  In this study, we analyze the statistics of both individual inertial
particles and inertial particle pairs in direct numerical simulations of
homogeneous isotropic turbulence in the absence of gravity. The effect of the
Taylor microscale Reynolds number $R_\lambda$ on the particle statistics is
examined over the largest range to date (from $R_\lambda = 88-597$). We first
explore the effect of preferential sampling on the single-particle statistics,
and use our understanding of preferential sampling to provide a physical
explanation for many of the trends in the particle velocity gradients, kinetic
energies, and accelerations at low $St$. As $St$ increases, inertial filtering
effects become more important, causing the particle kinetic energies and
accelerations to decrease.
  We then consider particle-pair statistics, and focus our attention on the
relative velocities and radial distribution functions (RDFs) of the particles.
The relative velocity statistics indicate that preferential-sampling effects
are important for $St \lesssim 0.1$ and that path-history/non-local effects
become increasingly important for $St \gtrsim 0.2$. The lower-order relative
velocity statistics are only weakly sensitive to changes in Reynolds number at
low $St$. We find that the RDFs peak near $St$ of order unity, that they
exhibit power-law scaling for low and intermediate $St$, and that they are
largely independent of Reynolds number for low and intermediate $St$. We also
observe that at large $St$, changes in the RDF are related to changes the
scaling exponents of the relative velocity variances. The particle collision
kernel is found to be largely insensitive to the flow Reynolds number,
suggesting that relatively low-Reynolds-number simulations may be able to
capture much of the relevant physics of droplet collisions and growth in the
adiabatic cores of atmospheric clouds.
