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This paper reports the study of hollow microballoon-filled epoxy composites also known as syntactic foams with various volume fractions of microballoons. Different mechanical and thermomechanical investigations were carried out to study the elastic and viscoelastic behavior of these foams. The density, void content, and microstructure of these materials were also studied for better characterization. In addition to the experimental testing, a representative 3D model of these syntactic foams was developed to further investigate their elastic behavior. The results indicate that changes in the volume percentage of the microballoons had a substantial impact on the elastic and viscoelastic behavior of these foams. These results will help in designing and optimizing custom-tailored syntactic foams for different engineering applications.

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Computational approaches could provide a viable and cost-effective alternative to expensive experiments for accurately evaluating the nonlinear constitutive behavior of cementitious nanocomposite materials. In the present study, the mechanical properties of cement paste reinforced with multi-wall carbon nanotubes (MWCNTs) are examined experimentally and numerically. A multiscale computational approach is adopted in order to verify the experimental results. For this scope, a random sequential adsorption algorithm was developed to generate non-overlapping matrix-inclusion three-dimensional (3D) representative volume elements (RVEs), considering the inclusions as straight elements. Nonlinear finite element analyses (FEA) were performed, and the homogenized elastic and inelastic mechanical properties were computed. The use of a multiscale computational approach to accurately evaluate the nonlinear constitutive behavior of cementitious materials has rarely been explored before. For this purpose, the RVEs were analyzed both in pure tension and compression. Young's modulus as well compressive and tensile strength results were compared and eventually matched the experimental values. Moreover, the effect of MWCNTs on the nonlinear stress-strain behavior of reinforced cement paste was noted. Subsequently, three-point bending tests were conducted, and the stress-strain behavior was verified with FEA in the macro scale. The numerical modeling reveals a positive correlation between the concentration of MWCNTs and improved mechanical properties, assuming ideal dispersion. However, it also highlights the impact of practical limitations, such as imperfect dispersion and potential defects, which can deteriorate the mechanical properties that are observed in the experimental results. Among the different cases studied, that with a 0.1 wt% MWCNTs/CP composite demonstrated the closest agreement between the numerical model and the experimental measurements. The numerical model achieved the best accuracy in estimating the Young's modulus (underestimation of 13%), compressive strength (overestimation of 1%), and tensile strength (underestimation of 6%) compared to other cases. Overall, these numerical findings contribute significantly to understanding the mechanical behavior of the nanocomposite material and offer valuable guidance for optimizing cement-based composites for engineering applications.

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The orientation of antibodies, employed as capture molecules on biosensors, determines biorecognition efficiency and bioassay performance. In a previous publication we demonstrated for antibodies attached covalently to silicon that an increase in their surface amount Γ, evaluated with ellipsometry, induces changes in their orientation, which is traced directly using Time-of-Flight Secondary Ion Mass Spectroscopy combined with Principal Component Analysis. Here, we extend the above studies to antibodies adsorbed physically on a 3-aminopropyltriethoxysilane (APTES) monolayer. Antibodies physisorbed on APTES (0 ≤ Γ ≤ 3.5 mg/m2) reveal the Γ ranges for flat-on, side-on, and vertical orientation consistent with random molecular packing. The relation between orientation and Γ is juxtaposed for silicon functionalized with APTES, APTES modified with glutaraldehyde (APTES/GA) and N-hydroxysuccinimide-silane (NHS-silane). Antibody reorientation occurs at lower Γ values when physisorption (APTES) is involved rather than chemisorption (APTES/GA, NHS-silane). At high Γ values, comparable proportions of molecules adapting head-on and tail-on vertical alignment are concluded for APTES and the NHS-silane monolayer, and they are related to intermolecular dipole-dipole interactions. Intermolecular forces seem to be less decisive than covalent binding for antibodies on the APTES/GA surface, with dominant head-on orientation. Independently, the impact of glutaraldehyde activation of APTES on vertical orientation is confirmed by separate TOF-SIMS measurements.

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Random Sequential Adsorption (RSA) is one of the most efficient theoretical models used to investigate adsorption of macromolecules and particles, with a long-standing tradition in the field of colloid and interface science. In the first part of this paper, we demonstrate how the RSA model can be applied to interpret the experimental data and extract information about the density of the adsorption monolayer, the kinetics of its growth, and microstructural properties such as pair-correlation function and monolayer roughness. We briefly summarized the most important generalizations of the RSA model for monolayers and reviewed its extensions considering, e.g., various particle shapes, the introduction of electrostatic interaction, or adsorption on non-uniform substrates. We thoroughly scrutinized the extended RSA model developed for bilayer and multilayer formation. We collected the mean saturated packing fractions of various two- and three-dimensional objects and provided the most accurate result for two-dimensional disk packing. In the second part of this paper, we summarize various numerical algorithms and techniques that allow one to effectively implement RSA algorithms. We describe efficient methods for detecting intersections of various shapes and techniques enabling generation of strictly saturated RSA packings built of a wide range of different shapes. We hinted at how an inherently sequential RSA scheme can be parallelized. Finally, we critically discuss the limitations of the model and possible directions for future studies.

