Intermediate Volume Fractions Research Articles

The neurovascular unit and its correlation with cognitive performance in patients with cerebral small vessel disease: a canonical correlation analysis approach

Growing evidence indicates an important role of neurovascular unit (NVU) dysfunction in the pathophysiology of cerebral small vessel disease (cSVD). Individually measurable functions of the NVU have been correlated with cognitive function, but a combined analysis is lacking. We aimed to perform a unified analysis of NVU function and its relation with cognitive performance. The relationship between NVU function in the white matter and cognitive performance (both latent variables composed of multiple measurable variables) was investigated in 73 patients with cSVD (mean age 70 ± 10 years, 41% women) using canonical correlation analysis. MRI-based NVU function measures included (1) the intravoxel incoherent motion derived perfusion volume fraction (f) and microvascular diffusivity (D*), reflecting cerebral microvascular flow; (2) the IVIM derived intermediate volume fraction (fint), indicative of the perivascular clearance system; and (3) the dynamic contrast-enhanced MRI derived blood–brain barrier (BBB) leakage rate (Ki) and leakage volume fraction (VL), reflecting BBB integrity. Cognitive performance was composed of 13 cognitive test scores. Canonical correlation analysis revealed a strong correlation between the latent variables NVU function and cognitive performance (r 0.73; p = 0.02). For the NVU, the dominating variables were D*, fint, and Ki. Cognitive performance was driven by multiple cognitive tests comprising different cognitive domains. The functionality of the NVU is correlated with cognitive performance in cSVD. Instead of focusing on individual pathophysiological mechanisms, future studies should target NVU dysfunction as a whole to acquire a coherent understanding of the complex disease mechanisms that occur in the NVU in cSVD.Trial registration: NTR3786 (Dutch Trial Register).

Exploring 2D X-ray diffraction phase fraction analysis with convolutional neural networks: Insights from kinematic-diffraction simulations

Deep-learning models are effective for analyzing the complex information in 2D X-ray diffraction (XRD) patterns. Accurately collecting parameters of the material sample is crucial during model training, significantly impacting model performance. In this study, we employ a kinematic-diffraction simulator to generate simulated 2D XRD patterns for Ti–6Al–4V alloy, allowing precise control of sample parameters. These simulated patterns are used to train convolutional neural networks, predicting β\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\upbeta$$\\end{document}-phase volume fractions. The training data set consists exclusively of 2D XRD patterns with pure α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\upalpha$$\\end{document}- or pure β\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\upbeta$$\\end{document}-phase, while the testing set incorporates patterns with intermediate phase volume fraction. In particular, we investigate how the architectures of the model influence prediction reliability and computational performance. Experimental results reveal that, with appropriate training, the convolutional neural network accurately detects intermediate phase volume fractions even trained with only pure-phase patterns, achieving a mean square error accuracy of 9.4×10-4\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$9.4 \ imes 10^{-4}$$\\end{document}.Graphical abstract

Colloidal gelation induced by ring polymers

We provide unambiguous experimental evidence that ring polymers are stronger depleting agents in colloidal suspensions than their linear counterparts. We use an intermediate volume fraction (ϕc=0.44) colloidal gel based on the classic poly(methyl methacrylate) (PMMA) hard spheres, in which the polystyrene depletant is either linear or ring of the same molar mass or the same size. We systematically increase the depletant concentration from zero (no attraction) to well above the gelation point and find that in the presence of rings, gels are formed at smaller concentrations and possess a larger storage modulus in comparison to those induced by the linear chains. Consequently, the yield stress is enhanced; however, the yield strain (gel deformability) remains concomitantly unaffected. Our experimental findings are in agreement with theoretical calculations based on effective interaction potentials. Hence, polymer architecture is a powerful entropic tool to tailor the strength of colloidal gels. Published by the American Physical Society 2024

Prediction of Compressive Behavior of Laser-Powder-Bed Fusion-Processed TPMS Lattices by Regression Analysis

Triply periodic minimal surface (TPMS) structures offer lightweight and high-stiffness solutions to different industrial applications. However, testing of these structures to calculate their mechanical properties is expensive. Therefore, it is important to predict the mechanical properties of these structures effectively. This study focuses on the effectiveness of using regression analysis and equations based on experimental results to predict the mechanical properties of diamond, gyroid, and primitive TPMS structures with different volume fractions and build orientations. Gyroid, diamond, and primitive specimens with three different volume fractions (0.2, 0.3, and 0.4) were manufactured using a laser powder bed fusion (LPBF) additive manufacturing process using three different build orientations (45°, 60°, and 90°) in the present study. Experimental and statistical results revealed that regression analysis and related equations can be used to predict the mass, yield stress, elastic modulus, specific energy absorption, and onset of densification values of TPMS structures with an intermediate volume fraction value and specified build orientation with an error range less than 1.4%, 7.1%, 19.04%, 21.6%, and 13.4%, respectively.

