Skip to main content
SpringerLink
Log in

Nature-Inspired Self-Powered Sensors and Energy Harvesters

  • Chapter
  • First Online:
Self-Powered and Soft Polymer MEMS/NEMS Devices

Part of the book series: SpringerBriefs in Applied Sciences and Technology ((BRIEFSAPPLSCIENCES))

Abstract

Chapter 3 presents a comprehensive review of the various biomimetic self-powered and low-powered MEMS pressure and flow sensors that take inspiration from the biological flow sensors found in the marine world. The sensing performance of the biological flow sensors in marine animals has inspired engineers and scientists to develop efficient state-of-the-art sensors for a variety of real-life applications. In an attempt to achieve high-performance artificial flow sensors, researchers have mimicked the morphology, sensing principle, materials, and functionality of the biological sensors. Inspiration was derived from the survival hydrodynamics featured by various marine animals to develop sensors for sensing tasks in underwater vehicles. The mechanoreceptors of crocodiles have inspired the development of slowly and rapidly adapting MEMS sensory domes for passive underwater sensing. Likewise, the lateral line sensing system in fishes which is capable of generating a three-dimensional map of the surroundings was mimicked to achieve artificial hydrodynamic vision on underwater vehicles. Harbor seals are known to achieve high sensitivity in sensing flows within the wake street of a swimming fish due to the undulatory geometry of the whiskers. Whisker inspired structures were embedded into MEMS sensing membranes to understand their vortex shedding behavior. At the outset, this work comprehensively reviews the sensing mechanisms observed in fishes, crocodiles, and harbor seals. In addition, this chapter presents an in-depth commentary on the recent developments in this area where different researchers have taken inspiration from these aforementioned underwater creatures and developed some of the most efficient artificial sensing systems.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 16.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Triantafyllou, M. S., Weymouth, G. D., & Miao, J. (2016). Biomimetic survival hydrodynamics and flow sensing. Annual Review of Fluid Mechanics, 48, 1–24. https://doi.org/10.1146/annurev-fluid-122414-034329.

    Article  MathSciNet  MATH  Google Scholar 

  2. Windsor, S. P., Norris, S. E., Cameron, S. M., et al. (2010). The flow fields involved in hydrodynamic imaging by blind Mexican cave fish (Astyanax fasciatus). Part I: Open water and heading towards a wall. The Journal of Experimental Biology, 213, 3819–3831. https://doi.org/10.1242/jeb.040741.

    Article  Google Scholar 

  3. Windsor, S. P., Norris, S. E., Cameron, S. M., et al. (2010). The flow fields involved in hydrodynamic imaging by blind Mexican cave fish (Astyanax fasciatus). Part II: Gliding parallel to a wall. The Journal of Experimental Biology, 213, 3832–3842. https://doi.org/10.1242/jeb.040790.

    Article  Google Scholar 

  4. Soares, D. (2002). An ancient sensory organ in crocodilians. Nature, 417, 241–242. https://doi.org/10.1038/417241a.

    Article  Google Scholar 

  5. Dehnhardt, G., Mauck, B., Hanke, W., & Bleckmann, H. (2001). Hydrodynamic trail-following in harbor seals (Phoca vitulina). Science (80- ), 293, 102–104. https://doi.org/10.1126/science.1060514.

    Article  Google Scholar 

  6. Fish, F. E., Howle, L. E., & Murray, M. M. (2008). Hydrodynamic flow control in marine mammals. Integrative and Comparative Biology, 48, 788–800.

    Article  Google Scholar 

  7. Yanase, K., Herbert, N. A., & Montgomery, J. C. (2012). Disrupted flow sensing impairs hydrodynamic performance and increases the metabolic cost of swimming in the yellowtail kingfish, Seriola lalandi. The Journal of Experimental Biology, 215, 3944–3954. https://doi.org/10.1242/jeb.073437.

