SM01.03.28 : Programmable Deformations of Microchannel Networks for Soft Robotics

5:00 PM–7:00 PM Apr 3, 2018

PCC North, 300 Level, Exhibit Hall C-E

Abhiteja Konda1 Donghee Lee3 Taesun You4 Xiaoyan Wang5 Stephen Morin1 2 Sangjin Ryu3 2

1, University of Nebraska-Lincoln, Lincoln, Nebraska, United States
3, University of Nebraska-Lincoln, Lincoln, Nebraska, United States
4, Louisiana State University, Baton Rouge, Louisiana, United States
5, University of Nebraska Medical Center, Omaha, Nebraska, United States
2, University of Nebraska-Lincoln, Lincoln, Nebraska, United States

Soft lithography is ubiquitous in the fabrication of microfluidics, which, as a technology, has enabled applications in several fields including analytical chemistry, medical diagnostics, microelectronics, and soft robotics. In most of these applications, soft lithography was employed to generate micro-channel geometries of fixed dimensions that ideally would remain invariant during operation. In soft robotics, however, micro-channels contained in soft actuating systems are inherently dynamic and the specific dimensions are expected to change and, by extension the liquid transport properties of the system. Not understanding this problem or generating ways to control it will hamper soft systems with distributed liquid transport systems. Herein, we explored the channel deformation phenomenon (using finite elemental analysis and experimental investigation) observed in elastomeric materials and applied it to the fabrication of microfluidic systems with dynamic channel geometries of predictable dimensions and morphology, thus leading to devices with “programmable” transport properties. While this approach can provide access to channel geometries that are otherwise challenging to fabricate using replica molding, it will also enable fabrication of systems with predictable deformation behavior in pneumatic actuation. We analyzed the channel profile at various states of deformation for comparison with the simulation domain by: (i) imaging channel replicates using microtomography (microCT) or optical microscope, and/or (ii) real-time monitoring of the channel deformation using optical microscopy. By linking these observations to simulation we could fabricate microchannel networks with predictable changes in geometry when subjected to various stresses. This work will provide insight into the channel deformation processes expected in soft robotic systems with embedded networks of microchannels (which may contain liquid metals, reagents, fuel sources, etc.) leading to devices with reliable/predictable transport properties throughout the deformations associated with actuation.