Moisture and Glass Transition Temperature Kinetics of Ambient-Cured Carbon/Epoxy Composites

Carbon fiber reinforced polymer composites are widely used in the rehabilitation, repair, and strengthening of civil, marine, and naval infrastructure and structural systems. In these applications, they are exposed to a range of exposure conditions, including humidity and immersion, which are known to affect the durability of the resin and the fiber–matrix interface over long periods of time. This paper presents results of long-term hygrothermal aging of wet layup carbon/epoxy composites including through acceleration by temperature focusing on the development of a comprehensive understanding of moisture uptake kinetics and its effects on glass transition temperature and interface and inter-/intra-laminar dominated performance characteristics. A two-phase model for uptake that incorporates both diffusion- and relaxation-/deterioration-dominated regimes, as well as a transition regime, is shown to describe uptake well. The inclusion of damage terms to the diffusion and relaxation coefficients is seen to capture changes well, with the effective diffusion and relaxation coefficients increasing with fiber volume fraction and temperature. Effects of uptake, including at elevated temperatures, reflective of accelerated aging, on glass transition temperature and flexural strength are correlated, emphasizing a three-stage progression of overall response in line with the moisture uptake changes. The drop in glass transition temperature per percent increase in moisture uptake was seen to range from a low of 4.38% per % increase in moisture content, for the highest volume fraction at the highest temperature, to a high of 6.95% per % increase in moisture content, for the intermediate volume fraction at the lowest temperature. The composites with heavier fabric showed the greatest drop in both glass transition temperature and flexural strength, indicating a level of correlation between these characteristics as well. It is shown that both glass transition temperature and flexural strength show steep initial decreases, followed by a regime with slower decrease and, then, an asymptotic or near-asymptotic response with time of immersion, suggesting a close correlation with moisture uptake, which forms the basis for future modeling.

Temperature-induced hysteresis in amplification and attenuation of surface-plasmon-polariton waves

The propagation of surface-plasmon-polariton (SPP) waves at the planar interface of a metal and a dielectric material was investigated for a dielectric material with strongly temperature-dependent constitutive properties. The metal was silver and the dielectric material was vanadium multioxide impregnated with a combination of active dyes. Depending upon the volume fraction of vanadium multioxide, either attenuation or amplification of the SPP waves may be achieved; the degree of attenuation or amplification is strongly dependent on both the temperature and whether the temperature is increasing or decreasing. At intermediate volume fractions of vanadium multioxide, for a fixed temperature, a SPP wave may experience attenuation if the temperature is increasing but experience amplification if the temperature is decreasing.

Molecular Dynamics of Lysine Dendrigrafts in Methanol–Water Mixtures

The molecular dynamics method was used to study the structure and properties of dendrigrafts of the first and second generations in methanol-water mixtures with various volume fractions of methanol. At a small volume fraction of methanol, the size and other properties of both dendrigrafts are very similar to those in pure water. A decrease in the dielectric constant of the mixed solvent with an increase in the methanol fraction leads to the penetration of counterions into the dendrigrafts and a reduction of the effective charge. This leads to a gradual collapse of dendrigrafts: a decrease in their size, and an increase in the internal density and the number of intramolecular hydrogen bonds inside them. At the same time, the number of solvent molecules inside the dendrigraft and the number of hydrogen bonds between the dendrigraft and the solvent decrease. At small fractions of methanol in the mixture, the dominant secondary structure in both dendrigrafts is an elongated polyproline II (PPII) helix. At intermediate volume fractions of methanol, the proportion of the PPII helix decreases, while the proportion of another elongated β-sheet secondary structure gradually increases. However, at a high fraction of methanol, the proportion of compact α-helix conformations begins to increase, while the proportion of both elongated conformations decreases.

