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Static granular packings play a central role in numerous industrial applications and natural settings. In these situations, fluid or fine particle flow through a bed of static particles is heavily influenced by the narrowest passage connecting the pores of the packing, commonly referred to as pore throats, or constrictions. Existing studies predominantly assume monodisperse rigid particles, but this is an oversimplification of the problem. In this work, we illustrate the connection between pore throat size, polydispersity, and particle deformation in a packed bed of spherical particles. Simple analytical expressions are provided to link these properties of the packing, followed by examples from Discrete Element Method (DEM) simulations of fine particle percolation demonstrating the impact of polydispersity and particle deformation. Our intent is to emphasize the substantial impact of polydispersity and particle deformation on constriction size, underscoring the importance of accounting for these effects in particle transport in granular packings. [ABSTRACT FROM AUTHOR]

An experimental investigation and a mathematical simulation of the gravitational stratification of a polydisperse water–oil emulsion in a rectangular cell have been performed. Histograms of the size distribution of droplets in the initial emulsion have been obtained using the approach based on the analysis of the images of an emulsion sample, made on an optical microscope at different magnifications. The concentration distributions of droplets along the height of the cell have been constructed using results of the digital processing of the photos of the emulsion, obtained in the experiment on its gravitational stratification. A methodology of numerical simulation of the stratification of a polydisperse emulsion system, based on the representation of this system as a set of quasi-monodisperse subsystems and on the combined solution of the equations for the sedimentation of droplets different in size in the one-liquid approximation, is proposed. [ABSTRACT FROM AUTHOR]

In this work, we investigated the linear viscoelasticity of semidilute polydisperse bubble suspensions via small amplitude oscillatory shear (SAOS) tests performed in a rheo-optical setup. For all tested suspensions, the measured viscoelastic moduli (G ′ , G ″) aligned with the theoretical predictions of the Jeffreys model for average dynamic capillary numbers (⟨ C d ⟩) greater than unity. But at lower ⟨ C d ⟩ values, experimental G ′ values exceeded theoretical predictions. To investigate this, we considered the effects of suspension polydispersity and various SAOS measurement artifacts, including bubble rise, coalescence, and changes in suspension microstructure over time. Polydispersity could not cause the observed deviation, because the viscoelastic trends deviate from those of classic single-mode relaxation only for bimodal bubble size distributions with equal volume fractions of very small and very large bubbles; in any other case, the polydisperse suspension behaves as monodisperse with a bubble radius equal to the volume-weighted mean radius. Furthermore, bubble rise proved to play a minor role, while SAOS rheo-optical experiments revealed that bubble size and organization varied negligibly during our measurements. The G ′ deviation at low ⟨ C d ⟩ values was linked to bubble fluid dynamic interactions induced by the bubble spatial distribution. Image analysis showed that at low bubble volume fractions, stronger and prolonged preshearing reduces these interactions by increasing the average interbubble distance. But this effect is negligible in denser suspensions, which show similar G ′ trends for any applied preshearing. Finally, a multimode Jeffreys model fitted to the experimental data showed that bubble interactions complicate the relaxation process, introducing multiple relaxation modes. [ABSTRACT FROM AUTHOR]

We study the effect of particle size polydispersity (δ) on the melting transition (T *), local ordering, solid–liquid coexistence phase and dynamics of two-dimensional Lennard–Jones fluids up to moderate polydispersity by means of computer simulations. The particle sizes are drawn at random from the Gaussian (G) and uniform (U) distribution functions. For these systems, we further consider two different kinds of particles, viz., particles having the same mass irrespective of size, and in the other case the mass of the particle scales with its size. It is observed that with increasing polydispersity, the value of T * initially increases due to improved packing efficiency (ϕ) followed by a decrease and terminates at δ ≈ 8% (U-system) and 14% (G-system) with no significant difference for both mass types. The interesting observation is that the particular value at which ϕ drops suddenly coincides with the peak of the heat capacity (CP) curve, indicating a transition. The quantification of local particle ordering through the hexatic order parameter (Q 6), Voronoi construction and pair correlation function reveals that the ordering decreases with increasing δ and T. Furthermore, the solid–liquid coexistence region for the G-system is shown to be comparatively wider in the T – δ plane phase diagram than that for the U system. Finally, the study of dynamics reveals that polydisperse systems relax faster compared to monodisperse systems; however, no significant qualitative differences, depending on the distribution type and mass polydispersity, are observed. [ABSTRACT FROM AUTHOR]

The distribution of fiber diameters plays a crucial role in the transport and sound absorbing properties of a three-dimensional random fibrous (3D-RF) medium. Conventionally, volume-weighted averaging of fiber diameters has been utilized as an appropriate microstructural descriptor to predict the static viscous permeability of 3D-RF media. However, the long wavelength acoustical properties of a 3D-RF medium are also sensitive to the smallest fibers, this is particularly true in the high-frequency regime. In our recent research, we demonstrated that an inverse volume-weighted averaging of fiber diameters can effectively serve as a complementary microstructural descriptor to capture the high-frequency behavior of polydisperse fibrous media. In the present work, we reexamine the identification of two representative volume elements (RVEs) which relies on the reconstruction of 3D-RF microstructures having volume-weighted and inverse-volume weighted averaged fiber diameters, respectively in the low-frequency and high frequency regimes. We investigate the implication of such a weighting procedure on the transport and sound absorbing properties of polydisperse fibrous media, highlighting their potential advantages. Furthermore, we discuss the challenges associated with this research field. Finally, we provide a brief perspective of the future directions and opportunities for advancing this area of study.

