Random Sequential Adsorption Research Articles

Percolation connectivity in deposits obtained usingcompetitive random sequential adsorption of binarydisk mixtures

Connectedness percolation phenomena in the two-dimensional (2D) packing of binary mixtures of disks with different diameters were studied numerically. The packings were produced using random sequential adsorption (RSA) model with simultaneous deposition of disks. The ratio of the particle diameters was varied within the range D=1-10, and the selection probability of the small disks was varied within the range 0-1. A core-shell structure of the particles was assumed for the analysis of connectivity. The packing coverages in a jamming state for different components, connectivities through small, large and both types of disks, the behavior of electrical conductivity were analyzed. The observed complex effects were explained accounting for the formation of conductive "bridges" from small disks in pores between large disks. 

Asphaltene Adsorption on Solid Surfaces Investigated Using Quartz Crystal Microbalance with Dissipation under Flow Conditions.

Asphaltenes can cause operational challenges in petroleum production facilities and adversely affect production by adsorption on mineral surfaces and alteration of the oil wettability of reservoirs. Therefore, understanding asphaltene adsorption mechanisms and their effects is crucial to improving the efficiency of oil production and reducing costs. In this study, we focus on understanding the impact of asphaltene concentration and the depositing environment of asphaltene adsorption on solid surfaces using the quartz crystal microbalance with dissipation (QCM-D) technique. The initial and long-term kinetics of adsorption at different concentrations were examined on three different solid surfaces including silicon dioxide to represent quartz mineral, stainless steel, and gold. The frequency-dissipation data showed evidence of monolayer adsorption initially, followed by multilayer formation. At short times, the adsorbed mass increased linearly with time, suggesting that the process was kinetically controlled rather than diffusion-controlled. The results were reproducible and did not depend on convection velocity but did depend on the surface material. At later stages, the monolayer development appeared to follow the random sequential adsorption (RSA) theory. Once multilayer adsorption commenced, the rates agreed well with the two-layer model of Zhu and Gu, 1990. The impact of asphaltene adsorption on the wettability of the surface was examined using contact angle studies, which showed decreasing water wettability with an increase in the adsorbed mass. The contact angle of water after 12 h of adsorption leveled off at around 100° on all three surfaces. Contact angle measurements were also used to evaluate if brine salinity causes the wettability alteration of surfaces with the adsorbed asphaltene. The results indicate that at 3% NaCl solution, the contact angle decreased only slightly by less than 2°.

Density and Correlation in a Random Sequential Adsorption Model

We consider the random sequential adsorption process on the one- dimensional lattice with nearest-neighbor exclusion. In this model, each site s 2 Z starts empty and a particle will be deposited in it at time ts, where (ts)s2Z is a sequence of independent random variables uniformly distributed on the interval [0; 1]. The site will be occupied if both of its neighbors are vacant. Analytical expressions for the density of occupied sites and the pair correlation function, for all time t, are well-established and have been obtained through methods such as generating functions and differential equations. In this study, we present a method based on probabilistic arguments for the calculation of these expressions.

Competitive random sequential adsorption of binary mixtures of disks and discorectangles

The two-dimensional (2D) packings of binary mixtures of disks with diameter d and discorectangles with aspect ratio ɛ (length-to-width ratio ε=l/d ) were studied numerically. The competitive random sequential adsorption (RSA) with simultaneous deposition of particles was considered. The aspect ratio was changed within the range ε=1−10 . In the competitive model, the particle was selected with probability pd (disks) and pε=1−pd (discorectangles), and then they were placed sequentially on a solid surface without overlapping with previously placed particles. Behavior of the total coverage in jamming state ϕ T at different values of pd and ɛ was analyzed. For core–shell structure of the particles the percolation connectivity of films was also discussed.

One-dimensional AB random sequential adsorption with one deposition per site

We investigate a modified version of the AB random sequential adsorption model. Specifically, this model involves the deposition of two distinct types of particles onto a lattice, with the constraint that different types cannot occupy neighboring sites. By restricting the deposition attempts to only one per site, we derive an analytical expression for the average densities of particles of types A and B, at all time instances, for all deposition probabilities of each particle type.

