiation-enhanced diffusion of atoms to depths that are much greater than the projective ion range. The paper considers the features of thermal processes and the effect of pulsed heating of near-surface titanium layers on diffusion transfer under conditions of synergy of high-intensity implantation of titanium ions and the energy impact of a repetitively-pulsed beam of high-power density on the surface in order to increase the depth of ion doping due to radiation-enhanced diffusion under conditions limited heating of the entire sample. The data of numerical simulation of dynamic changes in temperature fields in titanium and titanium self-diffusion under the action of ion beams with a submillisecond duration and a pulse power of tens of kW/cm2 and fluence of ions in a pulse 1.25 × 1015 ion/cm2 are presented. [ABSTRACT FROM AUTHOR]

Understanding the regulating mechanism of diffusive properties of ionic liquids (ILs) is vital for their practical chemical engineering applications. Herein, we investigate the regulating mechanism of three properties, the structural, thermodynamical, and diffusive properties, of imidazole ILs with 18 kinds of anion via molecular dynamics simulations combined with theoretical analysis. It shows that the radial distribution function and coordinate number for these 18 ILs are similar to each other. However, the vibrational spectrum and diffusive property change greatly with the anion structure, in which the self‐diffusive coefficient (SDC) even changes by an order of magnitude. Furthermore, free energy and entropy have an exponential relationship with SDC, while other structural properties or cation–anion correlations cannot be directly related to SDC. These quantitative relationships suggest that entropy or free energy can serve as the key indicators in designing functional ILs for high‐performance applications in the chemical engineering field. [ABSTRACT FROM AUTHOR]

Among the many possible applications of iron phosphate glasses, one of them is that they are promising materials in waste vitrification, particularly for radioactive waste. In vitrified form, waste elements should be permanently immobilized in a glass network as they are susceptible to harsh environmental conditions. The self-diffusion of the vitrified material species may limit the potential usefulness of the glasses. This paper presents the possibility of using molecular dynamics simulations to study this process and the substitution of SrO into an iron phosphate glass network. It was evidenced that the self-diffusion mechanism differed significantly depending on whether the glass was in a solid or liquid state. The proposed method also offered a relatively easy prediction of glass characteristic temperatures, such as transformation and flow. We also observed, and here describe, an aggregation process of the glass elements that may drive their crystallization. The obtained results are discussed in light of the experimental and theoretical structural feature literature data.

Self-diffusion of components of a binary chloroform – methanol system has been investigated by experimental (pulsed gradient spin-echo nuclear magnetic resonance (PGSE NMR)), molecular dynamics (MD) simulation and theoretical (athermal associated solution model) methods at 298 K. The concentration dependences of the effective hydrodynamic radii of the mixture components calculated on the basis of the Stokes-Einstein equation are shown to be extremal, which indicates molecular association in the system. The analysis of the radial distribution functions and the fraction of molecules of chloroform and methanol with i-hydrogen bonds obtained from MD simulations made it possible to determine the degree of self- and heteroassociation of the mixture components. The contributions of self-association and heteroassociation to the self-diffusion of the mixture components are estimated within the framework of the athermal associated solution model, taking into account the Stokes-Einstein equation.

One of the most relevant deterioration mechanisms of reinforced concrete (RC) structures is the corrosion of steel bars by chloride ions. The service life of structures could be extended by monitoring this process. The lack of correlation data between chloride ion diffusion and the electrical field has meant that alternative methods have been developed in this paper. One such method considers diffusivity and the electrical field as non-constant, although they are usually assumed constant, that is, without there being any variability of the involved factors. Therefore, a multi-factorial diffusivity that accounts for the material characteristics and environmental variations is adopted. In addition, an innovative stochastic approach to evaluate the variation of the electrical field while accounting for the non-linear voltage distortion, which considers a multispecies model, has been proposed. More complete 1D/2D electro-mechanical models that are solved by advanced numerical and analytical solutions for electro-mechanical diffusion have been developed. Results show that spatiotemporal numerical models estimate the chloride concentration well, estimating more reliable scenarios to provide information on the safety situation of the structure and make it more sustainable by employing successful preventive treatments. [ABSTRACT FROM AUTHOR]

