This research was supported by the Office of Naval Research through a US Naval Research Laboratory (NRL) 6.2 base program and performed while Kaushik Sampath was an employee of the Acoustics Division at NRL and Nicole Xu held an NRC Research Associateship award in the Laboratories for Computational Physics and Fluid Dynamics at NRL. The authors would like to acknowledge Dr. Ruben Hortensius (TSI Inc.) for technical support and guidance.

1. Fin fabrication
<ol>
	<li>Build a fin mold based on the desired shape design.
	<ol>
		<li>Design and build a custom 3D-printed gloss-finished mold of fin shape (Figure 1). See STL files for fabricating the mold in Supplementary Coding Files 1-4.</li>
		<li>Insert structural elements into the mold, such as a 3D-printed rigid plastic leading-edge spar. See the STL file of the spar in Supplementary Coding File 2.</li>
	</ol>
	</li>
	<li>Mix PDMS (see Table of Materials) in the desired part ratio.
	<ol>
		<li>Select the part ratio of base elastomer to curing agent (i.e., 10:1 or 20:1) to achieve higher or lower elastic modulus, respectively. Weigh the corresponding amounts of base and hardener. 
		NOTE: Both 10:1 and 20:1 (elastomer to curing agent) were used in the present study.</li>
		<li>Measure the fluorescent pigment (see Table of Materials) such that the total mixture contains 0.1%-1% pigment by weight, depending on the desired brightness of pigmentation. Add the pigment to the PDMS blend.</li>
		<li>Pour the measured amounts of elastomer, hardener, and pigment into a planetary centrifugal mixer (mixing at 423 x g for 30 s and de-aerating at 465 x g for 30 s) and mix accordingly.</li>
	</ol>
	</li>
	<li>Cast the fin in the mold.
	<ol>
		<li>Degas and pour the PDMS mixture into the mold for the fin. Place the mold into the oven at 70 &#176;C for 45 min, and let it cure overnight at 37 &#176;C.</li>
		<li>Once the curing is complete, remove the cast fin from the mold (Figure 2).</li>
	</ol>
	</li>
	<li>Perform tensile testing following the ASTM standard39.
	<ol>
		<li>For each fin cast in Step 1.3., cast one Type IV specimen using the same PDMS and pigment blend in a Type IV shaped mold using the previously described Steps 1.1.-1.3. 
		NOTE: See the STL files to cast the Type IV specimen in Supplementary Coding File 5 (mold shown in Figure 1C), and see Figure 3 for examples of the Type IV samples tested.</li>
		<li>Clamp the test specimen into the tensile testing machine (see Table of Materials). Measure the initial length, width, and thickness (mm) of the narrow sample section.</li>
		<li>Subject the test specimen to tension in 5 mm increments, ensuring that the sample remains stretched in the elastic region only, not overstretched. Decrease the tension in 5 mm increments until the total sample displacement is 0 mm (original position). Record the lengths (mm) and forces (N) of the narrow section at each increment.</li>
		<li>To calculate the elastic modulus of the sample, plot the stress-strain curve and determine the best linear fit and R2 value.</li>
	</ol>
	</li>
</ol>
2. Experimental setup and trials
<ol>
	<li>Mount the PLIF hardware (see Table of Materials) to a rectangular glass water tank (2.41 m&#160;x 0.76 m&#160;x 0.76 m).
	<ol>
		<li>Mount and use a pulsed laser system (see Table of Materials) to generate a planar light sheet intersecting the tank at its mid-plane at a specified frequency (30 Hz), as shown in Figure 4.</li>
		<li>Mount and use a 4 MP charge-coupled device (CCD) camera equipped with a lens (35 mm) and a longpass fluorescence filter (560 nm) (see Table of Materials).</li>
		<li>Calibrate the micrometer-to-pixel conversion by taking a single image from the CCD camera with a ruler placed in the laser sheet plane (Figure 5). Select two positions on the camera and divide the distance in micrometers by separating pixels. Ensure this micrometer-to-pixel ratio is small enough (sub-millimeter) for the application.</li>
	</ol>
	</li>
	<li>Synchronize the laser pulses and camera images with the flapping fin using trigger outputs from the fin software and signals from a delay generator and associated software (see Table of Materials) to coordinate the camera, laser heads, and fin motion. See Supplementary Figure 1 for an example of the delay generator software interface settings.
	<ol>
		<li>Set the laser system. 
		NOTE: Ensure all laser safety measures are in accordance with institutional guidelines.