A novel method to design monolithic catalysts for non-isothermal packed-bed reactors using topology optimisation

This research investigates the application of topology optimisation to the design of monolithic catalysts for packed-bed reactors with endothermic reactions. A reactor model has been developed based on the main assumptions of laminar flow and a first-order reaction. The model includes a catalytic reaction whose rate is determined by a proposed Arrhenius equation along with mass transfer limitations. Using the density-based method, the optimisation problem is formulated as a catalyst distribution problem. The catalyst volume fraction of elements in the discretised design domain determines the geometry of the monolithic structure and consequently the momentum, heat, and mass transfer characteristics of the reactor. By a combination of interpolation functions, continuous material properties and a sufficient penalisation for the intermediate fluid volume fraction values are derived. The Globally Convergent Method of Moving Asymptotes (GCMMA) was employed to solve the optimisation problem. The effects of initial guesses, the energy dissipation constraint, and the Peclet number on the design are investigated in a 2D framework. Then through a 3D optimisation, a complex structure with enhanced mass transfer, thermal, and hydraulic behaviour is developed. Compared to a reference honeycomb geometry with the same catalyst volume fraction, the resulting 3D optimised geometry shows quantitative improvements in terms of the conversion and pressure drop.

Thermo-Statistical Effects of Inclusions on Vesicles: Division into Multispheres and Polyhedral Deformation.

The construction of simple cellular models has attracted much attention as a way to explore the origin of life or elucidate the mechanisms of cell division. In the absence of complex regulatory systems, some bacteria spontaneously divide through thermostatistically elucidated mechanisms, and incorporating these simple physical principles could help to construct primitive or artificial cells. Because thermodynamic interactions play an essential role in such mechanisms, this review discusses the thermodynamic aspects of spontaneous division models of vesicles that contain a high density of inclusions, with their membrane serving as a boundary. Vesicles with highly dense inclusions are deformed according to the volume-to-area ratio. The phase separation of beads at specific intermediate volume fractions and the associated polyhedral deformation of the membrane are considered in relation to the Alder transition. Current advances in the development of a membrane-growth vesicular model are summarized. The thermostatistical understanding of these mechanisms could become a cornerstone for the construction of vesicular models that display spontaneous cell division.

Topology optimization considering multi-axis machining constraints using projection methods

Topology optimization under manufacturing constraints is an important and active area of research. The primary goal is to ensure optimized designs are manufacturable, and more specifically, are optimized considering the geometric restrictions associated with the considered manufacturing process. Herein we consider the manufacturing process of machining, which imposes a challenging set of geometric restrictions compared to free-form topology optimization. We consider the case of 2.5 axis machining, as well as more general 5-axis machining, and use a projection-based approach for ensuring designed voids have a direct path to the boundary of the design domain along a candidate machining axis, and at a minimum feature size of the machining tool. As with other projection approaches, these manufacturing constraints are achieved through the projection operations and explicit constraints are not needed. Intermediate volume fractions are prevented through SIMP penalization and sensitivities are computed by the adjoint method for use in a typical gradient-based optimizer. Various 2D and 3D minimum compliance examples are presented, and solutions are shown to respect the imposed 2.5 axis and 5 axis machining constraints with near 0/1 (void/solid) final distributions of material.

Yielding to stress in Pickering emulsions at dilute and intermediate volume fractions

Emulsions yield and flow (or lose their shape) when sufficient stress is applied to force the drops to move past each other. The drops in emulsions stabilised by nanoparticles do not move all at once, unlike in emulsions stabilised by surfactants. This is because particles that are not attached to the oil-water interface can aggregate into networks in the continuous phase. The networks around the drops must be disrupted before the drops can move. We used a combination of steady and oscillatory shear, and creep measurements to probe Pickering emulsion yielding behaviour at different drop volume fractions. We characterised the heterogeneous structure of the emulsions on the micro- and nano-scale using confocal fluorescence and electron microscopy techniques. A key finding is that two processes occur during the transition from solid to fluid flow in Pickering emulsions. This is best revealed by oscillatory measurements. We also found evidence of structure recovery in emulsions while they were being sheared. These results have implications for designing Pickering emulsions which retain their shape, rather than slumping.

Computational Screening of Physical Solvents for CO2 Pre-combustion Capture.