The ab initio intermolecular pair potentials of F 2 dimer were calculated for five leading stable configurations, using the symmetry-adapted perturbation theory. We employ an improved Lennard–Jones potential to best fit the potential energy surface of each leading configuration. The molecular anisotropy is characterized through the expansion of the degrees of freedom of the analytical potential energy surface (PES) using the spherical harmonics. The resulting analytical PES is used to calculate the second virial coefficients and compared with the experimental values and other theoretical works to test the quality of the presented intermolecular potential. Finally, we performed the theoretical computation of viscosity and self-diffusion transport properties for the F 2 ⋯ F 2 system. [ABSTRACT FROM AUTHOR]

In the present work, we carried out a molecular dynamics study of the kinetic properties of the FLiNaK molten salt, as well as a detailed study of the structure of this salt melt. The high value of the self-diffusion coefficient of fluorine ions is due to the large number of Coulomb repulsions between the most numerous negative ions. The calculated values of shear viscosity are in good agreement with the experimental data, as well as with the reference data obtained on the basis of finding the most reliable data. The total and partial functions of the radial distribution are calculated. According to the statistical analysis, fluorine ions have the greatest numerical diversity in the environment of similar ions, and sodium ions with the lowest representation in FLiNaK, have the least such diversity. For the subsystem of fluorine ions, the rotational symmetry of the fifth order is the most pronounced. Some of the fluorine ions form linear chains consisting of three atoms, which are not formed for positive ions. The results of the work give an understanding of the behavior molten FLiNaK under operating conditions in a molten salt reactor and will find application in future studies of this molten salt.

Despite its merits of high specific capacity and intrinsic safety for aqueous zinc‐ion batteries (AZIBs), Zn metal as anode suffers from dendritic growth and severe corrosion during battery operation. Here, an electrolyte surfactant of succinimide (SI) that occupies the compact region of the electrical double layer (EDL) at the Zn/electrolyte interface, which protects the Zn surface from the parasitic corrosion in aqueous electrolytes is reported. More importantly, both theoretical calculation and electrochemical analysis demonstrate that the occupation of SI at the EDL can restrict the self‐diffusion of Zn adatoms and tune interfacial reaction kinetics during Zn deposition, thereby promoting small and dense nuclei rather than large Zn dendrites. Accordingly, SI surfactants enable a high Coulombic efficiency of 99.95% and a long cumulative plated capacity over 6800 mAh cm−2 at 20 mA cm−2 for 10 mAh cm−2. Moreover, the feasibility of SI is also demonstrated on a long‐term cycling stability in Zn‐VS2 batteries. [ABSTRACT FROM AUTHOR]

The dynamical properties of four protic ionic liquids, based on the ethyltriazolium ([C 2 HTr 124 ]) and the ethylimidazolium ([C 2 HIm]) cation, were investigated. The associated anions were the triflate ([TfO]) and the bistriflimide ([TFSI]). Ionic conductivity values and self-diffusion coefficients were measured and discussed, extending the discussion to the concept of fragility. Furthermore, in order to allow the measurement of the ionic conductivity of very small volumes (<0.5 mL) of ionic liquid under an inert and dry atmosphere, a new setup was developed. It was found that the cation nature strongly affected the transport properties, the [C 2 HTr 124 ] cation resulting in slower dynamics than the [C 2 HIm] one. This was concluded from both conductivity and diffusivity measurements while for both properties, the anion had a lesser effect. By fitting the conductivity data with the Vogel–Fulcher–Tammann (VFT) equation, we could also estimate the fragility of these ionic liquids, which all fell in the range of very fragile glass-forming materials. Finally, the slower dynamics observed in the triazolium-based ionic liquids can be rationalized by the stronger interactions that this cation establishes with both anions, as deduced from the frequency analysis of relevant Raman signatures and density functional theory (DFT) calculations. [ABSTRACT FROM AUTHOR]