Abstract In the present study, low- and high-molecular-weight hyaluronic acids (LMW-HA and HMW-HA) were synthesized in vitro by truncated Streptococcus equisimilis hyaluronan synthases (SeHAS). The enzyme kinetic parameters were determined for each enzyme variant. The MW, structure, dispersity, and biological activity of polymers were determined by electrophoresis, FTIR spectroscopy, carbazole, cell proliferation, and cell migration assay, respectively. The specific activities were calculated as 7.5, 6.8, 4.9, and 2.8 µgHA µgenzyme −1 min−1 for SeHAS, HAS123, HAS23, and HASIntra, respectively. The results revealed SeHAS produced a polydisperse HMW-HA (268 kDa), while HAS123 and HAS23 produced a polydisperse LMW-HA (

In the present study, low- and high-molecular-weight hyaluronic acids (LMW-HA and HMW-HA) were synthesized in vitro by truncated Streptococcus equisimilis hyaluronan synthases (SeHAS). The enzyme kinetic parameters were determined for each enzyme variant. The MW, structure, dispersity, and biological activity of polymers were determined by electrophoresis, FTIR spectroscopy, carbazole, cell proliferation, and cell migration assay, respectively. The specific activities were calculated as 7.5, 6.8, 4.9, and 2.8 µgHA µgenzyme−1 min−1 for SeHAS, HAS123, HAS23, and HASIntra, respectively. The results revealed SeHAS produced a polydisperse HMW-HA (268 kDa), while HAS123 and HAS23 produced a polydisperse LMW-HA (< 30 kDa). Interestingly, HASIntra produced a low-disperse LMW-HA. Kinetics studies revealed the truncated variants displayed increased Km values for two substrates when compared to the wild-type enzyme. Biological assessments indicated all LMW-HAs showed a dose-dependent proliferation activity on endothelial cells (ECs), whereas HMW-HAs exhibited an inhibitory effect. Also, LMW-HAs had the highest cell migration effect at 10 µg/mL, while at 200 µg/mL, both LMW- and HMW-HAs postponed the healing recovery rate. The study elucidated that the transmembrane domains (TMDs) of SeHAS affect the enzyme kinetics, HA-titer, HA-size, and HA-dispersity. These findings open new insight into the rational engineering of SeHAS to produce size-defined HA. [ABSTRACT FROM AUTHOR]

For various purposes, it is required to compress the shape of the molecular weight distribution (MWD) of polymers into a limited set of parameters. With increasing molecular weight and polydispersity, the MWD data obtained from chromatography become increasingly unreliable due to deficiencies in the high molecular weight region, making estimation via melt rheology more preferable. A number of empirical parameters obtained from melt rheology can be related back to MWD parameters. The target of this study is to establish the reliability of such relations for polypropylene homo‐ and copolymers. It is found that correlations between polydispersity from rheological crossover modulus and polydispersity via chromatography are not always valid. Therefore, the range of applicability must be kept in mind when attempting predictions based on these correlations because rheological measurements are sensitive to molecular characteristics in ways different from chromatography. The use of a modified polydispersity index is shown to be more reliable. [ABSTRACT FROM AUTHOR]

Monodisperse gold nanoparticles (AuNPs) are an important guarantee of their scientific value and technical reproducibility in applications. The tartrate has a similar molecule structure and physicochemical properties to citrate, bur is much less reducibility and is usually not favorable for the formation of monodisperse AuNPs. We have prepared monodisperse AuNPs with tartrate (potassium sodium tartrate) as reducing and capping agent. Various parameters affecting the monodisperse properties during the preparation of tartrate‐capped AuNPs were analyzed, such as reversing the order of reactant addition and ripening of seeds, while adjusting the synthesis parameters such as time, temperature, and pH value. The final results show that the addition of a trace amount of silver (Ag) ion into chloroauric acid, the monodispersed tartrate‐capped AuNPs can be obtained with the size range of 9–40 nm. The fabricated gold seeds and grown tartrate‐capped AuNPs have narrow size dispersions (or polydispersity, σ<10 %). The minimum size dispersion of AuNPs with twice growth steps was as low as 5.73 %. So, the weak reducing agent of tartrate is one of good candidates to synthesize the monodispersity of AuNPs. Additionally, tartrate‐capped AuNPs have good stability and can be easily modified and form a large two‐dimensional (2D) monolayer nanostructure film. [ABSTRACT FROM AUTHOR]

This review focuses on how the modeling of dense granular media has advanced over the last 15 years. The jumping-off point of our review is the μ(I) rheology for dry granular flow, which opened the door to generic flow field modeling but was primarily geared toward problems involving small monodisperse grains of simple shapes. Our review focuses on advances in modeling more material types and behaviors including new approaches for modeling finite-grain-size effects or nonlocality, polydispersity and unmixing, and nontrivial grain shapes. We also discuss growing application areas with tractable order-reduction strategies with a focus on intrusion and locomotion problems. [ABSTRACT FROM AUTHOR]

Small‐angle X‐ray scattering (SAXS) which records reciprocal‐space signals with characteristic Bessel‐type oscillations is a powerful technique for studying nanoparticles. However, the size polydispersity (or size distribution) of nanoparticles in an ensemble sample smears the oscillational peaks and valleys in the SAXS profile, making it difficult to extract accurate real‐space information (e.g. three‐dimensional geometry) on the nanoparticles. In this work, a method capable of eliminating the size‐distribution‐induced smearing effect from SAXS profiles by taking the known size‐distribution function into consideration has been developed. The method employs a penalized iterative regression to fit the pair distance distribution function (PDDF) derived from a SAXS profile, recovering the representative PDDF of the nanoparticles. The method has been evaluated with a series of nanoparticle systems of various shapes and size distributions, showing their PDDF profiles to have high fidelity to the reference ideal PDDF profiles. Inverse Fourier transformation of the recovered PDDF profiles gives SAXS profiles presenting the characteristic Bessel‐type oscillations, enabling reconstruction of the representative three‐dimensional geometry of the nanoparticles. This method will help in the use of SAXS to image synthesized colloidal nanoparticles where size polydispersity is inevitable. [ABSTRACT FROM AUTHOR]