    Article  Google Scholar 

  8. Yanase, K., & Saarenrinne, P. (2015). Unsteady turbulent boundary layers in swimming rainbow trout. The Journal of Experimental Biology, 218, 1373–1385. https://doi.org/10.1242/jeb.108043.

    Article  Google Scholar 

  9. Montgomery, J. C., Baker, C. F., & Carton, A. G. (1997). The lateral line can mediate rheotaxis in fish. Nature, 389, 960–963. https://doi.org/10.1038/40135.

    Article  Google Scholar 

  10. Montgomery, J. C., Coombs, S., & Baker, C. F. (2001). The mechanosensory lateral line system of the hypogean form of Astyanax fasciatus. Environmental Biology of Fishes, 62, 87–96.

    Article  Google Scholar 

  11. Montgomery, J., Coombs, S., & Halstead, M. (1995). Biology of the mechanosensory lateral line in fishes. Reviews in Fish Biology and Fisheries, 5, 399–416. https://doi.org/10.1007/BF01103813.

    Article  Google Scholar 

  12. Bora, M., Kottapalli, A. G. P., Miao, J., & Triantafyllou, M. (2017). Sensing the flow beneath the fins. Bioinspiration & Biomimetics. https://doi.org/10.1088/1748-3190/aaa1c2.

    Article  Google Scholar 

  13. DIJKGRAAF, S. (1963). THE FUNCTIONING and SIGNIFICANCE OF THE LATERAL-LINE ORGANS. Biological Reviews, 38, 51–105. https://doi.org/10.1111/j.1469-185X.1963.tb00654.x.

    Article  Google Scholar 

  14. Peleshanko, S., Julian, M. D., Ornatska, M., et al. (2007). Hydrogel-encapsulated microfabricated haircells mimicking fish cupula neuromast. Advanced Materials, 19, 2903–2909. https://doi.org/10.1002/adma.200701141.

    Article  Google Scholar 

  15. Anderson, K. D., Lu, D., McConney, M. E., et al. (2008). Hydrogel microstructures combined with electrospun fibers and photopatterning for shape and modulus control. Polymer (Guildf), 49, 5284–5293. https://doi.org/10.1016/j.polymer.2008.09.039.

    Article  Google Scholar 

  16. McConney, M. E., Chen, N., Lu, D., et al. (2009). Biologically inspired design of hydrogel-capped hair sensors for enhanced underwater flow detection. Soft Matter, 5, 292–295. https://doi.org/10.1039/B808839J.

    Article  Google Scholar 

  17. Kottapalli, A. G. P., Bora, M., Asadnia, M., et al. (2016). Nanofibril scaffold assisted MEMS artificial hydrogel neuromasts for enhanced sensitivity flow sensing. Scientific Reports, 6, 19336. https://doi.org/10.1038/srep19336.

    Article  Google Scholar 

  18. Kottapalli, A. G. P., Asadnia, M., Miao, J., & Triantafyllou, M. (2015). Soft polymer membrane micro-sensor arrays inspired by the mechanosensory lateral line on the blind cavefish. Journal of Intelligent Material Systems and Structures, 26, 38–46. https://doi.org/10.1177/1045389X14521702.

    Article  Google Scholar 

  19. Asadnia, M., Kottapalli, A. G. P., Miao, J., et al. (2015). Artificial fish skin of self-powered micro-electromechanical systems hair cells for sensing hydrodynamic flow phenomena. Journal of the Royal Society, Interface, 12, 20150322. https://doi.org/10.1098/rsif.2015.0322.

    Article  Google Scholar 

  20. Coombs, S. (2001). Smart skins: Information processing by lateral line flow sensors. Autonomous Robots, 11, 255–261. https://doi.org/10.1023/A:1012491007495.

    Article  MATH  Google Scholar 

  21. Windsor, S. P., & McHenry, M. J. (2009). The influence of viscous hydrodynamics on the fish lateral-line system. Integrative and Comparative Biology, 49, 691–701. https://doi.org/10.1093/icb/icp084.

