Smoothed dissipative particle dynamics for mesoscale advection–diffusion–reaction problems

Smoothed dissipative particle dynamics (SDPD) is a widely used particle-based method for modeling soft matter systems at mesoscopic and macroscopic scales, offering thermodynamic consistency and direct control over the fluid’s transport properties. Here, we present an SDPD model that incorporates the transport of reactants on scales smaller than the discretizing particles, including the evolution of compositional fields. The proposed methodology is well-suited for modeling complex systems governed by advection–diffusion–reaction (ADR) dynamics. Implemented in Large-scale Atomic/Molecular Massively Parallel Simulator, the model is validated using a range of benchmark problems spanning diffusion-dominated, reaction-dominated, and coupled ADR regimes. Our simulation results demonstrate that the implemented SDPD model effectively captures complex behaviors, such as Turing pattern formation. The proposed model holds promise for applications across various fields, including biology, chemistry, materials science, and environmental engineering.