Reaction Diffusion

Reaction-diffusion systems model the interplay between local reactions and spatial diffusion, describing diverse phenomena from chemical reactions to biological pattern formation. Current research emphasizes developing efficient numerical methods, including physics-informed neural networks (PINNs), graph neural networks (GNNs), and novel iterative solvers, to overcome computational challenges associated with solving these often high-dimensional partial differential equations (PDEs). These advancements are improving the accuracy and speed of simulations, enabling applications in areas such as medical imaging analysis (e.g., modeling tumor growth), and the design of novel materials with controlled spatial patterns.