    Article  Google Scholar 

  22. McConney, M. E., Anderson, K. D., Brott, L. L., et al. (2009). Bioinspired material approaches to sensing. Advanced Functional Materials, 19, 2527–2544. https://doi.org/10.1002/adfm.200900606.

    Article  Google Scholar 

  23. Coombs, S., & Van Netten, S. (2005). The hydrodynamics and structural mechanics of the lateral line system. Fish Physiology, 23, 103–139.

    Article  Google Scholar 

  24. Tao, J., & Yu, X. B. (2012). Hair flow sensors: From bio-inspiration to bio-mimicking—A review. Smart Materials and Structures, 21, –113001. https://doi.org/10.1088/0964-1726/21/11/113001.

    Article  Google Scholar 

  25. Leitch, D. B., & Catania, K. C. (2012). Structure, innervation and response properties of integumentary sensory organs in crocodilians. The Journal of Experimental Biology, 215, 4217–4230. https://doi.org/10.1242/jeb.076836.

    Article  Google Scholar 

  26. Dehnhardt, G., Mauck, B., & Bleckmann, H. (1998). Seal whiskers detect water movements [6]. Nature, 394, 235–236.

    Article  Google Scholar 

  27. Williamson, C. H. K., & Govardhan, R. (2004). VORTEX-INDUCED VIBRATIONS. Annual Review of Fluid Mechanics. https://doi.org/10.1146/annurev.fluid.36.050802.122128.

    Article  MathSciNet  Google Scholar 

  28. Beem, H., Liu, Y., Barbastathis, G., & Triantafyllou, M. (2014). Vortex-induced vibration measurements of seal whiskers using digital holography. Ocean 2014 – Taipei. https://doi.org/10.1109/OCEANS-TAIPEI.2014.6964469.

  29. Hanke, W., Witte, M., Miersch, L., et al. (2010). Harbor seal vibrissa morphology suppresses vortex-induced vibrations. The Journal of Experimental Biology, 213, 2665–2672. https://doi.org/10.1242/jeb.043216.

    Article  Google Scholar 

  30. Beem, H. R., & Triantafyllou, M. S. (2015). Wake-induced “slaloming” response explains exquisite sensitivity of seal whisker-like sensors. Journal of Fluid Mechanics. https://doi.org/10.1017/jfm.2015.513.

    Article  MathSciNet  Google Scholar 

  31. Yang, Y., Chen, J., Engel, J., et al. (2006). Distant touch hydrodynamic imaging with an artificial lateral line. Proceedings of the National Academy of Sciences of the United States of America, 103, 18891–18895. https://doi.org/10.1073/pnas.0609274103.

    Article  Google Scholar 

  32. Chen, N., Tucker, C., Engel, J. M., et al. (2007). Design and characterization of artificial haircell sensor for flow sensing with ultrahigh velocity and angular sensitivity. Journal of Microelectromechanical Systems, 16, 999–1014. https://doi.org/10.1109/JMEMS.2007.902436.

    Article  Google Scholar 

  33. Bora, M., Kottapalli, A. G. P., Miao, J. M., & Triantafyllou, M. S. (2017). Fish-inspired self-powered microelectromechanical flow sensor with biomimetic hydrogel cupula. APL Materials, 5. https://doi.org/10.1063/1.5009128.

    Article  Google Scholar 

  34. Paull, L., Saeedi, S., Seto, M., & Li, H. (2014). AUV navigation and localization: A review. IEEE Journal of Oceanic Engineering, 39, 131–149. https://doi.org/10.1109/JOE.2013.2278891.

    Article  Google Scholar 

  35. Scalabrin, C., Marfia, C., & Boucher, J. (2009). How much fish is hidden in the surface and bottom acoustic blind zones? ICES Journal of Marine Science, 66, 1355–1363.

    Article  Google Scholar 

  36. Kanhere, E., Wang, N., Kottapalli, A. G. P., et al. (2016). Crocodile-inspired dome-shaped pressure receptors for passive hydrodynamic sensing. Bioinspiration & Biomimetics, 11. https://doi.org/10.1088/1748-3190/11/5/056007.