Growth Kinetics of Random Sequential Adsorption Packings Built of Two-Dimensional Shapes with Discrete Orientations

We studied random sequential adsorption packings constructed from rectangles, ellipses, and discorectangles, where the orientations of constituent shapes were picked from discrete sets of values with varying spacing. It allowed us to monitor the transition between the two edge cases: the parallel alignment and the arbitrary, continuous orientation of the shapes within the packing. The packings were generated numerically. Apart from determining the kinetics of packing growth in low- and high-density regimes, we analyzed the results in terms of packing density and probed the microstructural properties using the density autocorrelation function.

Two-stage random sequential adsorption of discorectangles and disks on a two-dimensional surface.

The different variants of two-stage random sequential adsorption (RSA) models for packing of disks and discorectangles on a two-dimensional (2D) surface were investigated. In the SD (sticks+disks) model, the discorectangles were first deposited and then the disks were added. In the DS (disks+sticks) model, the disks were first deposited and then discorectangles were added. At the first stage the particles were deposited up to the selected concentration and at the final (second) stage the particles were deposited up to the saturated (jamming) state. The main parameters of the models were the concentration of particles deposited at the first stage, aspect ratio of the discorectangles ɛ (length to diameter of ratio ɛ=l/d) and disk diameter D. All distances were measured using the value of d as a unit of measurement of linear dimensions, the disk diameter was varied in the interval D∈[1-10], and the aspect ratio value was varied in the interval ɛ∈[1-50]. The dependencies of the jamming coverage of particles deposited at the second stage versus the parameters of the models were analyzed. The presence of first deposited particles for both models regulated the maximum possible disk diameter D_{max} (SD model) or the maximum aspect ratio ɛ_{max} (DS model). This behavior was explained by the deposition of particles in the second stage into triangular (SD model) or elongated (DS model) pores formed by particles deposited at the first stage. The percolation connectivity of disks (SD model) and discorectangles (DS model) for the particles with a hard core and a soft shell structure was analyzed. The disconnectedness was ensured by overlapping of soft shells. The dependencies of connectivity versus the parameters of SD and DS models were also analyzed.

Percolation in random sequential adsorption of polydisperse mixtures of extended objects on a triangular lattice

Percolation properties of an adsorbed polydisperse mixture of extended objects on a triangular lattice are studied by Monte Carlo simulations. The depositing objects of various shapes are formed by self-avoiding walks on the lattice. We study polydisperse mixtures in which the size of the shape making the mixture increases gradually with the number of components. This study examines the influence of the shape of the primary object defining a polydisperse mixture on its percolation and jamming properties. The dependence of the jamming density and percolation threshold on the number of components n making the mixture is analyzed. Determining the contribution of the individual components in the lattice covering allowed a better insight into the deposit structure of the n-component mixture at the percolation threshold. In addition, we studied mixtures of objects of various shapes but the same size.

Mechanical Characterization of MWCNT-Reinforced Cement Paste: Experimental and Multiscale Computational Investigation.

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.

Inverse percolation by removing straight semirigid rods from bilayer square lattices.

Numerical simulations and finite-size scaling analysis have been carried out to study the problem of inverse percolation by removing semirigid rods from a L×L square lattice that contains two layers (and M=L×L×2 sites). The process starts with an initial configuration where all lattice sites are occupied by single monomers (each monomer occupies one lattice site) and, consequently, the opposite sides of the lattice are connected by nearest-neighbor occupied sites. Then the system is diluted by removing groups of k consecutive monomers according to a generalized random sequential adsorption mechanism. The study is conducted by following the behavior of two critical concentrations with size k: (1) jamming coverage θ_{j,k}, which represents the concentration of occupied sites at which the jamming state is reached, and (2) inverse percolation threshold θ_{c,k}, which corresponds to the maximum concentration of occupied sites for which connectivity disappears. The obtained results indicate that (1) the jamming coverage exhibits an increasing dependence on the size k-it rapidly increases for small values of k and asymptotically converges towards a definite value for infinitely large k sizes θ_{j,k→∞}≈0.2701-and (2) the inverse percolation threshold is a decreasing function of k in the range 1≤k≤17. For k≥18, all jammed configurations are percolating states (the lattice remains connected even when the highest allowed concentration of removed sites is reached) and, consequently, there is no nonpercolating phase. This finding contrasts with the results obtained in literature for a complementary problem, where straight rigid k-mers are randomly and irreversibly deposited on a square lattice forming two layers. In this case, percolating and nonpercolating phases extend to infinity in the space of the parameter k and the model presents percolation transition for the whole range of k. The results obtained in the present study were also compared with those reported for the case of inverse percolation by removal of rigid linear k-mers from a square monolayer. The differences observed between monolayer and bilayer problems were discussed in terms of vulnerability and network robustness. Finally, the accurate determination of the critical exponents ν, β, and γ reveals that the percolation phase transition involved in the system has the same universality class as the standard percolation problem.