Oxidative polymerization of plant oils and lipids is poorly understood yet widely encountered. Oils and fats are renewable resources providing biofuels and polymers. Oil oxidation is accelerated at high temperatures, typically above 110°C, where triacylglycerides are converted into toxic compounds and viscous deleterious polymers. Polymerization of mono‐unsaturated oil (210°C, 3 h, open to air) was investigated by comparing four similar sized molecules with different functional groups: oleic acid, methyl oleate, trans‐7‐tetradecene, and stearic acid. Non‐volatile products identified by NMR spectroscopy are minor ketones for saturated fatty acid (stearic acid), epoxides for acyl chains without acid groups (methyl oleate, tetradecane) and copious oligomerization, through ester cross‐links, for acyl chains with acid, and olefinic groups (oleic acid). Long range CH coupling clearly shows ester (not ether) cross‐links, contradicting long‐held beliefs. Chain fragmentation also occurs for heated oleic acid as revealed by formation of a species with a methylene group bonded to oxygen of an ester, CH2OC(O). Large size (slow diffusion) of the first oligomer (trimer) formed from oleic acid, used to represent hydrolyzed vegetable oil, was evidenced by DOSY (diffusion‐ordered spectroscopy). Combined NMR results show oligomers found in heated oleic acid are fatty acid estolides. Model oil reactions demonstrate why olefin and carboxylic acid groups are required for polymerization. [ABSTRACT FROM AUTHOR]

The equivalent characteristics of the materials' interfaces are known to impact the overall mechanical properties of ceramic–metal composites significantly. One technological method that has been suggested is raising the temperature of the liquid metal to improve the weak wettability of ceramic particles with liquid metals. Therefore, as the first step, it is necessary to produce the diffusion zone at the interface by heating the system and maintaining it at a preset temperature to develop the cohesive zone model of the interface using mode I and mode II fracture tests. This study uses the molecular dynamics method to study the interdiffusion at the interface of α-Al2O3/AlSi12. The hexagonal crystal structure of aluminum oxide with the Al- and O-terminated interfaces with AlSi12 are considered. A single diffusion couple is used for each system to determine the average main and cross ternary interdiffusion coefficients. In addition, the effect of temperature and the termination type on the interdiffusion coefficients is examined. The results demonstrate that the thickness of the interdiffusion zone is proportional to the annealing temperature and time, and Al- and O-terminated interfaces exhibit similar interdiffusion properties. [ABSTRACT FROM AUTHOR]

Structural and dynamical properties of nonlinear trigeminal tri-cationic imidazolium-based ionic liquids (TT-X3, X = Br¯, NO3¯, BF4¯) have been studied using molecular dynamics (MD) simulations. The liquid microstructures of TT-X3 ILs have been compared with mono- (M-X) and di-cationic (D-X2) ionic liquids (ILs).The developed OPLS force field with some corrections was utilized. Densities, heat of vaporization, mean square displacements, self-diffusion coefficients, molar electrical conductivities, and transference numbers have been calculated for all the ILs. The detailed microscopic structures have been discussed in terms of radial distribution functions (RDFs), combined radial-angular distribution functions (CDFs), and spatial distribution functions (SDFs). The results show that microscopic structure in TT-X3 ILs, similar to M-X and D-X2 ILs. As the number of imidazolium ring increases (from M-X to TT-X3 ILs), the probability of finding anions around cationic rings decreases. By comparing the heat of vaporization, for a special anion, it can be concluded that the heat of vaporization of tri-cationic ILs is more than that of mono- and di-cationic ILs. The dynamical properties show that, for di-cationic and tri-cationic ILs, the self-diffusion of the anions is more than the cations. By increasing the number of imidazolium rings, the self-diffusion of the anions and cations decreases. [ABSTRACT FROM AUTHOR]