We study the liquid phase behavior of ternary mixtures of monodisperse hard spheres in solution. The interactions are modeled in terms of the second virial coefficient and can be additive hard sphere (HS) or non-additive hard sphere (NAHS) interactions. We give the set of equations that defines the phase diagram for mixtures of three components. We calculate the theoretical liquid–liquid phase separation boundary for two-phase separation (the binodal) and, if applicable, the three-phase boundary, as well as the plait points and the spinodal. The sizes of the three components are fixed. The first component (A) is the smallest one, the second component (B) is four times the size of the smallest component, and the third (C) component is three times the size of the smallest one. The interaction between the first two components is fixed, and this AB sub-mixture shows phase separation. The interactions of component C with the other two components are varied. Component C can be compatible or incompatible with components A and B. Depending on the compatibility of the components, the phase diagram is altered. The addition of the third component has an influence on the phase boundary, plait points, stability region, fractionation, and volume ratio between the different phases. When all sub-mixtures (AB, AC, and BC) show phase separation, a three-phase system becomes possible when the incompatibility among all components is high enough. The position and size of the three-phase region is dependent on the interactions between the different sub-mixtures. We study the fractionation off all components depending on specific parent concentrations. [ABSTRACT FROM AUTHOR]

Shear strength characterization of coarse granular materials often requires modifying the original material in order to fit samples in standard testing devices. This is done, however, at the expense of changing the particle size distribution (psd), employing scaling-down techniques such as parallel grading or scalping methods. Such procedures hide, nevertheless, another challenge. As a given particle size can present a characteristic grain shape, altering the grain size distribution can strongly modify the distribution of grain shapes. While the effects of grain shape on shear strength have been vastly covered in the literature, the effect of having different shapes along grain sizes has yet to be systematically assessed and understood. This article explores the critical shear strength of samples composed of particles with size-shape correlations using 2D discrete element simulations. Two cases of particle shape variability across grain sizes are studied: (1) the sharpness of grains' corners - modeled via the number of sides of regular polygons - and (2) the geometric irregularity of grains - where the corners of a polygon are not necessarily evenly spaced. The effects of these geometrical properties on the shear strength are assessed through a series of numerical simple shearing tests up to large levels of deformation. We find that granular materials presenting different number of sides across grain sizes can strongly modify their mechanical response depending on the grain-size correlation. On the contrary, grain shape irregularity turns out not to have a major effect on the critical shear strength. Microstructural analyses allow us to identify how each correlation affects load transmission mechanisms between grains, and the contribution of each grain shape class to the macroscopic shear strength. This work shows that particle sizes are not the only sample descriptor to consider when applying scaling-down techniques. It is equally key to characterize particle shapes across grain sizes to capture the material's mechanical response adequately.

Self‐diffusion of poly(acrylic acid) (PAA) in dilute solution is studied by pulsed field gradient (PFG)‐NMR, also known as DOSY, and correlated to molecular weight with scaling laws at varying pH. Fitting a diffusion coefficient distribution model to PFG‐NMR data, the molecular weight polydispersity of commercial PAA samples is quantified. Due to good agreement with GPC data, diffusion measurements offer a viable alternative to estimate chain length properties with minimal sample preparation. Similar results are achieved by dynamic light scattering (DLS), however, with lower precision. The evolution of the scaling exponent with increasing pH indicates a transition from a globular state in highly acidic conditions (ν = 0.46) to a partially stretched conformation with a maximum at pH 5 (ν = 0.67). At higher pH, counterion screening counteracts chain expansion, while an unexpected increase in the width of the diffusion coefficient distribution occurs. A universal scaling law of the diffusivity applies for a chain length range of 25 ≤ N ≤ 1585, albeit with distinctly different scaling exponents. While opposing arguments are brought forward in recent literature concerning the pH‐dependence of short‐chain conformations, analysis supports the view that chain conformation is significantly affected by pH, even for short chains. [ABSTRACT FROM AUTHOR]

Summary: The aim of this research was to investigate the effect of curcuma dispersion bead milling on particle size evolution over time. The study of 10 wt.% and 20 wt.% curcuma dispersions revealed that dispersions' polydispersity was decreasing up to 180 min which was found to be the optimum milling time with the volume mean diameter (d4,3) of (11.47 ± 0.85) μm. This diameter was the most effective with respect to the curcuma powder coagulation process attributed to the effect of curcuma oils after the milling time of 180 min. The mechanochemically atomized curcuma was used as a potential source of curcuminoids. By differential scanning calorimetry (DSC), two endothermic peaks were observed and related to curcuma melting effects. Curcumin powder exhibited one broad melting peak at 176 °C. Obtained data indicated that effective mechanochemical treatment makes curcuma powder a highly beneficial supplement applicable in food matrices of the human diet. [ABSTRACT FROM AUTHOR]

In‐depth analyses, including discharge behaviour, electrochemical impedance analysis, and for the first time, nonlinear frequency response analysis, are conducted on the ageing of negative electrodes with varying particle size distribution. The electrode‐resolved analysis is used to distinguish the kinetic and transport losses at the respective electrodes. For fine to medium‐sized particles at the negative electrode, ageing impacts are found more on the positive electrode: the impedance and nonlinear responses increase, suggesting that the charge transfer process at the positive electrode is worsened. Meanwhile, for coarse and broad negative particles, the impedance and nonlinear responses at negative electrodes decrease due to improved kinetics from micro‐cracking. The second harmonic reveals a change in the nature of the charge transfer during ageing: the charge transfer process at the positive electrode becomes asymmetric for fine and medium‐sized negative particles. Vice versa, the charge transfer process at the negative electrode becomes symmetric for coarse and broad negative particles. [ABSTRACT FROM AUTHOR]

