Many living structures are coated by thin films, which have distinct mechanical properties from the bulk. In particular, these thin layers may grow faster or slower than the inner core. Differential growth creates a balanced interplay between tension and compression and plays a critical role in enhancing structural rigidity. Typical examples with a compressive outer surface and a tensile inner core are the petioles of celery, caladium, or rhubarb. While plant physiologists have studied the impact of tissue tension on plant rigidity for more than a century, the fundamental theory of growing surfaces remains poorly understood. Here, we establish a theoretical and computational framework for continua with growing surfaces and demonstrate its application to classical phenomena in plant growth. To allow the surface to grow independently of the bulk, we equip it with its own potential energy and its own surface stress. We derive the governing equations for growing surfaces of zero thickness and obtain their spatial discretization using the finite-element method. To illustrate the features of our new surface growth model we simulate the effects of growth-induced longitudinal tissue tension in a stalk of rhubarb. Our results demonstrate that different growth rates create a mechanical environment of axial tissue tension and residual stress, which can be released by peeling off the outer layer. Our novel framework for continua with growing surfaces has immediate biomedical applications beyond these classical model problems in botany: it can be easily extended to model and predict surface growth in asthma, gastritis, obstructive sleep apnoea, brain development, and tumor invasion. Beyond biology and medicine, surface growth models are valuable tools for material scientists when designing functionalized surfaces with distinct user-defined properties. © The Author(s) 2013.
|Original language||English (US)|
|Number of pages||15|
|Journal||Mathematics and Mechanics of Solids|
|State||Published - May 24 2013|
Bibliographical noteKAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): KUK-C1-013-04
Acknowledgements: Maria A. Holland was supported by the Stanford Graduate Fellowship. Alain Goriely is a Wolfson Royal Society Merit Holder and acknowledges support from a Reintegration Grant under EC Framework VII and from award KUK-C1-013-04 from the King Abdullah University of Science and Technology (KAUST). Ellen Kuhl acknowledges support by the National Science Foundation (CAREER award CMMI 0952021) and INSPIRE (grant number 1233054) and by the National Institutes of Health (grant number U54 GM072970).
This publication acknowledges KAUST support, but has no KAUST affiliated authors.