# Morphology and Kinetics of Random Sequential Adsorption of Superballs: From Hexapods to Cubes Source: [Morphology and Kinetics of Random Sequential Adsorption of Superballs: From Hexapods to Cubes]() Collection index: [llms.txt]() Data updated: 2025-10-25T00:06:40.080Z Authors: Pooria Yousefi, Hessam Malmir, Muhammad Sahimi Published: 2019-05-30T16:14:43.000Z ## Abstract Superballs represent a class of particles whose shapes are defined by ${\|x\|}^{2p}+{\|y\|}^{2p}+{\|z\|}^{2p} \\le R^{2p}$, with $p\\in(0,\\infty)$ being the "deformation parameter". $0\1$ one has, respectively, families of convex octahedrallike and cubelike particles, with $p=1,\\;0.5$ and $\\infty$ representing spheres, octahedra, and cubes. Colloidal zeolite suspensions, catalysis, and adsorption, as well as biomedical magnetic nanoparticles are but a few of the applications of packing of superballs. We introduce a universal method for simulating random sequential adsorption of superballs, which we refer to as "low-entropy" algorithm, in contrast with the conventional algorithm that represents a "high-entropy" method. The two algorithms yield, respectively, precise estimates of the jamming fraction $\\phi\_\\infty(p)$ and $\\nu(p)$, the exponent that characterizes the kinetics of adsorption at long times $t$, $\\phi(\\infty)-\\phi(t)\\sim t^{-\\nu(p)}$. Precise estimates of $\\phi\_\\infty(p)$ and $\\nu(p)$ are obtained and shown to be in agreement, in some special limits, with the existing analytical and numerical results. ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. ## Original sources and implementation [Original paper]() [PDF]()