A computational scheme was used to screen physical solvents for CO2 pre-combustion capture by integrating the commercial NIST database, an in-house computational database, chem-informatics, and molecular modeling. A commercially available screened hydrophobic solvent, diethyl sebacate, was identified from the screening with favorable physical properties and promising absorption performance. The promising performance to use diethyl sebacate in CO2 pre-combustion capture has also been confirmed from experiments. Water loading in diethyl sebacate is very low, and therefore, water is kept with H2 in the gas stream. The favorable CO2 interaction with diethyl sebacate and the intermediate solvent free volume fraction leads to both high CO2 solubility and high CO2/H2 solubility selectivity in diethyl sebacate. An in-house NETL computational database was built to characterize CO2, H2, N2, and H2O interactions with 202 different chemical functional groups. It was found that 13% of the functional groups belong to the strong interaction category with the CO2 interaction energy between -15 and -21 kJ/mol; 62% of the functional groups interact intermediately with CO2 (-8 to -15 kJ/mol). The remaining 25% of functional groups interact weakly with CO2 (below -8 kJ/mol). In addition, calculations show that CO2 interactions with the functional groups are stronger than N2 and H2 interactions but are weaker than H2O interactions. The CO2 and H2O interactions with the same functional groups exhibit a very strong linear positive correlation coefficient of 0.92. The relationship between CO2 and H2 gas solubilities and solvent fractional free volume (FFV) has been systematically studied for seven solvents at 298.2 K. A skewed bell-shaped relation was obtained between CO2 solubility and solvent FFV. When an organic compound has a density approximately 10% lower than its density at 298.2 K and 1 bar, it exhibits the highest CO2 loading at that specific solvent density and FFV. Note that the solvent densities were varied using simulations, which are difficult to be obtained from the experiment. In contrast, H2 solubility results exhibit an almost perfect positive linear correlation with the solvent FFV. The theoretical maximum and minimum physical CO2 solubilities in any organic compound at 298.2 K were estimated to be 11 and 0.4 mol/MPa L, respectively. An examination of 182 experimental CO2 physical solubility data and 29 simulated CO2 physical solubilities shows that all the CO2 physical solubility data are within the maximum and minimum with only a few exceptions. Finally, simulations suggest that in order to develop physical solvents with both high CO2 solubility and high CO2/H2 solubility selectivity, the solvents should contain functional groups which are available to interact strongly with CO2 while minimizing FFV.

3D random walk model of diffusion in human Hypo- and Hyper- mineralized collagen fibrils

Bone tissue is composed at the nanoscale of apatite minerals, collagen molecules and water that form the mineralized collagen fibril (MCF). Water has a crucial role in bone biomineralization. We developed a 3D random walk model to investigate the water diffusion process within the MCF for three different scenarios, namely low, intermediate and high mineral volume fraction. The MCF geometric model is obtained after applying 6·106 translational and rotational perturbations to an ordered arrangement of mineral. Subsequently, we compute 300 random trajectories of water molecules within the MCF for each mineral volume fraction. Every trajectory is constituted of up to 500 k positions of the water particle. We determined the diffusion coefficient from the linear fit of the mean squared displacement of water molecules as a function of time. We investigate changes in the diffusivity values in relation to variation of bone mineral content. The analysis performed on the random walk data, for all mineralization conditions, leads to diffusion coefficients in good agreement with the diffusivity outcomes achieved from previous experimental studies. Thus, the 3D geometrical configuration adopted in this numerical study appears suitable for modelling the MCF with different volume fractions, from hypo- to hyper-mineralized conditions. We observed that low mineral content is associated with an increase of the water diffusion, while lower values of diffusivity are determined in hypermineralized conditions. In agreement with experimental data, our results highlight the influence of the structural alterations on the mass transport properties.

Shear thinning and thickening in dispersions of spherical nanoparticles

We present a molecular dynamics study of the flow of rigid spherical nanoparticles in a simple fluid. We evaluate the viscosity of the dispersion as a function of shear rate and nanoparticle volume fraction. We observe shear-thinning behavior at low volume fractions; as the shear rate increases, the shear forces overcome the Brownian forces, resulting in more frequent and more violent collisions between the nanoparticles. This in turn results in more dissipation. We show that in order to be in the shear-thinning regime the nanoparticles have to order themselves into layers longitudinal to the flow to minimize the collisions. As the nanoparticle volume fraction increases there is less room to form the ordered layers; consequently as the shear rate increases the nanoparticles collide more, which results in turn in shear thickening. Most interestingly, we show that at intermediate volume fractions the system exhibits metastability, with successions of ordered and disordered states along the same trajectory. Our results suggest that for nanoparticles in a simple fluid the hydroclustering phenomenon is not present; instead the order-disorder transition is the leading mechanism for the transition from shear thinning to shear thickening.

