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Abstract We describe experiments and simulations to investigate the dynamics of a ball bouncing on a rough vibrating surface. Directly measuring the impulse due to each bounce we find that the frictional interaction with the surface is strongly enhanced near to the side wall. The enhanced dissipation arises as a consequence of the coupling between the collision, rotation and surface friction. This dissipation, which for our experimental conditions was estimated to be up to three times larger than the more obvious inelastic collision, can result in an enhanced probability density near boundaries and particle–particle spatial correlations. Our findings imply that the effective particle collision properties cannot be considered independently of the surface’s frictional properties.

Decades after incorporating plastics into consumer markets, research shows that these polymers have spread worldwide. Fragmentation of large debris leads to smaller particles, collectively called microplastics (MPs), which have become ubiquitous in aquatic environments. A fundamental aspect of understanding the implications of MP contamination on ecosystems is resolving the complex interactions of these artificial substrates with microbial cells. Using polystyrene microparticles as model polymers, we conducted an exploratory study where these interactions are quantitatively analyzed using an in vitro system consisting of single-bacterial species capturing and aggregating MPs in water. Here we show that the production of Psl exopolysaccharide by Pseudomonas aeruginosa (PA) does not alter MPs colloidal stability but plays a key role in microspheres adhesion to the cell surface. Further aggregation of MPs by PA cells depends on bacterial mobility and the presence of sufficient flow to prevent rapid sedimentation of early MP-PA assembles. Surprisingly, cells in MP-PA aggregates are not in a sessile state despite the production of Psl, enhancing the motility of the aggregates by an order of magnitude relative to passive diffusion. The generated data could inform the creation of predictive models that accurately describe the dynamics and influence of bacterial growth on plastics debris., (© 2022 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.)