Bacterial interactions are fundamental in shaping community structure and function, driving processes that range from plastic degradation in marine ecosystems to dynamics within the human gut microbiome. Yet, studying these interactions is challenging due to difficulties in resolving spatiotemporal scales, quantifying interaction strengths, and integrating intrinsic cellular behaviors with extrinsic environmental conditions. Individual-based modeling addresses these challenges through single-cell-level simulations that explicitly model growth, division, motility, and environmental responses. By capturing both the spatial organization and social interactions, individual-based modeling reveals how microbial interactions and environmental gradients collectively shape community architecture, species coexistence, and adaptive responses. In particular, individual-based modeling provides mechanistic insights into how social behaviors—such as competition, metabolic cooperation, and quorum sensing—are regulated by spatial structure, uncovering the interplay between localized interactions and emergent community properties. In this review, we synthesize recent applications of individual-based modeling in studying bacterial spatial and social interactions, highlighting how their interplay governs community stability, diversity, and resilience. By linking individual-scale interactions with the ecosystem-level organization, individual-based modeling offers a predictive framework for understanding microbial ecology and informing strategies for controlling and engineering bacterial consortia in both natural and applied settings.

Spiral jet mills are ubiquitous in the pharmaceutical industry. Breakage and classification in spiral jet mills occur due to complex interactions between the fluid and the solid phases. The study of these interactions requires the use of computational fluid dynamics (CFD) for the fluid phase coupled with discrete element models (DEM) for the particle phase. In this study, we investigate particle dynamics in a 50-mm spiral jet mill through coupled CFD-DEM simulations. The simulations showed that the fluid was significantly decelerated by the presence of the particles in the milling chamber. Furthermore, we study the particle dynamics and collision statistics at two different operating conditions and three different particle loadings. As expected, the particle velocity was affected by both the particle loading and operating pressure. The particles moved slower at low pressures and high loadings. We also found that particle–particle collisions outnumbered particle–wall collisions.