This study is seeking a better understanding of polyethylene glycol (PEG) as a solvent to promote its use in chemical synthesis. The effect of adding two solutes of interest, 2,2,6,6-tetramethylpiperidinyloxyl (TEMPO) and 5-tert-butylisophthalic acid (5-TBIPA) to PEG200 (average molar weight of 200 g·mol−1) on the solution density, viscosity, and self-diffusion coefficients is monitored in a temperature range of 298.15–358.15 K to deduce how these solutes interact with the PEG200 solvent. The effect of water, the most common impurity in PEGs, is also monitored and found to be nearly negligibly small. Addition of (5-TBIPA) increases solution density and viscosity. Combined with the observation that 5-TBIPA consistently self-diffuses at about half the rate as PEG200 at all investigated experimental conditions, this suggests strong attractive solute–solvent interactions likely through hydrogen bonding interactions. In contrast, addition of TEMPO causes lower solution densities and viscosities suggesting that the solute–solvent interactions of TEMPO lead to an overall weakening of the intermolecular interactions present compared to neat PEG200. Inspection of the viscosity and self-diffusion temperature dependence reveals slight deviations from the Arrhenius equation. Interestingly, the activation energies obtained from the viscosity and the self-diffusion data are essentially identical in values suggesting that the same dynamic processes and thus the same activation barriers govern translational motion and momentum transfer in these PEG200 solutions. [ABSTRACT FROM AUTHOR]

The review considers a number of typical mechanisms of degradation of thermoelectric materials in the process of their functioning as a part of thermoelectric generator modules. Among them are diffusion and self-diffusion in thermoelectric materials and contact structures, loss of dopants by thermoelectric materials due to sublimation, formation of intermetallic compounds in contact structures, accumulation of structural defects under the influence of thermal and mechanical loads, mechanical destruction of thermoelectric legs, contact structures and other structural members of modules, chemical interaction of thermoelectric materials with other structural members. The main design and technological ways and methods of reducing the negative impact of these mechanisms on the reliability of thermoelectric materials and modules are also considered.

In this study, the lattice fluid (LF) and Vrentas's self-diffusion (VSD) model were employed to predict the gas sorption, diffusion, and permeability through various rubbery polymeric membranes, like PDMS, PB, PE, and PIP as homopolymers and SBR (36 wt.%) and EVAc (54 wt.%) as copolymers. The LF model with use of variable characteristic parameters that were based on the temperature and pressure range of interest, enabled to predict convex behavior of pressure-induced sorption of PDMS and PB with an AARD < 3%. The Dullien method was also used to calculate the self-diffusion coefficient of pure components in the selected polymers. Extending VSD model led to reliable gas diffusion predictions with AARD < 10% for all systems. Furthermore, using concept of bulk modulus in combination with Tait equation, pressure functionality of diffusion factor was successfully corrected. The pressure and temperature dependency of the gas permeability through the selected homopolymers and copolymers were also investigated by the proposed model, and it was observed that the predicted permeability values were consistent with the experimental data. [ABSTRACT FROM AUTHOR]

We consider a two-species simple exclusion process on a periodic lattice. We use the method of matched asymptotics to derive evolution equations for the two population densities in the dilute regime, namely a cross-diffusion system of partial differential equations for the two species’ densities. First, our result captures non-trivial interaction terms neglected in the mean-field approach, including a non-diagonal mobility matrix with explicit density dependence. Second, it generalises the rigorous hydrodynamic limit of Quastel (Commun Pure Appl Math 45(6):623–679, 1992), valid for species with equal jump rates and given in terms of a non-explicit self-diffusion coefficient, to the case of unequal rates in the dilute regime. In the equal-rates case, by combining matched asymptotic approximations in the low- and high-density limits, we obtain a cubic polynomial approximation of the self-diffusion coefficient that is numerically accurate for all densities. This cubic approximation agrees extremely well with numerical simulations. It also coincides with the Taylor expansion up to the second-order in the density of the self-diffusion coefficient obtained using a rigorous recursive method. [ABSTRACT FROM AUTHOR]