Acyl‐coenzyme A thioesterase (Acot) enzymes are involved in a broad range of essential intracellular roles including cell signalling, lipid metabolism, inflammation and the opening of ion channels. Dysregulation in lipid metabolism has been linked to neuroinflammatory and neurological disorders such as Alzheimer's and Parkinson's diseases. Structurally, Acot enzymes adopt a circularised trimeric arrangement with each monomer containing an N‐ and a C‐terminal hotdog domain. Acot7 spontaneously forms amyloid fibrils in vitro under physiological conditions. The resultant amyloid fibrillar structures were characterised by dye‐binding fluorescence assays, far‐UV circular dichroism spectroscopy, transmission electron microscopy and X‐ray fibre diffraction. Acot7 has an unusual mechanism of aggregation with no lag phase. The initial phase (~ 18 h) of aggregation involves conformational rearrangement within the oligomers to form species of enhanced β‐sheet character. The subsequent loss of α‐helical structure is accompanied by large‐scale amyloid fibril formation. The crystal structure of Acot7 revealed an unexpected arrangement of the two domains within the circularised trimeric structure, which is the basis for a proposed mechanism of amyloid fibril formation involving domain swapping during the initial phase of aggregation. Acot7 formed fibrils in the presence of its substrate arachidonoyl‐CoA and its inhibitors and maintained its enzyme activity during fibril assembly. It is proposed that the Acot7 fibrillar form acts as functional amyloid. [ABSTRACT FROM AUTHOR]

This article presents an upgrade of the D+ software [Ginsburg et al. (2019). J. Appl. Cryst.52, 219–242], expanding its hierarchical solution X‐ray scattering modeling capabilities for fiber diffraction and single crystallographic orientations. This upgrade was carried out using the reciprocal grid algorithm [Ginsburg et al. (2016). J. Chem. Inf. Model.56, 1518–1527], providing D+ its computational strength. Furthermore, the extensive modifications made to the Python API of D+ are described, broadening the X‐ray analysis performed with D+ to account for the effects of the instrument‐resolution function and polydispersity. In addition, structure‐factor and radial‐distribution‐function modules were added, taking into account the effects of thermal fluctuations and intermolecular interactions. Finally, numerical examples demonstrate the usage and potential of the added features. [ABSTRACT FROM AUTHOR]

Controlling particle dispersity is of huge importance for practical applications in nanoscience and technology. The analysis of small‐angle scattering of X‐rays and neutrons for strongly polydisperse particulate systems is considered from the point of view of describing the type of size distribution function without applying classical regularization approaches. This article presents the development of a method for determining the polydispersity parameters of nanoobjects, based on the analysis of the ratio of various moments of the size distribution function, which are proportional to different invariants of the scattering curve. The use of the unified exponential/power‐law approximation to describe small‐angle scattering data makes it possible to determine the type of distribution, the average size and the spread. The possibilities of the method were tested for several hydrosols of metallic nanoparticles. [ABSTRACT FROM AUTHOR]

This work reports that the rheology of ideally monodisperse lambda (λ) phage DNA solutions is extremely sensitive to the applied strain in dynamic oscillatory experiments. λ DNA exhibits nonlinearity at strains far smaller than what is observed in conventional synthetic polymers. However, it is found that polydisperse calf thymus DNA does not exhibit the extreme strain sensitivity. By mixing samples of monodisperse λ DNA with the polydisperse calf thymus DNA, we correlate the molecular weight distribution (or polydispersity) to the onset of nonlinear viscoelasticity. We demonstrate that the strain sensitivity weakens as the polydispersity index increases. This is the first work correlating the inception of nonlinear viscoelasticity in entangled polymer system such as lambda DNA solution to the polydispersity of the samples. The experimental data suggests that ideally monodisperse polymer systems are very sensitive to the applied strain and have a very early transition to the nonlinear regime. We conclude that nominally monodisperse synthetic polymers are not sufficiently monodispersed to exhibit the early onset. [ABSTRACT FROM AUTHOR]

Featured Application: A methodology was developed for the efficient nanoencapsulation of non-water-soluble biomolecules, such as the flavonoid quercetin, through the nanoprecipitation technique and using Eudragit® polymers for pharmaceutical use. These data are intended to provide an approach for the future administration of bioactive compounds for pharmaceutical uses. Eudragit® polymers have proven their potential as a means to control the release of aqueous insoluble drugs in various delivery systems as polymer nanoparticles (PNPs). The size (S) and polydispersity index (PDI) of PNPs are crucial factors for their interaction with biological systems from a pharmaceutical standpoint. This study aimed to determine the impact of the volumes of the organic phase (OP) and aqueous phase (AP), as well as the polymer amount (PA), on the size and PDI of PNPs prepared using the nanoprecipitation method for encapsulating quercetin (Qr). The study also evaluated the toxic effects of PNPs on human erythrocytes. The PNPs were prepared using preformed polymers derived from methacrylic acid and polyvinyl alcohol (PVA) as a surfactant. The nanoprecipitation technique enabled the production of particles smaller than 200 nm with a PDI lower than 0.2, and the study established the significant impact (p < 0.05) of the three variables related to the polymers and solvents. The selected PNPs contained 5 mg of Qr and 50 mg of Eudragit polymers (1:10 w/w Eudragit® EPO, E100, L100, and Eudragit L100-55) and diverse concentrations of PVA. The study found that including PVA in the AP increased the Qr encapsulation by up to 98%. The hemolytic potential of Eudragit® PNPs and Qr was assessed in human erythrocytes, with no significant cytotoxic activity observed (p < 0.001) compared with the control. In conclusion, via the nanoprecipitation technique, preparing PNPs with defined and homogeneous S to entrap the flavonol Qr efficiently is possible. [ABSTRACT FROM AUTHOR]

Polymer informatics is an emerging discipline that has benefited from the strong development that data science has experienced over the last decade. Machine learning methods are useful to infer QSPR (Quantitative Structure-Property Relationships) models that allow predicting mechanical properties related to the industrial profile of polymeric materials based on their structural repeating units (SRUs). Nonetheless, the chemical structure of the SRU is only one of the many factors that affects the industrial usefulness of a polymer. Other equally relevant factors are polymer molecular weight, molecular weight distribution, and production method, which are related to the inherent polydispersity of this kind of material. For this reason, the computational characterization used for the building of QSPR models for predicting mechanical properties should consider these main factors. The aim of this paper is to highlight recent advances in data science to address the inclusion of polydispersity information of polymeric materials in QSPR modeling. We present two dimensions of discussion: data representation and algorithmic issues. In the first one, we examine how different strategies can be applied to include polydispersity data in the molecular descriptors that characterize the polymers. We explain two data representation approaches designed by our group, named as trivalued and multivalued molecular descriptors. In the second dimension, we discuss algorithms proposed to deal with these new molecular descriptor representations during the construction of the QSPR models. Thus, we present here a comprehensible and integral methodology to address the challenges that polydispersity generates in the QSPR modeling of mechanical properties of polymers.