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Although the polygonal shape of epithelial cells has been drawing the attention of scientists for several centuries, only a decade and a half ago it was demonstrated that distributions of polygon types (DOPTs) are similar in proliferative epithelia of many different plant and animal species. In this study, we show that hyper-proliferation of cancer cells disrupts this universal paradigm and results in randomly organized epithelial structures. Examining non-synchronized and synchronized HeLa cervix cells, we suppose that the spread of cell sizes is the main parameter controlling the DOPT in the cancer cell monolayers. To test this hypothesis, we develop a theory of morphologically similar random polygonal packings. By analysing differences between tumoural and normal epithelial cell monolayers, we conclude that the latter have more ordered structures because of their lower proliferation rates and, consequently, more effective relaxation of mechanical stress associated with cell division and growth. To explain the structural features of normal proliferative epithelium, we take into account the spread of cell sizes in the monolayer. The proposed theory also rationalizes some highly ordered unconventional post-mitotic epithelia.

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The myelin sheath-a multi-double-bilayer membrane wrapped around axons-is an essential part of the nervous system which enables rapid signal conduction. Damage of this complex membrane system results in demyelinating diseases such as multiple sclerosis (MS). The process in which myelin is generated in vivo is called myelination. In our study, we investigated the adhesion process of large unilamellar vesicles with a supported membrane bilayer that was coated with myelin basic protein (MBP) using time-resolved neutron reflectometry. Our aim was to mimic and to study the myelination process of membrane systems having either a lipid-composition resembling that of native myelin or that of the standard animal model for experimental autoimmune encephalomyelitis (EAE) which represents MS-like conditions. We were able to measure the kinetics of the partial formation of a double bilayer in those systems and to characterize the scattering length density profiles of the initial and final states of the membrane. The kinetics could be modeled using a random sequential adsorption simulation. By using a free energy minimization method, we were able to calculate the shape of the adhered vesicles and to determine the adhesion energy per MBP. For the native membrane the resulting adhesion energy per MBP is larger than that of the EAE modified membrane type. Our observations might help in understanding myelination and especially remyelination-a process in which damaged myelin is repaired-which is a promising candidate for treatment of the still mostly incurable demyelinating diseases such as MS.

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We revisit the model of the ballistic deposition studied in [5] and prove several combinatorial properties of the random tree structure formed by the underlying stochastic process. Our results include limit theorems for the number of roots and the empirical average of the distance between two successive roots of the underlying tree-like structure as well as certain intricate moments calculations.

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Virus removal by membrane bioreactors depends on virus-membrane and virus-foulant interactions. The adsorption of human adenovirus 2 (HAdV-2) on polyvinylidene fluoride (PVDF) membrane and a major membrane foulant, extracellular polymeric substances (EPS), were measured in a quartz crystal microbalance. In 3-100mM CaCl2 solutions, irreversible adsorption of HAdV-2 was observed on both pristine and EPS-fouled PVDF surfaces. The HAdV-2 adsorption kinetics was successfully fitted with the random sequential adsorption (RSA) model. The applicability of the RSA model for HAdV-2 adsorption is confirmed by comparing the two fitting parameters, adsorption rate constant k(a) and area occupied by each adsorbed HAdV-2 particle a, with experimentally measured parameters. A linear correlation between the fitting parameter k(a) and the measured attachment efficiency was found, suggesting that the RSA model correctly describes the interaction forces dominating the HAdV-2 adsorption. By comparing the fitting parameter d(ads) with the hydrodynamic diameter of HAdV-2, we conclude that virus-virus and virus-surface interactions determine the area occupied by each adsorbed HAdV-2 particle, and thus influence the adsorption capacity. These results provide insights into virus retention and will benefit improving virus removal in membrane filtration.

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The biggest problem when analyzing the brain is that its synaptic connections are extremely complex. Generally, the billions of neurons making up the brain exchange information through two types of highly specialized structures: chemical synapses (the vast majority) and so-called gap junctions (a substrate of one class of electrical synapse). Here we are interested in exploring the three-dimensional spatial distribution of chemical synapses in the cerebral cortex. Recent research has showed that the three-dimensional spatial distribution of synapses in layer III of the neocortex can be modeled by a random sequential adsorption (RSA) point process, i.e., synapses are distributed in space almost randomly, with the only constraint that they cannot overlap. In this study we hypothesize that RSA processes can also explain the distribution of synapses in all cortical layers. We also investigate whether there are differences in both the synaptic density and spatial distribution of synapses between layers. Using combined focused ion beam milling and scanning electron microscopy (FIB/SEM), we obtained three-dimensional samples from the six layers of the rat somatosensory cortex and identified and reconstructed the synaptic junctions. A total volume of tissue of approximately 4500µm(3) and around 4000 synapses from three different animals were analyzed. Different samples, layers and/or animals were aggregated and compared using RSA replicated spatial point processes. The results showed no significant differences in the synaptic distribution across the different rats used in the study. We found that RSA processes described the spatial distribution of synapses in all samples of each layer. We also found that the synaptic distribution in layers II to VI conforms to a common underlying RSA process with different densities per layer. Interestingly, the results showed that synapses in layer I had a slightly different spatial distribution from the other layers.

