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Recent measurements of inertial particles in isotropic turbulence (Hammond & Meng, J. Fluid Mech., vol. 921, 2021, A16) revealed surprising extreme clustering of particles at near-contact separations 
$(r)$, whereby the radial distribution function, 
$g(r)$, grows from 
$O(10)$ to 
$O(10^3)$ with a 
$(r/a)^{-6}$ scaling (where 
$a$ is the particle radius), and a surprising upturn of the mean inward particle-pair relative velocity (MIRV). Hydrodynamic interactions (HIs) were proposed to explain the extreme clustering, but despite predicting the correct scaling 
$(r/a)^{-6}$, the HI theory underpredicted 
$g(r)$ by at least two orders of magnitude (Bragg et al., J. Fluid Mech., vol. 933, 2022, A31). To further understand the extreme clustering phenomenon and the relevance of HI, we characterize 
$g(r)$ and particle-pair kinematics for Stokes numbers 
$0.07 \leq St \leq 3.68$ in a homogeneous isotropic turbulence chamber using three-dimensional (3-D) particle tracking resolved to near–contact. A drift–diffusion equation governing 
$g(r)$ is presented to investigate the kinematic mechanisms of particle pairs. Measurements in all 24 conditions show that when 
$r/a\lessapprox 20$, extreme clustering consistently occurs, scaling as 
$g(r) \sim (r/a)^{-k}$ with 
$4.5 \leq k \leq 7.6$, which increases with 
$St$. Here 
$g(r)$ varies with 
$St$, particle size, density and polydispersity in ways that HI cannot explain. The extreme clustering region features an inward drift contributed by particle-pair turbophoresis and an inward radial relative acceleration. The latter indicates an interparticle attractive force at these separations that HI also cannot explain. The MIRV turns upward when approaching the extreme clustering region, opposite to direct numerical simulation predictions. These observations further support our previous assessment that extreme clustering arises from particle–particle interactions, but HI is not the main mechanism.
Hydrodynamic clogging in planar channels is studied via direct numerical simulation for the first time, utilising a novel numerical test cell and stochastic methodology with special focus on the influence of electrostatic forces. Electrostatic physics is incorporated into an existing coupled lattice Boltzmann-discrete element method framework, which is verified rigorously. First, the dynamics of the problem is governed by the Stokes number, 
$St$. At low 
$St$, the clogging probability, 
$P$, increases with 
$St$ due to increasing collision frequency. At high 
$St$, however, 
$P$ decreases with 
$St$ due to quadratic scaling of hydrodynamic force acting on arches. Under electrostatic forces, clogging is well represented by the wall adhesion number, 
$Ad_w$. For 
$Ad_w \lesssim 4$, the mechanical dependence on 
$St$ is exhibited, while for 
$4 < Ad_w < 20$, there is a transition to high 
$P$ as sliding along, and attachment to, the channel surface occurs increasingly. For 
$Ad_w \gtrsim 20$, clogging occurs with 
$P > 0.95$. Particle agglomeration, however, can also decrease 
$P$ due to diminished interaction with channel walls. Distinct parametric regions of clogging are also observed in relation to the channel width, while a critical width 
$w/d^*=2.6$ is reported, which increases to 
$w/d^*=4$ with strong electrostatic surface attachment. The number of particles that form stable arches across a planar channel is determined to be 
$n=\left \lceil {w/d}\right \rceil + 1$. Finally, sensitivity to the Coulomb friction coefficient is determined in favour of calibrating numerical parameters to bulk system behaviour. The greatest sensitivities occur in situations where the arch stability is lowest, while clogging becomes independent of friction for strong wall adhesion.
