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In collisional gas–solid flows, dense particle clusters are often observed that greatly affect the transport properties of the mixture. The characterisation and prediction of this phenomenon are challenging due to limited optical access, the wide range of scales involved and the interplay of different mechanisms. Here, we consider a laboratory setup in which particles fall against upward-moving air in a square vertical duct: a classic configuration in riser reactors. The use of non-cohesive, monodispersed, spherical particles and the ability to independently vary the solid volume fraction ( $$\varPhi _V = 0.1\,\% - 0.8\,\%$$ ) and the bulk airflow Reynolds number ( $$Re_{bulk} = 300 - 1200$$ ) allows us to isolate key elements of the multiphase dynamics, providing the first laboratory observation of cluster-induced turbulence. Above a threshold $$\varPhi _V$$ , the system exhibits intense fluctuations of concentration and velocity, as measured by high-speed imaging via a backlighting technique which returns optically depth-averaged fields. The space–time autocorrelations reveal dense and persistent mesoscale structures falling faster than the surrounding particles and trailing long wakes. These are shown to be the statistical footprints of visually observed clusters, mostly found in the vicinity of the walls. They are identified via a percolation analysis, tracked in time, and characterised in terms of size, shape, location and velocity. Larger clusters are denser, longer-lived and have greater descent velocity. At the present particle Stokes number, the threshold $$\varPhi _V \sim 0.5$$ % (largely independent from $$Re_{bulk}$$ ) is consistent with the view that clusters appear when the typical interval between successive collisions is shorter than the particle response time. 

Clusters of inertial particles in turbulence are usually identified from the spatial coherence of the particle concentration field, neglecting their temporal persistence. The latter is in fact essential to the ability of the particles to interact with each other and to modify the flow. Here, we leverage simulations of homogeneous isotropic turbulence laden with small heavy particles and develop a Lagrangian framework to follow them before, during and after their time as part of a coherent cluster. We define a criterion to establish whether a cluster survives over successive time steps, and use it to characterize its lifetime. We find that cluster lives have typical durations of a few Kolmogorov time scales, with positive correlation between cluster size and lifetime. Increasing inertia and gravitational settling both lead to longer lifetimes. Small clusters emerge from the coagulation of non-clustered particles, quickly followed by disintegration into prevalently non-clustered particles. By contrast, large clusters result from the recombination of other large clusters. The birth of a cluster is preceded by an exponential contraction of the particle cloud, and its death coincides with the beginning of a slower exponential expansion, The contraction is simultaneous to a decline in the local small-scale turbulence activity, while the expansion is accompanied by its recovery. Therefore, during their lifetime, the clusters experience lower-than-average enstrophy and strain rate in the fluid. This relatively quiescent state of the flow is thus a necessary condition for the cluster survival, at least in the considered range of turbulence intensity and particle inertia.