We present an algorithm to predict the linear relaxation spectra for linear polymers of fully general and arbitrary polydispersity. As is common in the tube theory descriptions of linear polymers, we assume that the stress relaxation is affected by both the constraint release and tube escape modes, but unlike most existing descriptions we consider how these two modes of relaxation affect each other. We argue that the proper description for relaxation in an arbitrary blend of linear polymers requires consideration of multiple embedded tubes affecting the different relaxation pathways; we propose a novel but minimal description involving five embedded tubes. Building on prior work for binary blends, we derive the scaling level descriptions of the relaxation pathways. We use a large number of existing experimental results on the stress and dielectric relaxations to validate our model, ensuring we explore a very broad range of parameter space. [ABSTRACT FROM AUTHOR]

In this work, we examine the steady shear rheology of semidilute polydisperse bubble suspensions to elucidate the role of polydispersity on the viscosity of these systems. We prove theoretically that the effect of polydispersity on suspension viscosity becomes apparent only if the bubble size distribution is bimodal, with very small and very large bubbles having similar volume fractions. In any other case, we can consider the polydisperse suspension as monodisperse, with the average bubble diameter equal to the De Brouckere mean diameter (d 43). To confirm the theoretical results, we carried out steady shear rheological tests. Our measurements revealed an unexpected double power-law decay of the suspension relative viscosity at average capillary numbers between 0.01 and 1. To investigate this behavior further, we visualized the produced bubble suspensions under shear. The visualization experiments revealed that bubbles started forming clusters and threads at an average capillary number around 0.01, where we observed the first decay of viscosity. Clustering and alignment have been associated with shear-thinning behavior in particle suspensions. We believe that the same holds for bubble suspensions, where bubble clusters and threads align with the imposed shear flow, reducing the streamline distortions and, in turn, resulting in a decrease in the suspension viscosity. Consequently, we can attribute the first decay of the relative viscosity to the formation of bubble clusters and threads, proving that the novel shear-thinning behavior we observed is due to a combination of bubble clustering and deformation. [ABSTRACT FROM AUTHOR]

Paraffin waxes are a promising material for heat storage with high energy density. Their low thermal conductivity, which limits the speed of charging and discharging in heat buffers, was previously shown to be improved by adding graphene nanofillers. In the present study, using molecular dynamics simulations, the segregation by molecular weight of polydisperse paraffin near graphene flakes is investigated. In liquid bidisperse paraffin composed of decane and triacontane, an aligned layer containing mainly triacontane was observed next to the graphene. Upon slow cooling, the wax crystallised into distinct layers parallel to the graphene sheet, with much stronger segregation by molecular weight than in the crystallised bidisperse wax without graphene. For polydisperse wax, the segregation effect was much less pronounced. The molten paraffin had a somewhat higher concentration of the longest chains in the first layers next to the graphene, but during crystallisation, the molecular weight segregation was only slightly increased. Measurements of crystallinity using an alternative version of the method developed by Yamamoto showed that the layers of wax were highly aligned parallel to the graphene, both in the solid state with all wax crystallised and in the liquid state with one layer of aligned wax above and below the graphene. Thermal conductivity was increased in planes parallel to the graphene flakes. The strong segregation of chain lengths in the bidisperse wax resulted in clear differences in thermal conductivity in the segregated regions. The less segregated polydisperse wax showed less variation in thermal conductivity. [ABSTRACT FROM AUTHOR]

Methods of fractional analysis of powders based on heat-resistant nickel alloys, electron microscopy and elemental analysis, study of bulk density of powder fractions, as well as approaches of mathematical modeling of packing density were applied in the work. Spherical powders based on heat-resistant nickel alloys of two different fractions: 50...200 μm and ≤63 μm were studied. The morphology of the surface of spherical particles of powders based on heat-resistant nickel alloys of different fractional composition, as well as their granulometric characteristics, was researched. It is shown that as the fractional composition of powder fractions decreases, their homogeneity and bulk density increase. At the same time, it was established that more finely dispersed fractions are characterized by worse fluidity indicators. According to the simulation results, the optimal fractional composition of the powder for filling the previously specified volume was determined. It is shown that as the size of the investigated particles decreases, their packing density increases.

Size and zeta potential are critical physicochemical properties of nanoparticles (NPs), influencing their biological activity and safety profile. These are essential for further industrial upscale and clinical success. However, the characterization of polydisperse, non-spherical NPs is a challenge for traditional characterization techniques (ex., dynamic light scattering (DLS)). In this paper, superparamagnetic iron oxide nanoparticles (SPIONs) were coated with polyvinyl alcohol (PVAL) exhibiting different terminal groups at their surface, either hydroxyl (OH), carboxyl (COOH) or amino (NH2) end groups. Size, zeta potential and concentration were characterized by orthogonal methods, namely, batch DLS, nanoparticle tracking analysis (NTA), tunable resistive pulse sensing (TRPS), transmission electron microscopy (TEM), asymmetric flow field flow fractionation (AF4) coupled to multi-angle light scattering (MALS), UV–Visible and online DLS. Finally, coated SPIONs were incubated with albumin, and size changes were monitored by AF4-MALS-UV-DLS. NTA showed the biggest mean sizes, even though DLS PVAL-COOH SPION graphs presented aggregates in the micrometer range. TRPS detected more NPs in suspension than NTA. Finally, AF4-MALS-UV-DLS could successfully resolve the different sizes of the coated SPION suspensions. The results highlight the importance of combining techniques with different principles for NPs characterization. The advantages and limitations of each method are discussed here. [ABSTRACT FROM AUTHOR]