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In this paper we attempt to understand monolayer formation of spherical particles on a solid surface immersed in a suspension and driven by electrostatic interaction force. The study focuses on the theoretical aspects of the particle adsorption and modeling work based on the random sequential adsorption (RSA) approach is done in order to describe the particle adsorption kinetics and the saturation coverage. The theoretical model is then compared with experimental data obtained under conditions similar to those of the modeling work. Studying the adsorption of polystyrene particles on a silicon wafer in an aqueous system was employed to experimentally validate the theoretical framework. It has been shown both theoretically and experimentally that the particle and solid surface zeta potential values do influence the adsorption kinetics but the effect is too negligible to be of any use in accelerating the kinetics. We have shown that the electrostatically driven particle adsorption is a transport limited process and the rate of transport is not a major function of the zeta potential values of the particle and the solid surface. The faster kinetics seen when the ionic concentration of the suspension is increased is because of the blocking effects and not due to faster approach of particles towards the solid surface. Finally, we have made an important addition to the existing models by incorporating the variation in the flux as a function of particle/solid surface zeta potentials, surface coverage and the randomized position of incidence of an incoming particle on the solid surface.

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Latex-microgel core-satellite particles were prepared by electrostatic assembly of negatively charged polystyrene latex and positively charged microgels of a poly(N-isopropylmethacrylamide) (pNIPMAM) and poly[2-methacryloyloxy)ethyl] trimethylammonium chloride (pMETAC) copolymer. The number of satellites per core, determined by scanning electron microscopy, varied from 3 to 10 depending on the sizes of the microgel and latex microparticles. The numbers of satellites per core for different size ratios were compared with the predictions for thermodynamically controlled (maximum packing) and kinetically controlled (random sequential adsorption) assembly, and it was shown that the assembly of latex and microgel proceeds through a random sequential adsorption mechanism. The charges of the microgels and latex particles were retained within the assemblies; therefore, the core-satellite particles have well-defined regions of positive and negative charge. These regions were used to direct the adsorption of gold and latex nanoparticles of opposite charge in order to create multicomponent colloids.

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Many biochemical reactions are confined to interfaces, such as membranes or cell walls. Despite their importance, no canonical rate laws describing the kinetics of surface-active enzymes exist. Combining the approach chosen by Michaelis and Menten 100 years ago with concepts from surface chemical physics, we here present an approach to derive generic rate laws of enzymatic processes at surfaces. We illustrate this by a simple reversible conversion on a surface to stress key differences to the classical case in solution. The available area function, a concept from surface physics which enters the rate law, covers different models of adsorption and presents a unifying perspective on saturation effects and competition between enzymes. A remarkable implication is the direct dependence of the rate of a given enzyme on all other enzymatic species able to bind at the surface. The generic approach highlights general principles of the kinetics of surface-active enzymes and allows to build consistent mathematical models of more complex pathways involving reactions at interfaces.

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Protein adsorption plays a significant role in biological phenomena such as cell-surface interactions and the coagulation of blood. Two-dimensional random sequential adsorption (RSA) models are widely used to model the adsorption of proteins on solid surfaces. Continuum equations have been developed so that the results of RSA simulations can be used to predict the kinetics of adsorption. Recently, Brownian dynamics simulations have become popular for modeling protein adsorption. In this work a continuum model was developed to allow the results from a Brownian dynamics simulation to be used as the boundary condition in a computational fluid dynamics (CFD) simulation. Brownian dynamics simulations were used to model the diffusive transport of hard-sphere particles in a liquid and the adsorption of the particles onto a solid surface. The configuration of the adsorbed particles was analyzed to quantify the chemical potential near the surface, which was found to be a function of the distance from the surface and the fractional surface coverage. The near-surface chemical potential was used to derive a continuum model of adsorption that incorporates the results from the Brownian dynamics simulations. The equations of the continuum model were discretized and coupled to a CFD simulation of diffusive transport to the surface. The kinetics of adsorption predicted by the continuum model closely matched the results from the Brownian dynamics simulation. This new model allows the results from mesoscale simulations to be incorporated into micro- or macro-scale CFD transport simulations of protein adsorption in practical devices.