Random sequential adsorption of self-avoiding chains on two-dimensional lattices.

Random sequential adsorption of extended objects deposited on two-dimensional regular lattices is studied. The depositing objects are chains formed by occupying adsorption sites on the substrate through a self-avoiding walk of k lattice steps; these objects are also called "tortuous k-mers." We study how the jamming coverage, θ_{j,k}, depends on k for lattices with different connectivity (honeycomb, square, and triangular). The dependence can be fitted by the function θ_{j,k}=θ_{j,k→∞}+B/k+C/k^{2}, where B and C are found to be shared parameters by the three lattices and θ_{j,k→∞} (>0) is the jamming coverage for infinitely long k-mers for each of them. The jamming coverage is found to have a growing behavior with the connectivity of the lattice. In addition, θ_{j,k} is found to be higher for tortuous k-mers than for the previously reported for linear k-mers in each lattice. The results were obtained by means of numerical simulation through an efficient algorithm whose characteristics are discussed in detail. The computational method introduced here also allows us to investigate the full-time kinetics of the surface coverage θ_{k}(t) [θ_{j,k}≡θ_{k}(t→∞)]. Along this line, different time regimes are identified and characterized.

A finite element model for 3D printed recycled parts from end-of-life wind turbine blades

Wind turbines are important for clean electric energy, but the increasing number of end-of-life wind turbine blades has become a hazardous waste problem worldwide. A novel recycling approach based on mechanical grinding and combined with 3D printing techniques is a promising solution that will reduce waste at a low cost while retaining the excellent mechanical properties of recycled fabricated samples.Considering the material structure complexity of 3D printed samples, the Representative Volume Element (RVE) is a promising simulation model. This paper proposes a Modified Random Sequential Adsorption (MRSA) algorithm for the efficient generation of RVEs with hybrid and arbitrary-geometry reinforcements. Compared with the classical RSA algorithm, MRSA is advantageous in fiber intersection computational cost. The error between FEA and experiments is lower than results obtained from Mori-Tanaka and Halpin-Tsai. The effects of fiber content, fiber aspect ratio, fiber orientation and local fiber density are discussed. The model will be helpful for accurately predicting properties of 3D printing materials that use recycled wind turbine waste.

Random sequential adsorption of aligned regular polygons and rounded squares: Transition in the kinetics of packing growth.

We study two-dimensional random sequential adsorption (RSA) of flat polygons and rounded squares aligned in parallel to find a transition in the asymptotic behavior of the kinetics of packing growth. Differences in the kinetics for RSA of disks and parallel squares were confirmed in previous analytical and numerical reports. Here, by analyzing the two classes of shapes in question we can precisely control the shape of the packed figuresand thus localize the transition. Additionally, we study how the asymptotic properties of the kinetics depend on the packing size. We also provide accurate estimations of saturated packing fractions. The microstructural properties of generated packings are analyzed in terms of the density autocorrelation function.