The physical properties of polymeric materials, which are mixtures of various molecules, are determined by the sum of their contributions. Industrially important isotactic polypropylene (iPP), which is produced using heterogeneous Ziegler–Natta catalysts, shows broader distributions of molecular weight and stereoregularity because of the multisite nature, compared to molecular catalysts. However, systematic studies on the effects of these distributions on physical properties are lacking, especially for variations in stereoregularity. In this study, polypropylene (PP) additives with various molecular weights and stereoregularities (and their distributions) are added to an iPP matrix to clarify the effects of low‐concentration components on the overall physical properties. The results indicate the importance of incorporating the PP additives into the crystal structure of the iPP matrix. [ABSTRACT FROM AUTHOR]

Discrete Network (DN) models are a useful tool to investigate structure–property relationships in rubbery networks such as elastomers and hydrogels. In a DN model, polymer chains are represented by entropic springs connected at crosslinking points, and the partitioning of stretches among the chains is dictated by the condition of mechanical equilibrium at each crosslink. A key feature of these models is that springs have a zero natural length, and are therefore pre-stretched in the reference configuration. However, the role of chain pre-stretch distribution on the emerging mechanical properties has often been overlooked. In this work we investigate the elastic properties of DNs where the average chain pre-stretch, chain density and chain length distribution can be prescribed independently via a novel network generation algorithm. We show that increasing the average pre-stretch increases the network stiffness and decreases its extensibility limit. We also compare predictions of semi-analytical micromechanical models of rubber elasticity to DN predictions taken as reference. Deviations between analytical model and DN predictions are attributed to the combination of two factors: the loss of affinity at large strain and the initial pre-stretch distribution, which is not taken into account in analytical estimates. DN simulations further show that the assumption of one-to-one mapping between chain stretch and chain orientation on which microsphere models rely is not satisfied. [ABSTRACT FROM AUTHOR]

We study the liquid phase behavior of ternary mixtures of monodisperse hard spheres in solution. The interactions are modeled in terms of the second virial coefficient and can be additive hard sphere (HS) or non-additive hard sphere (NAHS) interactions. We give the set of equations that defines the phase diagram for mixtures of three components. We calculate the theoretical liquid–liquid phase separation boundary for two-phase separation (the binodal) and, if applicable, the three-phase boundary, as well as the plait points and the spinodal. The sizes of the three components are fixed. The first component (A) is the smallest one, the second component (B) is four times the size of the smallest component, and the third (C) component is three times the size of the smallest one. The interaction between the first two components is fixed, and this AB sub-mixture shows phase separation. The interactions of component C with the other two components are varied. Component C can be compatible or incompatible with components A and B. Depending on the compatibility of the components, the phase diagram is altered. The addition of the third component has an influence on the phase boundary, plait points, stability region, fractionation, and volume ratio between the different phases. When all sub-mixtures (AB, AC, and BC) show phase separation, a three-phase system becomes possible when the incompatibility among all components is high enough. The position and size of the three-phase region is dependent on the interactions between the different sub-mixtures. We study the fractionation off all components depending on specific parent concentrations.

Abstract Polyelectrolyte complexes (PECs) as drug delivery systems are widely explored since they are easily obtained by coacervation and biopolymers can be associated. However, particle distribution is a challenging critical parameter that has been infrequently focused. This work evaluated the effect of NaCl concentration on the physicochemical properties of PECs based on chitosan and hypromellose loaded with methotrexate. The particle size, zeta potential and polydispersity index (PdI) were determined by DLS, besides of drug entrapment efficiency (EE) and in vitro drug release profile determination. Particle size decreased while NaCl concentration rised, achieving a narrower size distribution of (345±79 nm) and PdI (0.285±0.067) with 200 mmol/L NaCl. The higher the NaCl concentration, the lower the zeta potential at acid pH. The EE was kept similar ((28.2±4.5) %) from 0 to 300 mmol/L NaCl, while 400 mmol/L NaCl impaired the drug entrapment. The addition of (200 and 300) mmol/L NaCl did not affect the drug release profile, but it was faster with (100 or 400) mmol/L. In conclusion, the addition of 200 mmol/L NaCl reduced particle size and PdI with no changes in the EE and drug release. Therefore, the ionic strength plays an important role on PECs development.

A multiscale simulation method is used to calculate the rheological properties of entangled Nylon 6 melts, including the stress relaxation modulus, storage and loss moduli, and the melt viscosity. The three‐level multiscale approach includes all‐atom, coarse‐grained and slip‐spring models, each operating at different levels of resolution and encompassing a wide range of length scales and over nine orders of magnitude in time. These models are unified by matching the polymer chain structure and dynamics as well as the stress relaxation, and together predict the rheological master curves at various temperatures using time–temperature superposition. The calculated viscosity agrees reasonably with experiment. The effect of polydispersity on rheology is also studied by simulating a polydisperse melt with chain lengths follow the Schulz‐Zimm distribution. Under the same weight‐average molecular weight, the polydisperse melt shows faster stress relaxation and lower viscosity compared to the monodisperse melt. For polymers that undergo rapid degradation at elevated temperatures, such as Nylon, the proposed approach offers a useful means to investigate rheology over a wide range of conditions. Importantly, the approach is fully predictive in that calculations of rheology are generated without relying on experimental information, and it therefore offers potential for design of polymeric materials on the basis of purely molecular models. [ABSTRACT FROM AUTHOR]

