Aging Dynamics in Chemical Gardens: A Combined Computational and Experimental Study

Amari Morris 

Bruno Batista

Oliver Steinbock

Florida State University

Chemical gardens are intricate structures formed by precipitation reactions. Despite their inorganic nature, they exhibit emergent, life-like properties and shapes. Our study employs a cellular automaton (CA) model to simulate the growth and aging of these structures, effectively capturing their evolving patterns and dynamics. The core premise of this model suggests that, as the material undergoes aging, it significantly impacts the probability of continuing growth. To corroborate and quantify our simulation, we conduct experiments in a Hele-Shaw cell where pattern growth is intermittently interrupted for various wait times, t. Our analysis of the growth positions reveals two distinct behaviors: When the wait time (t) is short, the pattern expansion continues smoothly at the original growth points; with longer wait times, however, breaches occur in older regions of the precipitate. These observations suggest that the underlying aging kinetics of the material control the pattern formation, supporting the assumptions of our CA model. This research offers foundational insights into the growth dynamics of biological systems, which often occur at differing rates in their bulk volume and surface layers.