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Plant leaves as templates for soft lithography
Citation
Wu, W and Guijt, RM and Silina, YE and Koch, M and Manz, A, Plant leaves as templates for soft lithography, RSC Advances, 6, (27) pp. 22469-22475. ISSN 2046-2069 (2016) [Refereed Article]
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Copyright Statement
Licensed under Creative Commons Attribution 3.0 Unported (CC BY 3.0) https://creativecommons.org/licenses/by/3.0/
Abstract
We report a simple fast, practical and effective method for the replication of the complex venation patterns of natural leaves into PDMS with accuracy down to a lateral size of 500 nm. Optimising the amount of crosslinker enabled the replication and sealing of the microvascular structures to yield enclosed microfluidic networks. The use of plant leaves as templates for soft lithography was demonstrated across over ten species and included reticulate, arcuate, pinnate, parallel and palmate venation patterns. SEM imaging revealed replication of the plants microscopic and sub-microscopic topography into the PDMS structures, making this method especially attractive for mimicking biological structures for in vitro assays. Flow analysis revealed that the autonomous liquid transport velocity in 1st-order microchannel was 1.5–2.2 times faster than that in the 2nd-order microchannels across three leaf types, with the sorptivity rule surprisingly preserved during self-powered flow through leaf-inspired vascularity from Carpinus betulus.
Item Details
Item Type: | Refereed Article |
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Keywords: | soft lithography, plant leaves, biomimetrics |
Research Division: | Chemical Sciences |
Research Group: | Analytical chemistry |
Research Field: | Separation science |
Objective Division: | Expanding Knowledge |
Objective Group: | Expanding knowledge |
Objective Field: | Expanding knowledge in the chemical sciences |
UTAS Author: | Guijt, RM (Dr Rosanne Guijt) |
ID Code: | 108283 |
Year Published: | 2016 |
Web of Science® Times Cited: | 27 |
Deposited By: | Pharmacy |
Deposited On: | 2016-04-18 |
Last Modified: | 2017-10-30 |
Downloads: | 142 View Download Statistics |
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