A great progress has been made over the last decades in studying concentration scaling on rheometric properties of monodisperse polymer solutions. However, the effects of polydisperse polymer solutions on such a concentration scaling remain elusive. In this work, rheometric properties of industrially relevant polydisperse and high molecular weight polyacrylamide (PAAm) aqueous solution have been studied. The results show a concentration scaling of the characteristic relaxation time, the plateau modulus and the zero-shear viscosity across a concentration range from 10c* to 250c*. The time-concentration superposition principle is validated and extended in the data analysis of the terminal dynamic regime. The concentration scaling exponent of their shifting factors is significantly smaller than the results of monodisperse polymer solutions in good and θ solvents reported in the literature. The steady shear viscosity and shear stress of 18M PAAm aqueous solutions with relatively lower concentration (≤35c*) could also be superimposed into a master curve with the shear-thinning exponent of 0.73±0.03 and 0.27±0.03, respectively, over a wide range of shear rates in about six orders of magnitudes. However, for 18M PAAm aqueous solutions with higher concentration (≥48c*) in an intermediate shear thinning regime, the scaling exponent shows a pronounced concentration dependence. The shear thinning exponent of steady shear viscosity varies from 0.73 to 0.57 as concentration is increased, and then increases from 0.57 to 0.90 from sufficiently high shear rate. Further increasing shear rate, the shear-thinning exponent of 18M PAAm aqueous solutions at all concentrations converges to the lower bounded value observed in the relatively less concentrated (≤35c*) 18M PAAm aqueous solutions, i.e., 0.73±0.02 for shear viscosity and 0.27±0.02 for steady shear stress, respectively. It reveals that the concentration effects of polydisperse polymer solutions could be greatly reduced by the dynamic "molecular individualism" in strong shear flow. [ABSTRACT FROM AUTHOR]

Acoustic droplet vaporization is the ultrasound-mediated phase change of liquid droplets into gas microbubbles. Following the phase change, oxygen diffuses from the surrounding fluid into the microbubble. An in vitro model was used to study the effects of droplet diameter, the presence of an ultrasound contrast agent, ultrasound duty cycle, and droplet concentration on the magnitude of oxygen scavenging in oxygenated deionized water. Perfluoropentane droplets were manufactured through a microfluidic approach at nominal diameters of 1, 3, 5, 7, 9, and 12 µm and studied at concentrations varying from 5.1 × 10−5 to 6.3 × 10−3 mL/mL. Droplets were exposed to an ultrasound transduced by an EkoSonicTM catheter (2.35 MHz, 47 W, and duty cycles of 1.70%, 2.34%, or 3.79%). Oxygen scavenging and the total volume of perfluoropentane that phase-transitioned increased with droplet concentration. The ADV transition efficiency decreased with increasing droplet concentration. The increasing duty cycle resulted in statistically significant increases in oxygen scavenging for 1, 3, 5, and 7 µm droplets, although the increase was smaller than when the droplet diameter or concentration were increased. Under the ultrasound conditions tested, droplet diameter and concentration had the greatest impact on the amount of ADV and subsequent oxygen scavenging occurred, which should be considered when using ADV-mediated oxygen scavenging in therapeutic ultrasounds. [ABSTRACT FROM AUTHOR]

We derive exact results for correlations in the displacement fields { δ r } ≡ { δ r μ = x , y } in near-crystalline athermal systems in two dimensions. We analyze the displacement correlations produced by different types of microscopic disorder, and show that disorder at the microscopic scale gives rise to long-range correlations with a dependence on the system size L given by ⟨ δ r μ δ r ν ⟩ ∼ c μ ν (r / L , θ) . In addition, we show that polydispersity in the constituent particle sizes and random bond disorder give rise to a logarithmic system size scaling, with c μ ν (ρ , θ) ∼ const μ ν - a μ ν (θ) log ρ + b μ ν (θ) ρ 2 for ρ (= r / L) → 0 . This scaling is different for the case of displacement correlations produced by random external forces at each vertex of the network, given by c μ ν f (ρ , θ) ∼ const μ ν f - (a μ ν f (θ) + b μ ν f (θ) log ρ) ρ 2 . Additionally, we find that correlations produced by polydispersity and the correlations produced by disorder in bond stiffness differ in their symmetry properties. Finally, we also predict the displacement correlations for a model of polydispersed soft disks subject to external pinning forces, that involve two different types of microscopic disorder. We verify our theoretical predictions using numerical simulations of polydispersed soft disks with random spring contacts in two dimensions. [ABSTRACT FROM AUTHOR]

Sea ice in the marginal ice zone (MIZ) consists of relatively small floes with a wide size span. In response to oceanic and atmospheric forcing, it behaves as an approximately two-dimensional, highly polydisperse granular material. The established viscous-plastic rheologies used in continuum sea ice models are not suitable for the MIZ; the collisional rheology, in which sea ice is treated as a granular gas, captures only one aspect of the granular behaviour, typical for a narrow range of conditions when dynamics is dominated by binary floe collisions. This paper reviews rheology models and concepts from research on granular materials relevant for MIZ dynamics (average stress as a result of 'microscopic' interactions of grains; μ(I) and collisional rheologies). Idealized discrete-element simulations are used to illustrate granular effects and strong influence of the floe size distribution on strain–stress relationships in sheared sea ice, demonstrating the need for an MIZ rheology model capturing the whole range of 'regimes', from quasi-static/dense flow in the inner MIZ to the inertial flow in the outer MIZ. This article is part of the theme issue 'Theory, modelling and observations of marginal ice zone dynamics: multidisciplinary perspectives and outlooks'. [ABSTRACT FROM AUTHOR]

The ability to separate enzymes, or cells or viruses, from a mixture is important and can be realized by the incorporation of the mixture into a macromolecular solution. This incorporation may lead to a spontaneous phase separation, with one phase containing the majority of one of the species of interest. Inspired by this phenomenon, we studied the theoretical phase behavior of a model system composed of an asymmetric binary mixture of hard spheres, of which the smaller component was monodisperse and the larger component was polydisperse. The interactions were modeled in terms of the second virial coefficient and could be additive hard sphere (HS) or nonadditive hard sphere (NAHS) interactions. The polydisperse component was subdivided into two subcomponents and had an average size ten or three times the size of the monodisperse component. We gave the set of equations that defined the phase diagram for mixtures with more than two components in a solvent. We calculated the theoretical liquid–liquid phase separation boundary for the two-phase separation (the binodal) and three-phase separation, the plait point, and the spinodal. We varied the distribution of the polydisperse component in skewness and polydispersity, and we varied the nonadditivity between the subcomponents as well as between the main components. We compared the phase behavior of the polydisperse mixtures with binary monodisperse mixtures for the same average size and binary monodisperse mixtures for the same effective interaction. We found that when the compatibility between the polydisperse subcomponents decreased, the three-phase separation became possible. The shape and position of the phase boundary was dependent on the nonadditivity between the subcomponents as well as their size distribution. We conclude that it is the phase enriched in the polydisperse component that demixes into an additional phase when the incompatibility between the subcomponents increases. [ABSTRACT FROM AUTHOR]