The evaluation of an oil's oxidation status during industrial production is highly important for monitoring the oil's purity and nutritional value during production, transportation, storage, and cooking. The oil and food industry is seeking a real-time, non-destructive, rapid, robust, and low-cost sensor for nutritional oil's material characterization. Towards this goal, a 1H LF-NMR relaxation sensor application based on the chemical and structural profiling of non-oxidized and oxidized oils was developed. This study dealt with a relatively large-scale oil oxidation database, which included crude data of a 1H LF-NMR relaxation curve, and its reconstruction into T1 and T2 spectral fingerprints, self-diffusion coefficient D, and conventional standard chemical test results. This study used a convolutional neural network (CNN) that was trained to classify T2 relaxation curves into three ordinal classes representing three different oil oxidation levels (non-oxidized, partial oxidation, and high level of oxidation). Supervised learning was used on the T2 signals paired with the ground-truth labels of oxidation values as per conventional chemical lab oxidation tests. The test data results (not used for training) show a high classification accuracy (95%). The proposed AI method integrates a large training set, an LF-NMR sensor, and a machine learning program that meets the requirements of the oil and food industry and can be further developed for other applications. [ABSTRACT FROM AUTHOR]

Interactions between nanoparticles (NPs) determine their self-organization and dynamic processes. In these systems, a quantitative description of the interparticle forces is complicated by the presence of the hydrophobic effect (HE), treatable only qualitatively, and due to the competition between the hydrophobic and hydrophilic forces. Recently, instead, a sort of crossover of HE from hydrophilic to hydrophobic has been experimentally observed on a local scale, by increasing the temperature, in pure confined water and studying the occurrence of this crossover in different water–methanol solutions. Starting from these results, we then considered the idea of studying this process in different nanoparticle solutions. By using photon correlation spectroscopy (PCS) experiments on dendrimer with OH terminal groups (dissolved in water and methanol, respectively), we show the existence of this hydrophobic–hydrophilic crossover with a well defined temperature and nanoparticle volume fraction dependence. In this frame, we have used the mode coupling theory extended model to evaluate the measured time-dependent density correlation functions (ISFs). In this context we will, therefore, show how the measured spectra are strongly dependent on the specificity of the interactions between the particles in solution. The observed transition demonstrates that just the HE, depending sensitively on the system thermodynamics, determines the hydrophobic and hydrophilic interaction properties of the studied nanostructures surface. [ABSTRACT FROM AUTHOR]

1H NMR with a pulsed magnetic field gradient method are used to measure the coefficients of self-diffusion of ferulic and sinapic acids in binary carbon tetrachloride–acetone-d6 solvent at temperatures of 278 and 298 K. Data show that the acids' coefficients of self-diffusion grow along with the concentration of acetone-d6 and temperature. It is shown that the effective hydrodynamic radii of acids do not depend on the composition of the binary solvent within the experimental error. In light of molecular association, this behavior can be explained by the competition between two processes: acid–acetone heteroassociation and acid–acid self-association. [ABSTRACT FROM AUTHOR]

The Spatio-temporal pattern induced by self-diffusion of a predator-prey model with Boiling type III functional response that incorporates the hunting cooperation between predators has been investigated in this paper. For the local model without structure, the stability of non-negative equilibria with or without collaborative hunting in predators is studied. For the Spatio-temporal model, we analyze the effect of hunting cooperation term on diffusion-driven Turing instability of the homogeneous positive equilibria. To get an idea about patterns formation near the Turing bifurcation, we derive and give a detailed study of the amplitude equation using the multiple-scale analysis. Our result shows that hunting cooperation plays a crucial role in determining the stability and the Turing bifurcation of the model, which is in sharp contrast to the case without cooperation in hunting. Furthermore, some numerical simulations are illustrated to visualize the complex dynamic behavior of the model. [ABSTRACT FROM AUTHOR]