Mesoscopic model generation for different grades of concrete

Concrete is a complex composite material with extremely complex behaviour. In macroscale, concrete is considered as homogeneous. But to derive exact macroscopic characteristics, properties of the individual components of concrete and their effects on the material behaviour must be considered as a heterogenous system, concrete can be modelled in two different scales, the microscale and the mesoscale. At the mesoscale it can be interpreted as a composite material made up of three phases: coarse aggregate, mortar, and interfacial transition zone (ITZ). Mortar is further separated into fine aggregate and cement paste at the microscopic level. Mesoscale analysis is thought to be a better choice due to its reduced computational requirements, and it has grown in popularity in research field. This conference paper mainly deals with the generation of mesoscopic models of concrete of different grades using parameterisation approach. Random aggregate structure with random polyhedral shaped aggregates and Fuller’s distribution curve is generated. Realistic concrete aggregates are created by sequentially slicing a cuboid to create a polyhedron with several faces when an aggregate size distribution is given. A hierarchic random sequential adsorption algorithm is used to assemble the generated aggregates into the mesostructure.

Computational Investigation of Precursor Blocking during Area-Selective Atomic Layer Deposition Using Aniline as a Small-Molecule Inhibitor

Area-selective atomic layer deposition using small-molecule inhibitors (SMIs) involves vapor-phase dosing of inhibitor molecules, resulting in an industry-compatible approach. However, the identification of suitable SMIs that yield a high selectivity remains a challenging task. Recently, aniline (C6H5NH2) was shown to be an effective SMI during the area-selective deposition (ASD) of TiN, giving 6 nm of selective growth on SiO2 in the presence of Ru and Co non-growth areas. In this work, using density functional theory (DFT) and random sequential adsorption (RSA) simulations, we investigated how aniline can effectively block precursor adsorption on specific areas. Our DFT calculations confirmed that aniline selectively adsorbs on Ru and Co non-growth areas, whereas its adsorption on the SiO2 growth area is limited to physisorption. DFT reveals two stable adsorption configurations of aniline on the metal surfaces. Further calculations on the aniline-functionalized surfaces show that the aniline inhibitor significantly reduces the interaction of Ti precursor, tetrakis(dimethylamino)titanium, with the non-growth area. In addition, RSA simulations showed that the co-presence of two stable adsorption configurations allows for a high surface inhibitor coverage on both Co and Ru surfaces. As the surface saturates, there is a transition from the thermodynamically most favorable adsorption configuration to the sterically most favorable adsorption configuration, which results in a sufficiently dense inhibition layer, such that an incoming precursor molecule cannot fit in between the adsorbed precursor molecules. We also found that, as a result of the catalytic activity of the metallic non-growth area, further reactions of inhibitor molecules, such as hydrogenolysis, can play a role in precursor blocking.

Grand canonical Brownian dynamics simulations of adsorption and self-assembly of SAS-6 rings on a surface.

The Spindle Assembly Abnormal Protein 6 (SAS-6) forms dimers, which then self-assemble into rings that are critical for the nine-fold symmetry of the centriole organelle. It has recently been shown experimentally that the self-assembly of SAS-6 rings is strongly facilitated on a surface, shifting the reaction equilibrium by four orders of magnitude compared to the bulk. Moreover, a fraction of non-canonical symmetries (i.e., different from nine) was observed. In order to understand which aspects of the system are relevant to ensure efficient self-assembly and selection of the nine-fold symmetry, we have performed Brownian dynamics computer simulation with patchy particles and then compared our results with the experimental ones. Adsorption onto the surface was simulated by a grand canonical Monte Carlo procedure and random sequential adsorption kinetics. Furthermore, self-assembly was described by Langevin equations with hydrodynamic mobility matrices. We find that as long as the interaction energies are weak, the assembly kinetics can be described well by coagulation-fragmentation equations in the reaction-limited approximation. By contrast, larger interaction energies lead to kinetic trapping and diffusion-limited assembly. We find that the selection of nine-fold symmetry requires a small value for the angular interaction range. These predictions are confirmed by the experimentally observed reaction constant and angle fluctuations. Overall, our simulations suggest that the SAS-6 system works at the crossover between a relatively weak binding energy that avoids kinetic trapping and a small angular range that favors the nine-fold symmetry.