The dynamics of two model glass‐formers (three‐dimensional [3D] oligomer melt and two‐dimensional [2D] polydisperse colloidal system) are analyzed using MD simulations. It is found that the standard deviation of the shear modulus shows a striking peak near the glass transition Tg, which is explained with a quantitative theory. The simulation data well below Tg suggest that static multi‐point correlations of local stress are long‐range. The obtained correlation functions of time‐dependent and wavevector‐resolved stress for the 2D system are in excellent agreement with the developed theory indicating that the frozen‐in stress inhomogeneities in the glassy state are correlated according to a power law. [ABSTRACT FROM AUTHOR]

This study unveils the "green" metal-organic framework (MOF) structuring mechanism by decoding proton transfer in water during ZIF-8 synthesis. Combining in situ small- to wide-angle X-ray scattering, multiscale simulations, and quantum calculations, we reveal that the ZIF-8 early-stage nucleation and crystallization process in aqueous solution unfolds in three distinct stages. In stage I, imidazole ligands replace water in zinc-water cages, triggering an "acidity flip" that promotes proton transfer. This leads to the assembly of structures from single zinc ions to 3D amorphous cluster nuclei. In stage II, amorphous nuclei undergo a critical transformation, evolving into crystalline nuclei and subsequently forming mesoscale-ordered structures and crystallites. The process proceeds until the amorphous precursors are completely consumed, with the transformation kinetics governed by an energy barrier that determines the rate-limiting step. In stage III, stable crystallite nanoparticles form in solution, characterized by a temperature-dependent thermal equilibrium of molecular interactions at the crystal-solution interface. Beyond these core advancements, we explore the influence of encapsulated pepsin and nonencapsulated lysozyme on ZIF-8 formation, finding that their amino acid proton transfer capacity and concentration influence the resulting biomolecule-MOF composite's shape and encapsulation efficiency. The findings contribute to understanding the molecular mechanisms behind biomimetic mineralization and have potential implications for engineering proteins within amorphous MOF nuclei as protein embryo growth sites.

Abstract Flexible conducting materials are required for the design and fabrication of a host of applications involving flexible electronic items. A flexible substrate like paper or polymer is generally employed for deposition of metal by a variety of processes. Among many physical properties, the roughness of the substrate is considered an important parameter, although, its exact role on effective conductivity of the coating is not known. Nor any study has been carried out to understand how the three‐dimensional porous structure of the substrate surface affects the microscopic packing of grains that constitute the metal coating. With the objective of elucidating the effect of substrate roughness on the conductivity of paper electrodes, we have used six different commonly available papers for vacuum coating with copper. For a smooth substrate, the grains that constitute the coating appear spherical, however, turns ellipsoidal as the substrate roughness and heterogeneity is increased; ellipsoidal grains result in higher packing efficiency leading to higher conductivity. We have also presented a model to relate the packing efficiency to the asphericity, polydispersity, and skewness of size distribution of grains.

Eudragit® polymers have proven their potential as a means to control the release of aqueous insoluble drugs in various delivery systems as polymer nanoparticles (PNPs). The size (S) and polydispersity index (PDI) of PNPs are crucial factors for their interaction with biological systems from a pharmaceutical standpoint. This study aimed to determine the impact of the volumes of the organic phase (OP) and aqueous phase (AP), as well as the polymer amount (PA), on the size and PDI of PNPs prepared using the nanoprecipitation method for encapsulating quercetin (Qr). The study also evaluated the toxic effects of PNPs on human erythrocytes. The PNPs were prepared using preformed polymers derived from methacrylic acid and polyvinyl alcohol (PVA) as a surfactant. The nanoprecipitation technique enabled the production of particles smaller than 200 nm with a PDI lower than 0.2, and the study established the significant impact (p < 0.05) of the three variables related to the polymers and solvents. The selected PNPs contained 5 mg of Qr and 50 mg of Eudragit polymers (1:10 w/w Eudragit® EPO, E100, L100, and Eudragit L100-55) and diverse concentrations of PVA. The study found that including PVA in the AP increased the Qr encapsulation by up to 98%. The hemolytic potential of Eudragit® PNPs and Qr was assessed in human erythrocytes, with no significant cytotoxic activity observed (p < 0.001) compared with the control. In conclusion, via the nanoprecipitation technique, preparing PNPs with defined and homogeneous S to entrap the flavonol Qr efficiently is possible.

A general method to invert parameter distributions of a polydisperse system using data acquired from a small-angle scattering (SAS) experiment is presented. The forward problem, i.e. calculating the scattering intensity given the distributions of any causal parameters of a theoretical model, is generalized as a multi-linear map, characterized by a high-dimensional Green tensor that represents the complete scattering physics. The inverse problem, i.e. finding the maximum-likelihood estimation of the parameter distributions (in free form) given the scattering intensity (either a curve or an image) acquired from an experiment, is formulated as a constrained nonlinear programming (NLP) problem. This NLP problem is solved with high accuracy and efficiency via several theoretical and computational enhancements, such as an automatic data scaling for accuracy preservation and GPU acceleration for large-scale multiparameter systems. Six numerical examples are presented, including both synthetic tests and solutions to real neutron and X-ray data sets, where the method is compared with several existing methods in terms of their generality, accuracy and computational cost. These examples show that SAS inversion is subject to a high degree of non-uniqueness of solution or structural ambiguity. With an ultra-high accuracy, the method can yield a series of near-optimal solutions that fit data to different acceptable levels. [ABSTRACT FROM AUTHOR]