The diffusion coefficient of a metallic alloy system is critical to understanding phase transformations, mechanical properties, and failure mechanisms such as creep. Rather than performing costly and time consuming experiments, first-principles calculations based on density functional theory have emerged as a robust alternative to experimentally determined diffusion coefficients. In this work, first-principles calculations based on density functional theory are used to investigate the effects of varying the exchange-correlation functional and supercell size had on the accuracy of calculated self-diffusion coefficients. Self-diffusion and thermodynamic properties of Cu, Ni, and Ag are calculated using the two exchange-correlation functionals: the local density approximation and the generalized gradient approximation of Perdew, Burke, and Ernzerhof for solids. Supercells of 32, 64, and 108 atoms are used to investigate the minimum supercell size necessary to isolate the vacancy. Finally, two methods for accounting for vibrational entropy contributions due to temperature are employed: a simple estimation of the diffusion prefactor used previously in the literature and harmonic phonon calculations. The estimation of the diffusion prefactor produces acceptable results for Cu, but not for the other metals investigated. The harmonic phonon calculations improves both self-diffusion and thermodynamic properties when compared to experimental values for Cu, Ni, and Ag. For Cu and Ni, self-diffusion coefficients and related thermodynamic properties are consistent and stable regardless of the supercell size or exchange-correlation functional employed. [ABSTRACT FROM AUTHOR]

One primary concern in colloid science is understanding the relationship of its macroscopic rheology and diffusion behavior with the observed microscopic arrangements of the nanoparticles in the fluid. This manuscript addresses the study of these dynamical properties through a first-principle stochastic method. Both properties directly relate to the observed fluid structure factor, which depends on a few known material parameters. However, in the literature, this static quantity is reported up to the first prominent peak of its small momentum transfer of the scattered radiation, leading to inaccurate determination of the transport properties. Here, it is proposed to use the rescaled mean spherical approximation under the requirement of fitting the experimental data of the structure beyond the dependence of more significant wave numbers. The predicted viscosity agrees with the observed ones at a low volume fraction of particles for ferrofluids dispersed in polymer solvents. This rheological quantity is inversely related to the self-diffusion coefficient of a tracer particle. [ABSTRACT FROM AUTHOR]

In this paper, the spatiotemporal dynamics and pattern formation of a space–time discrete intraguild predation model with self-diffusion are investigated. The model is obtained by applying a coupled map lattice (CML) method. First, using linear stability analysis, the existence and stability conditions for fixed points are determined. Second, using the center manifold theorem and the bifurcation theory, the occurrence of flip, Neimark-Sacker, and Turing bifurcations are discussed. It is shown that the patterns obtained are results of Turing, flip, and Neimark-Sacker instabilities. Numerical simulations are performed to verify the theoretical analysis and to reveal complex and rich dynamics of the model, such as times series, maximal Lyapunov exponent, bifurcation diagrams, and phase portraits. Interesting patterns like spiral pattern, polygonal pattern, and the combinations of patterns of spiral waves and stripes are formed. The CML model's results help to understand how a spatially extended, discrete intraguild predation model forms complex patterns. Notably, the continuous reaction–diffusion counterpart of the model under study is incapable of experiencing Turing instability. • Dynamics of a space–time discrete intraguild predation model with self-diffusion are investigated. • Interesting patterns like spiral pattern, polygonal pattern, and the combinations of patterns of spiral waves and stripes are formed. • The continuous reaction–diffusion counterpart of the model under study is incapable of experiencing Turing instability. [ABSTRACT FROM AUTHOR]

A novel dedicated device is introduced to enable investigation of the filtration draining process of different acid-induced milk gels using Magnetic Resonance Imaging (MRI). This approach allows the spatio-temporal resolution of serum content and distribution in gels throughout draining. Its application for the characterization of five acid gels formulated using reconstituted or fresh milk and using different thermal treatments and/or lactic starters indicates its large potential for a better understanding of acid-induced gel draining in dairy industry. Self-diffusion and relaxation measurements using Time Domain-Nuclear Magnetic Resonance (TD-NMR) were performed on the gels following filtration draining to validate and supplement the MRI results, while gels obtained through centrifugation were examined in view of correlating T 2 relaxation times to the water content of gels. The presence of lipids in reconstituted milk or the substitution of a casein fraction by microparticulated denatured whey proteins were shown to impact the structure of gels and their serum holding capacity. • New MRI device to study the filtration draining process of acid-induced milk gels. • Spatio-temporal resolution of serum content in acid milk gels throughout filtration draining. • Self-diffusion and relaxation measurements using TD-NMR on gels to validate and supplement the MRI measurements. • Effects of acid gel formulation and preparation on filtration and centrifugation draining kinetics. [ABSTRACT FROM AUTHOR]