CCCs off-axial orientation sensitivity analysis in hole pin-bearing failure via hierarchical multiscale simulation framework

In current investigation, a sequential multiscale modelling strategy together with corresponding experimental validation aimed to evaluate the influence of off-axial orientation on three-dimensional orthogonal woven carbon/carbon composites (3DOWCCCs) pin-bearing failure behavior. A hierarchical numerical simulation methodology at micro−/meso−/macroscales was developed to obtain the predictions. With the intention of acquiring precise mechanical responses of unnotched 3DOWCCCs, fiber and void stochastic arrangements in micro-level representative volume elements (RVEs) were generated using Random Sequential Adsorption (RSA) algorithm, meanwhile the geometrical reconstruction of meso-level RVE was accomplished via X-ray computed tomography (X-CT). Moreover, off-axial angle sensitivity analysis was presented through the comparison between macroscale modelling and testing results. The stress interaction and coupling impacts were embedded in material constitutive laws, which combined Murakami-Ohno theory for yarn based on continuum damage mechanics, and exponential damage rule for carbon matrix, incorporating trilinear cohesive zone model (CZM) for interface, and the achieved predictions agreed reasonably well with the experimental results. It is concluded that, for on-axial specimen, the warp yarns fracture and material out-of-plane swelling were the primary damage mechanism, while the material out-of-plane swelling in conjunction with yarns in-plane rotation dominated the structural failure under off-axial cases.

Percolation in two-species antagonistic random sequential adsorption in two dimensions.

We consider two-species random sequential adsorption (RSA) in which species A and B adsorb randomly on a lattice with the restriction that opposite species cannot occupy nearest-neighbor sites. When the probability x_{A} of choosing an A particle for an adsorption trial reaches a critical value 0.626441(1), the A species percolates and/or the blocked sites X (those with at least one A and one B nearest neighbor) percolate. Analysis of the size-distribution exponent τ, the wrapping probabilities, and the excess cluster number shows that the percolation transition is consistent with that of ordinary percolation. We obtain an exact result for the low x_{B}=1-x_{A} jamming behavior: θ_{A}=1-x_{B}+b_{2}x_{B}^{2}+O(x_{B}^{3}),θ_{B}=x_{B}/(z+1)+O(x_{B}^{2}) for a z-coordinated lattice, where θ_{A} and θ_{B} are, respectively, the saturation coverages of species A and B. We also show how differences between wrapping probabilities of A and X clusters, as well as differences in the number of A and X clusters, can be used to find the percolation transition point accurately.

Adsorption of Metals on (100) Metallic Surfaces: Monte Carlo Simulations and Geometrical Phase Transitions.

Adsorption and continuous phase transitions (percolation) of metals on (100) metallic surfaces are studied by means of Monte Carlo simulations and the finite-size scaling theory. The studied systems are Ag/Au(100), Au/Ag(100), Ag/Pt(100), and Pt/Ag(100), and the embedded atom method (EAM) is employed for energy calculations. Pairwise interactions are also considered for comparative purposes. The study of critical exponents reveals that these systems belong to the same universality as random sequential adsorption (RSA). For the four systems studied, and the two kinds of interactions considered, phase diagrams of percolation threshold, θc, as a function of temperature are presented. In all cases, and for all temperatures, θc is always below the value corresponding to RSA, as expected for attractive interactions, and it tends to that value as T → ∞. At intermediate temperatures, a particular behavior is found for EAM interactions.

Improved Heat Transfer in Guar Gel Composites Reinforced with Randomly Distributed Glass Microspheres

Improved heat transfer in composites consisting of guar gel matrix and randomly distributed glass microspheres is extensively studied to predict the effective thermal conductivity of composites using the finite element method. In the study, the proper and probabilistic three-dimensional random distribution of microspheres in the continuous matrix is automatically generated by a simple and efficient random sequential adsorption algorithm which is developed by considering the correlation of three factors including particle size, number of particles, and particle volume fraction controlling the geometric configuration of random packing. Then the dependences of the effective thermal conductivity of composite materials on some important factors are investigated numerically, including the particle volume fraction, the particle spatial distribution, the number of particles, the nonuniformity of particle size, the particle dispersion morphology and the thermal conductivity contrast between particle and matrix. The related numerical results are compared with theoretical predictions and available experimental results to assess the validity of the numerical model. These results can provide good guidance for the design of advanced microsphere reinforced composite materials.