Bio-inspired all-optical artificial neuromast for 2D flow sensing

Wolf, Ben; Morton, Jonathan; MacPherson, William N.; Netten, Sietse M. van

doi:10.1088/1748-3190/aaa786

Cited by 54 publications

(62 citation statements)

References 29 publications

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“…In most of the cases, the sensors comprised of high-aspect-ratio polymeric pillars mimicking cilia, with piezoresistive or piezoelectric sensing membranes at the bases. Some other artificial cilia flow sensors, involving hot wire anemometry and optical sensing, have also been explored by various researchers [10,11]. Inspired by biological hair cells, Chen et al [5] developed an artificial hair cell flow sensor comprising of a silicon cantilever beam with a 700 µm tall, high-aspect-ratio SU-8 pillar at its distal tip.…”

Section: Introductionmentioning

confidence: 99%

Piezoresistive Carbon Nanofiber-Based Cilia-Inspired Flow Sensor

2020

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Evolving over millions of years, hair-like natural flow sensors called cilia, which are found in fish, crickets, spiders, and inner ear cochlea, have achieved high resolution and sensitivity in flow sensing. In the pursuit of achieving such exceptional flow sensing performance in artificial sensors, researchers in the past have attempted to mimic the material, morphological, and functional properties of biological cilia sensors, to develop MEMS-based artificial cilia flow sensors. However, the fabrication of bio-inspired artificial cilia sensors involves complex and cumbersome micromachining techniques that lay constraints on the choice of materials, and prolongs the time taken to research, design, and fabricate new and novel designs, subsequently increasing the time-to-market. In this work, we establish a novel process flow for fabricating inexpensive, yet highly sensitive, cilia-inspired flow sensors. The artificial cilia flow sensor presented here, features a cilia-inspired high-aspect-ratio titanium pillar on an electrospun carbon nanofiber (CNF) sensing membrane. Tip displacement response calibration experiments conducted on the artificial cilia flow sensor demonstrated a lower detection threshold of 50 µm. Furthermore, flow calibration experiments conducted on the sensor revealed a steady-state airflow sensitivity of 6.16 mV/(m s−1) and an oscillatory flow sensitivity of 26 mV/(m s−1), with a lower detection threshold limit of 12.1 mm/s in the case of oscillatory flows. The flow sensing calibration experiments establish the feasibility of the proposed method for developing inexpensive, yet sensitive, flow sensors; which will be useful for applications involving precise flow monitoring in microfluidic devices, precise air/oxygen intake monitoring for hypoxic patients, and other biomedical devices tailored for intravenous drip/urine flow monitoring. In addition, this work also establishes the applicability of CNFs as novel sensing elements in MEMS devices and flexible sensors.

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Section: Introductionmentioning

confidence: 99%

Piezoresistive Carbon Nanofiber-Based Cilia-Inspired Flow Sensor

2020

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“…The additional FBG on each sensor is used in order to form a square cross-section structure. This concept has already been reported in literature [8,9] however here we explore the use of several sensing elements to extend the operating range of the overall system. In the intended application of this attitude senor the design is motivated by the need to determine the orientation of a subsea structure.…”

Section: Introductionmentioning

confidence: 91%

Fibre Bragg Grating based Attitude Sensor

Papachristou

Morton

Dzipalski

et al. 2018

26th International Conference on Optical Fiber Sensors

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We present a system of three Fibre Bragg Grating (FBG) curvature sensors configured as a multi-axis attitude sensor. The FBG response on each sensor provides information about its deflection due to gravity acting on a sensing mass. The three sensor system can be processed to give 3-D attitude information with an accuracy of ±2° demonstrated. The fabrication, calibration and performance of the sensors is discussed.

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“…The effectiveness and versatility of the lateral line organ has yielded several bio-inspired artificial flow sensors [29][30][31][32][33]. Arranging these sensors in arrays on artificial swimmers has attracted attention to transform underwater sensing [3,[34][35][36][37][38][39].…”

Section: Introductionmentioning

confidence: 99%

Optimal Flow Sensing for Schooling Swimmers

et al. 2020

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Fish schooling implies an awareness of the swimmers for their companions. In flow mediated environments, in addition to visual cues, pressure and shear sensors on the fish body are critical for providing quantitative information that assists the quantification of proximity to other fish. Here we examine the distribution of sensors on the surface of an artificial swimmer so that it can optimally identify a leading group of swimmers. We employ Bayesian experimental design coupled with numerical simulations of the two-dimensional Navier Stokes equations for multiple self-propelled swimmers. The follower tracks the school using information from its own surface pressure and shear stress. We demonstrate that the optimal sensor distribution of the follower is qualitatively similar to the distribution of neuromasts on fish. Our results show that it is possible to identify accurately the center of mass and the number of the leading swimmers using surface only information.

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Bio-inspired all-optical artificial neuromast for 2D flow sensing

Cited by 54 publications

References 29 publications

Piezoresistive Carbon Nanofiber-Based Cilia-Inspired Flow Sensor

Piezoresistive Carbon Nanofiber-Based Cilia-Inspired Flow Sensor

Fibre Bragg Grating based Attitude Sensor

Optimal Flow Sensing for Schooling Swimmers

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