Solid electrolyte interphase (SEI) is considered as an effective way to suppress Li dendrite. However, most of the constructed SEI films are usually nonuniform and incompact due to the uncertain interface between Li and electrolyte, finally resulting in failure to Li anode protection. To overcome such disadvantage, a stable pristine SEI film is formed successfully by self‐diffusion and assembly when the surface reaction occur between the molten Li and the substrate, benefitting from the ultra‐high chemical activity, atomic level smoothness, and flowability of liquid lithium. It is an inside–outside process via the obtained Li composites migrating from reaction interface to the Li liquid metal surface. Then, the obtained SEI can lead to a stable and long‐lifespan Li integrated electrode, showing the self‐diffusion/assembly strategy upon liquid Li‐metal is a promising way for practical dendrite‐free anode. [ABSTRACT FROM AUTHOR]

Fullerene derivatives are of great interest in various fields of science and technology. Fullerene derivatives are known to have pronounced anticancer and antiviral activity. They have antibacterial properties. Their properties are largely determined by association processes. Understanding the nature and properties of associates in solvents of various types will make it possible to make significant progress in understanding the mechanisms of aggregation of molecules of fullerene derivatives in solutions. Thus, this work, aimed at studying the size and stability of associates, is relevant and promising for further research. The NMR method in a pulsed field gradient was used, which makes it possible to directly study the translational mobility of molecules. The sizes of individual molecules and associates were calculated based on the Stokes–Einstein model. The lifetime of associates was also estimated. The interaction of water-soluble C60 fullerene derivatives with erythrocytes was also evaluated. The values of self-diffusion coefficients and the lifetime of molecules of their compounds in cell membranes are obtained. It is concluded that the molecules of fullerene derivatives are fixed on the cell surface, and their forward movement is controlled by lateral diffusion. [ABSTRACT FROM AUTHOR]

The food quality of edible oils is dependent on basic chemical and structural changes that can occur by oxidation during preparation and storage. A rapid and efficient analytical method of the different steps of oil oxidation is described using a time-domain nuclear magnetic resonance (TD-NMR) sensor for measuring signals related to the chemical and physical properties of the oil. The degree of thermal oxidation of edible oils at 80 °C was measured by the conventional methodologies of peroxide and aldehyde analysis. Intact non-modified samples of the same oils were more rapidly analyzed for oxidation using a TD-NMR sensor for 2D T1-T2 and self-diffusion (D) measurements. A good linear correlation between the D values and the conventional chemical analysis was achieved, with the highest correlation of R2 = 0.8536 for the D vs. the aldehyde concentrations during the thermal oxidation of poly-unsaturated linseed oils, the oil most susceptible to oxidation. A good correlation between the D and aldehyde levels was also achieved for all the other oils. The possibility to simplify and minimize the time of oxidative analysis using the TD NMR sensors D values is discussed as an indicator of the oil's oxidation quality, as a rapid and accurate methodology for the oil industry. [ABSTRACT FROM AUTHOR]

We discuss a phenomenon regarding water that was until recently a subject of scientific interest: i.e., the dynamical crossover, from the fragile to strong glass forming material, for both bulk and protein hydration water. Such crossover is characterized by a temperature TL in which significant dynamical changes like the decoupling (or the violation of the Stokes-Einstein relation) of homologous transport parameters, e.g., the density relaxation time τ and the viscosity η, occur in the system. On this respect we considered the dynamic properties of water-protein systems. More precisely, we focused our study on proteins and their hydration water, as far as bulk and confined water. In order to clarify the effects of the water dynamical crossover on the protein properties we considered and discussed in a comparative way previous and new experimental data, obtained from different techniques and molecular dynamic simulation (MD). We pointed out the reasons for different dynamical findings from the use of different experimental techniques.