    Article  Google Scholar 

  37. Stocking, J. B., Eberhardt, W. C., Shakhsheer, Y. A., et al. (2010). A capacitance-based whisker-like artificial sensor for fluid motion sensing. In Proceedings of IEEE Sensors (pp. 2224–2229). Kona, HI, USA: IEEE.

    Google Scholar 

  38. Eberhardt, W. C., Shakhsheer, Y. A., Calhoun, B. H., et al. (2011). A bio-inspired artificial whisker for fluid motion sensing with increased sensitivity and reliability. In Proceedings of IEEE Sensors (pp. 982–985). Limerick, Ireland: IEEE.

    Google Scholar 

  39. Valdivia, Y., Alvarado, P., Subramaniam, V., & Triantafyllou, M. (2012). Design of a bio-inspired whisker sensor for underwater applications. In Proceedings of IEEE sensors. Taipei, Taiwan: IEEE.

    Google Scholar 

  40. Alvarado, P. V., Subramaniam, V., & Triantafyllou, M. (2013). Performance analysis and characterization of bio-inspired whisker sensors for underwater applications. In IEEE International Conference on Intelligent Robots and Systems (pp. 5956–5961). Tokyo, Japan: IEEE.

    Google Scholar 

  41. Eberhardt, W. C., Wakefield, B. F., Murphy, C. T., et al. (2016). Development of an artificial sensor for hydrodynamic detection inspired by a seal’s whisker array. Bioinspiration & Biomimetics, 11, 056011. https://doi.org/10.1088/1748-3190/11/5/056011.

    Article  Google Scholar 

  42. Kottapalli, A. G. P., Asadnia, M., Hans, H., et al. (2014). Harbor seal inspired MEMS artificial micro-whisker sensor. In Proceedings of the IEEE international conference on micro electro mechanical systems (MEMS). San Francisco, USA: IEEE.

    Google Scholar 

  43. Kottapalli, A. G. P., Asadnia, M., Miao, J. M., & Triantafyllou, M. S. (2015). Harbor seal whisker inspired flow sensors to reduce vortex-induced vibrations. In Proceedings of the IEEE international conference on micro electro mechanical systems (MEMS). Estoril, Portugal: IEEE.

    Google Scholar 

Download references

Acknowledgments

This research is supported by the National Research Foundation (NRF) Singapore under its Campus for Research Excellence and Technological Enterprise program. The Center for Environmental Sensing and Modeling (CENSAM) is an interdisciplinary research group of the Singapore-MIT Alliance for Research and Technology (SMART).

Author information

Authors and Affiliations

  1. Department of Advanced Production Engineering, Engineering and Technology Institute Groningen (ENTEG), Faculty of Science and Engineering, University of Groningen, Groningen, The Netherlands

    Debarun Sengupta & Ajay Giri Prakash Kottapalli

  2. Microsystems Research, School of Electrical Engineering and Telecommunications, The University of New South Wales, Kensington, Australia

    Ssu-Han Chen

  3. MIT Sea Grant College Programme, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA

    Ajay Giri Prakash Kottapalli

Authors
  1. Debarun Sengupta
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ssu-Han Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ajay Giri Prakash Kottapalli
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ajay Giri Prakash Kottapalli .

Rights and permissions

Reprints and permissions

Copyright information

© 2019 The Author(s), under exclusive licence to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Sengupta, D., Chen, SH., Kottapalli, A.G.P. (2019). Nature-Inspired Self-Powered Sensors and Energy Harvesters. In: Self-Powered and Soft Polymer MEMS/NEMS Devices. SpringerBriefs in Applied Sciences and Technology. Springer, Cham. https://doi.org/10.1007/978-3-030-05554-7_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-05554-7_3

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-05553-0

  • Online ISBN: 978-3-030-05554-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation