Issue 5, 2019

Modular soft robotic microdevices for dexterous biomanipulation

Abstract

We present a methodology for building biologically inspired, soft microelectromechanical systems (MEMS) devices. Our strategy combines several advanced techniques including programmable colloidal self-assembly, light-harvesting with plasmonic nanotransducers, and in situ polymerization of compliant hydrogel mechanisms. We synthesize optomechanical microactuators using a template-assisted microfluidic approach in which gold nanorods coated with thermoresponsive poly(N-isopropylmethacrylamide) (pNIPMAM) polymer function as nanoscale building blocks. The resulting microactuators exhibit mechanical properties (4.8 ± 2.1 kPa stiffness) and performance metrics (relative stroke up to 0.3 and stress up to 10 kPa) that are comparable to that of bioengineered muscular constructs. Near-infrared (NIR) laser illumination provides effective spatiotemporal control over actuation (sub-micron spatial resolution at millisecond temporal resolution). Spatially modulated hydrogel photolithography guided by an experimentally validated finite element-based design methodology allows construction of compliant poly(ethylene glycol) diacrylate (PEGDA) mechanisms around the microactuators. We demonstrate the versatility of our approach by manufacturing a diverse array of microdevices including lever arms, continuum microrobots, and dexterous microgrippers. We present a microscale compression device that is developed for mechanical testing of three-dimensional biological samples such as spheroids under physiological conditions.

Graphical abstract: Modular soft robotic microdevices for dexterous biomanipulation

Supplementary files

Article information

Article type
Paper
Submitted
01 nov 2018
Accepted
18 jan 2019
First published
04 feb 2019
This article is Open Access
Creative Commons BY-NC license

Lab Chip, 2019,19, 778-788

Modular soft robotic microdevices for dexterous biomanipulation

B. Özkale, R. Parreira, A. Bekdemir, L. Pancaldi, E. Özelçi, C. Amadio, M. Kaynak, F. Stellacci, D. J. Mooney and M. S. Sakar, Lab Chip, 2019, 19, 778 DOI: 10.1039/C8LC01200H

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