Influence of TMAO as co-solvent on the gelation of silica-PNIPAm core-shell nanogels at intermediate volume fractions.

We study the structure and dynamics of poly(N‐isopropylacrylamide) (PNIPAm) core‐shell nanogels dispersed in aqueous trimethylamine N‐oxide (TMAO) solutions by means of small‐angle X‐ray scattering and X‐ray photon correlation spectroscopy (XPCS). Upon increasing the temperature above the lower critical solution temperature of PNIPAm at 33 °C, a colloidal gel is formed as identified by an increase of I(q) at small q as well as a slowing down of sample dynamics by various orders of magnitude. With increasing TMAO concentration the gelation transition shifts linearly to lower temperatures. Above a TMAO concentration of approximately 0.40 mol/L corresponding to a 1 : 1 ratio of TMAO and NIPAm groups, collapsed PNIPAm states are found for all temperatures without any gelation transition. This suggests that reduction of PNIPAm‐water hydrogen bonds due to the presence of TMAO results in a stabilisation of the collapsed PNIPAm state and suppresses gelation of the nanogel.

Mechanisms and patterns of magmatic fluid transport in cooling hydrous intrusions

Volatile outgassing from hydrous magma intrusions emplaced and cooling in the Earth's upper crust is key to a number of geologic processes including volcanic eruptions and ore deposition, yet the physical interactions between production, storage and transport of a magmatic volatile phase within magmatic intrusions and their large-scale thermal evolution have remained elusive. We performed numerical simulations of aqueous volatile transport in generic magma chambers as they crystallize in response to conductive and convective cooling and thereby transition from a crystal - volatile - melt suspension to a mush and eventually to a rigid rock. We used simplified but realistic material properties based on published phase equilibrium experiments, published grain-scale modeling results and general geological constraints.We found that the intrusion depth and water content exert decisive control on the rates and mechanisms of intrusion outgassing. Above a critical volatile content, highly permeable capillary tubes develop in crystal mush regions with intermediate crystal volume fractions (∼ 0.5 to 0.7), and such grain-scale tubes provide rapid intrusion-scale degassing paths. These tubes are located in a ring-like mush region inside the intrusion, allowing strongly lateral flow and focusing towards the top of the intrusion. If the water content of the magma is close to saturation at the time of emplacement (5 to 6 wt% H2O) and the depth of the magma chamber roof is at least 4 km deep, initially distributed breakthrough points may coalesce to a single area of fluid release. Large-scale intrusion geometry determines this location of focused fluid release, and cooling rate and size of the intrusion determine overall fluid flux. Feedbacks between local hydrofracturing and heat advection break up the focused fluid expulsion into many short-lived pulses. These conditions for large-scale fluid focusing favor the formation of porphyry copper deposits, but might also trigger caldera-forming ignimbrite eruptions.

Translational and rotational dynamics of a self-propelled Janus probe in crowded environments.

We computationally investigate the dynamics of a self-propelled Janus probe in crowded environments. The crowding is caused by the presence of viscoelastic polymers or non-viscoelastic disconnected monomers. Our simulations show that the translational as well as rotational mean square displacements have a distinctive three-step growth for fixed values of self-propulsion force, and steadily increase with self-propulsion, irrespective of the nature of the crowder. On the other hand, in the absence of crowders, the rotational dynamics of the Janus probe is independent of self-propulsion force. On replacing the repulsive polymers with sticky ones, translational and rotational mean square displacements of the Janus probe show a sharp drop. Since different faces of a Janus particle interact differently with the environment, we show that the direction of self-propulsion also affects its dynamics. The ratio of long-time translational and rotational diffusivities of the self-propelled probe with a fixed self-propulsion, when plotted against the area fraction of the crowders, passes through a minimum and at higher area fraction merges to its value in the absence of the crowder. This points towards the decoupling of the translational and rotational dynamics of the self-propelled probe at an intermediate area fraction of the crowders. However, such translational-rotational decoupling is absent for passive probes.

