  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". $0<p<0.5$ represents a family of hexapodlike (concave
octahedrallike) particles, while for $0.5\leq p<1$ and $p>1$ 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.
