Turing patterns on radially growing domains: experiments and simulations

Literature Information

Publication Date 2019-03-06
DOI 10.1039/C8CP07797E
Impact Factor 3.676
Authors

Christopher Konow, Noah H. Somberg, Jocelyne Chavez, Irving R. Epstein, Milos Dolnik


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Abstract

We study Turing pattern formation in a system undergoing radial growth in two dimensions. The photosensitive chlorine dioxide–iodine–malonic acid reaction is illuminated to inhibit patterning, with a growing non-illuminated circular domain in which the pattern develops. We examine the relationship between the linear radial growth rate and the resulting pattern morphology. Faster growth causes the pattern to form parallel to the growing boundary as concentric rings, while slower growth leads to pattern formation perpendicular to the growing boundary. We observe three distinct growth modes for the Turing patterns, which also depend on the radial growth rate. The experimental results are qualitatively reproduced in numerical simulations using the Lengyel–Epstein model with an additional term to account for the photosensitivity of the reaction. These results may provide new insight into how patterns form in growing biological systems.

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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
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Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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