Extending estimation of the critical deposition velocity in solid–liquid pipe flow to ideal and non-ideal particles at low and intermediate solid volume fractions

The critical deposition velocity in horizontal pipe flow of liquid-solid slurries separates bed-forming and fully suspended flows. A compilation of critical deposition velocity data is presented using new experimental data (for particles ranging from 9 to 690 µm in diameter) along with data from the literature, and a close correlation between the particle Reynolds number and the Archimedes number (which describe the properties of the flow and the liquid and solid phases) is found. The role of solid particle packing is discussed and suggestions are made for the incorporation of solid-phase material properties – specifically particle shape and angularity, and surface forces – into an empirical parameter, the volume factor, α, to account for the deviation of particle behaviour from ideal, non-interacting, hard-sphere behaviour.

Spectral Diffusion Analysis of Intravoxel Incoherent Motion MRI in Cerebral Small Vessel Disease.

BackgroundCerebral intravoxel incoherent motion (IVIM) imaging assumes two components. However, more compartments are likely present in pathologic tissue. We hypothesized that spectral analysis using a nonnegative least‐squares (NNLS) approach can detect an additional, intermediate diffusion component, distinct from the parenchymal and microvascular components, in lesion‐prone regions.PurposeTo investigate the presence of this intermediate diffusion component and its relation with cerebral small vessel disease (cSVD)‐related lesions.Study TypeProspective cross‐sectional study.PopulationPatients with cSVD (n = 69, median age 69.8) and controls (n = 39, median age 68.9).Field Strength/SequenceWhole‐brain inversion recovery IVIM acquisition at 3.0T.AssessmentEnlarged perivascular spaces (PVS) were rated by three raters. White matter hyperintensities (WMH) were identified on a fluid attenuated inversion recovery (FLAIR) image using a semiautomated algorithm.Statistical TestsRelations between IVIM measures and cSVD‐related lesions were studied using the Spearman's rank order correlation.ResultsNNLS yielded diffusion spectra from which the intermediate volume fraction f int was apparent between parenchymal diffusion and microvasular pseudodiffusion. WMH volume and the extent of MRI‐visible enlarged PVS in the basal ganglia (BG) and centrum semiovale (CSO) were correlated with f int in the WMHs, BG, and CSO, respectively. f int was 4.2 ± 1.7%, 7.0 ± 4.1% and 13.6 ± 7.7% in BG and 3.9 ± 1.3%, 4.4 ± 1.4% and 4.5 ± 1.2% in CSO for the groups with low, moderate, and high number of enlarged PVS, respectively, and increased with the extent of enlarged PVS (BG: r = 0.49, P < 0.01; CSO: r = 0.23, P = 0.02). f int in the WMHs was 27.1 ± 13.1%, and increased with the WMH volume (r = 0.57, P < 0.01).Data ConclusionWe revealed the presence of an intermediate diffusion component in lesion‐prone regions of cSVD and demonstrated its relation with enlarged PVS and WMHs. In tissue with these lesions, tissue degeneration or perivascular edema can lead to more freely diffusing interstitial fluid contributing to f int. Level of Evidence: 2 Technical Efficacy: Stage 2J. Magn. Reson. Imaging 2020;51:1170–1180.

Interactive thermal and inertial buckling of rotating temperature-dependent FG-CNT reinforced composite beams

Current research deals with thermal buckling of rotating carbon nanotube reinforced composite (CNTRC) beams. Material properties of the composite beam are assumed to be temperature dependent. Also volume fraction of CNT may change across the beam thickness which results in a functionally graded media. Beam is subjected to uniform temperature rise and constant angular rotating speed. The governing equations of the composite beam are obtained using the Timoshenko beam theory and von Kármán type of kinematic assumptions. Material properties of the composite media are estimated using a refined rule of mixtures approach. The obtained governing equations of the composite beam are linearized to study the pre-buckling deformations and conditions for the occurrence of classical bifurcation buckling are analysed. After that, using the adjacent equilibrium criterion, the stability equations governing the onset of buckling are obtained. These equations are solved by means of the generalized differential quadratures method. Numerical results are given to analyse the conditions of thermo-inertial buckling for rotating FG-CNTRC beams with different boundary conditions, various volume fractions and graded patterns for CNTs and different geometrical parameters. It is shown that beams with intermediate volume fraction of CNTs do not have necessarily intermediate critical buckling temperature. Also for certain conditions of boundary conditions, rotation may increase the critical buckling temperature of the beam.