Nanofibril scaffold assisted MEMS artificial hydrogel neuromasts for enhanced sensitivity flow sensing
We present the development and testing of superficial neuromast-inspired flow sensors that also attain high sensitivity and resolution through a biomimetic hyaulronic acid-based hydrogel cupula dressing. The inspiration comes from the spatially distributed neuromasts of the blind cavefish that live...
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sg-ntu-dr.10356-874792023-03-04T17:11:35Z Nanofibril scaffold assisted MEMS artificial hydrogel neuromasts for enhanced sensitivity flow sensing Kottapalli, Ajay Giri Prakash Bora, Meghali Asadnia, Mohsen Miao, Jianmin Triantafyllou, Michael Venkatraman, Subbu Subramanian School of Materials Science & Engineering School of Mechanical and Aerospace Engineering Singapore-MIT Alliance Programme Hydrogel Nanofibers DRNTU::Engineering::Mechanical engineering We present the development and testing of superficial neuromast-inspired flow sensors that also attain high sensitivity and resolution through a biomimetic hyaulronic acid-based hydrogel cupula dressing. The inspiration comes from the spatially distributed neuromasts of the blind cavefish that live in completely dark undersea caves; the sensors enable the fish to form three-dimensional flow and object maps, enabling them to maneuver efficiently in cluttered environments. A canopy shaped electrospun nanofibril scaffold, inspired by the cupular fibrils, assists the drop-casting process allowing the formation of a prolate spheroid-shaped artificial cupula. Rheological and nanoindentation characterizations showed that the Young’s modulus of the artificial cupula closely matches the biological cupula (10–100 Pa). A comparative experimental study conducted to evaluate the sensitivities of the naked hair cell sensor and the cupula-dressed sensor in sensing steady-state flows demonstrated a sensitivity enhancement by 3.5–5 times due to the presence of hydrogel cupula. The novel strategies of sensor development presented in this report are applicable to the design and fabrication of other biomimetic sensors as well. The developed sensors can be used in the navigation and maneuvering of underwater robots, but can also find applications in biomedical and microfluidic devices. NRF (Natl Research Foundation, S’pore) Published version 2018-11-26T02:38:10Z 2019-12-06T16:42:47Z 2018-11-26T02:38:10Z 2019-12-06T16:42:47Z 2016 Journal Article Kottapalli, A. G. P., Bora, M., Asadnia, M., Miao, J., Venkatraman, S. S., & Triantafyllou, M. (2016). Nanofibril scaffold assisted MEMS artificial hydrogel neuromasts for enhanced sensitivity flow sensing. Scientific Reports, 6,19336-. doi:10.1038/srep19336. https://hdl.handle.net/10356/87479 http://hdl.handle.net/10220/46699 10.1038/srep19336 26763299 en Scientific Reports © 2016 The Authors (Nature Publishing Group). This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ 12 p. application/pdf |
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Hydrogel Nanofibers DRNTU::Engineering::Mechanical engineering Kottapalli, Ajay Giri Prakash Bora, Meghali Asadnia, Mohsen Miao, Jianmin Triantafyllou, Michael Venkatraman, Subbu Subramanian Nanofibril scaffold assisted MEMS artificial hydrogel neuromasts for enhanced sensitivity flow sensing |
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We present the development and testing of superficial neuromast-inspired flow sensors that also attain high sensitivity and resolution through a biomimetic hyaulronic acid-based hydrogel cupula dressing. The inspiration comes from the spatially distributed neuromasts of the blind cavefish that live in completely dark undersea caves; the sensors enable the fish to form three-dimensional flow and object maps, enabling them to maneuver efficiently in cluttered environments. A canopy shaped electrospun nanofibril scaffold, inspired by the cupular fibrils, assists the drop-casting process allowing the formation of a prolate spheroid-shaped artificial cupula. Rheological and nanoindentation characterizations showed that the Young’s modulus of the artificial cupula closely matches the biological cupula (10–100 Pa). A comparative experimental study conducted to evaluate the sensitivities of the naked hair cell sensor and the cupula-dressed sensor in sensing steady-state flows demonstrated a sensitivity enhancement by 3.5–5 times due to the presence of hydrogel cupula. The novel strategies of sensor development presented in this report are applicable to the design and fabrication of other biomimetic sensors as well. The developed sensors can be used in the navigation and maneuvering of underwater robots, but can also find applications in biomedical and microfluidic devices. |
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School of Materials Science & Engineering |
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School of Materials Science & Engineering Kottapalli, Ajay Giri Prakash Bora, Meghali Asadnia, Mohsen Miao, Jianmin Triantafyllou, Michael Venkatraman, Subbu Subramanian |
format |
Article |
author |
Kottapalli, Ajay Giri Prakash Bora, Meghali Asadnia, Mohsen Miao, Jianmin Triantafyllou, Michael Venkatraman, Subbu Subramanian |
author_sort |
Kottapalli, Ajay Giri Prakash |
title |
Nanofibril scaffold assisted MEMS artificial hydrogel neuromasts for enhanced sensitivity flow sensing |
title_short |
Nanofibril scaffold assisted MEMS artificial hydrogel neuromasts for enhanced sensitivity flow sensing |
title_full |
Nanofibril scaffold assisted MEMS artificial hydrogel neuromasts for enhanced sensitivity flow sensing |
title_fullStr |
Nanofibril scaffold assisted MEMS artificial hydrogel neuromasts for enhanced sensitivity flow sensing |
title_full_unstemmed |
Nanofibril scaffold assisted MEMS artificial hydrogel neuromasts for enhanced sensitivity flow sensing |
title_sort |
nanofibril scaffold assisted mems artificial hydrogel neuromasts for enhanced sensitivity flow sensing |
publishDate |
2018 |
url |
https://hdl.handle.net/10356/87479 http://hdl.handle.net/10220/46699 |
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1759854216424194048 |