2007
DOI: 10.1016/j.physa.2006.11.001
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Random sequential adsorption of polydisperse spherical particles: An integral-equation theory

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Cited by 9 publications
(7 citation statements)
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“…On the other hand, in the RSA of squares on a lattice, the ex-cluded volume condition has a much more drastic effect, so that only monomers (s = a) and other small squares can be adsorbed in a dense region. This preferential adsorption of the minimum-sized particles was formerly observed in continuum models with uniform incident distributions [18,26].…”
Section: Adsorbed Particle Size Distributionsupporting
confidence: 66%
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“…On the other hand, in the RSA of squares on a lattice, the ex-cluded volume condition has a much more drastic effect, so that only monomers (s = a) and other small squares can be adsorbed in a dense region. This preferential adsorption of the minimum-sized particles was formerly observed in continuum models with uniform incident distributions [18,26].…”
Section: Adsorbed Particle Size Distributionsupporting
confidence: 66%
“…This is similar to our findings for w = 1/2. However, in lat- tice RSA, the monotonic decay was formerly observed only with uniform incident distributions [18,20,28] and was independent of the distribution width and deposition time.…”
Section: Adsorbed Particle Size Distributionsmentioning
confidence: 91%
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“…[3] for sequential quenching is based on the multicomponent treatment, in which particles depositing on a surface at different times are regarded as different species. Its application to the RSA of the polydisperse particles was recently investigated [11]. In this work, we focus on another theory which is based on a binary-mixture treatment, in which an evolving sequentially quenched system is viewed as a binary mixture of the previously quenched particles (denoted by the index m) and the (infinitely dilute) newly added particle(s) (denoted by f ), of number densities ρ and dρ, respectively.…”
Section: An Integral-equation Theory Based On Binary-mixture Approximmentioning
confidence: 99%
“…Since then, many variants of this problem have been studied -by considering the role of dimensionality and shape of both the particles and the substrate as well as particle size distribution. These include considerations of heterogeneous 1D particles on 1D substrates, 1D particles on flat 2D substrates (needles on a plane [8,16], polymer chains on a lattice [2,17], dimers on a ladder [18,19]), 2D particles on flat 2D substrates (disks, rectangles/ellipses [16,20] with fixed or arbitrary orientation, stars and other concave objects [21], mixed concave/convex objects [4], or compound objects [14] on a plane or on a narrow strip [22]); 3D particles on fractals [23] or porous solids [7]; and 3D particles on flat 2D substrate (polydisperse spheres on a plane [24]).…”
mentioning
confidence: 99%