		<ol>
			<li>Turn the laser system on by rotating the power key to the right to run the chiller that cools the laser heads. The fault light blinks until the system is ready to power the lasers. Do not press the power button that turns the lasers on until all laser modes are set correctly.</li>
			<li>Set the Trigger Source to EXT LAMP/EXT Q-SW (external lamp/external Q-switch).</li>
			<li>For both laser heads, set the laser energy to the desired level (i.e., approximately 60%-80% of the full power) and ensure that the Q-switch is turned on by pressing each Q-switch button.</li>
			<li>Turn the lasers on by pressing the Power button. 
			NOTE: As the Trigger Source is set to EXT LAMP/EXT Q-SW, the laser heads are ready to fire, but only fire after the system receives an external trigger from the software.</li>
		</ol>
		</li>
		<li>Set the camera.
		<ol>
			<li>Plug in the power cables to the camera and ensure proper connections to the computer and software.</li>
			<li>Open the camera settings software and select the proper port.
			<ol>
				<li>Under Trigger &#62; Settings, set &#34;Trigger in:&#34; to External and &#34;Mode:&#34; to Fast.</li>
				<li>Under Exposure, set &#34;Exposure Control&#34; to Off.</li>
			</ol>
			</li>
			<li>Open the camera capture software and select the proper camera card.
			<ol>
				<li>Click on the Grab Sequence button.</li>
				<li>Click on the Capture Settings button, select TIFF images, select Series of frames ..., and select the desired file path, 6 Digit Number, Continuous, and Accept.</li>
				<li>Click on Start Capture. 
				NOTE: As the camera settings are set to an external trigger, the camera is ready to collect images but only captures these images after the system receives an external trigger from the software.</li>
			</ol>
			</li>
		</ol>
		</li>
		<li>Set the delay generator.
		<ol>
			<li>Turn on the delay generator, and connect the External Gate Channel to the fin trigger, Channels A-D to the laser (A: laser head 1, B: Q-switch to laser 1, C: laser head 2, and D: Q-switch to laser 2), and Channel E to the camera.</li>
			<li>Open the delay generator software.</li>
			<li>Select the &#34;Pulse Mode&#34; to Burst and &#34;System Resolution&#34; to 4 ns.</li>
			<li>Set the &#34;Period (s)&#34; to 0.033333352.</li>
			<li>Set the &#34;External Trigger/Gate Mode&#34; to Triggered, &#34;Threshold (V)&#34; to 0.20, and &#34;Trigger Edge&#34; as Rising.</li>
			<li>On Channels &#62; Ch A, click on the Enabled checkbox. Set the &#34;Delay (s)&#34; to 0.000000004, &#34;Width (s)&#34; to 0.005000000, &#34;Amplitude (V)&#34; to 5.00, &#34;Channel Mode&#34; to Duty Cycle, &#34;Wait Count&#34; to 0, &#34;Sync Source&#34; to T0, &#34;Polarity&#34; to Normal, &#34;Multiplexer&#34; to A, &#34;Duty Cycle On&#34; to 1, &#34;Duty Cycle Off&#34; to 1, and &#34;Gate Mode&#34; to Disabled.</li>
			<li>On Channels &#62; Ch B, click on the Enabled checkbox. Set the &#34;Delay (s)&#34; to 0.000138000, &#34;Width (s)&#34; to 0.005000000, &#34;Amplitude (V)&#34; to 5.00, &#34;Channel Mode&#34; to Duty Cycle, &#34;Wait Count&#34; to 0, &#34;Sync Source&#34; to Ch A, &#34;Polarity&#34; to Normal, &#34;Multiplexer&#34; to B, &#34;Duty Cycle On&#34; to 1, &#34;Duty Cycle Off&#34; to 1, and &#34;Gate Mode&#34; to Disabled.</li>
			<li>On Channels &#62; Ch C, click on the Enabled checkbox. Set the &#34;Delay (s)&#34; to 0.033333304, &#34;Width (s)&#34; to 0.005000000, &#34;Amplitude (V)&#34; to 5.00, &#34;Channel Mode&#34; to Duty Cycle, &#34;Wait Count&#34; to 0, &#34;Sync Source&#34; to Ch A, &#34;Polarity&#34; to Normal, &#34;Multiplexer&#34; to C, &#34;Duty Cycle On&#34; to 1, &#34;Duty Cycle Off&#34; to 1, and &#34;Gate Mode&#34; to Disabled.</li>
			<li>On Channels &#62; Ch D, click on the Enabled checkbox. Set the &#34;Delay (s)&#34; to 0.000138000, &#34;Width (s)&#34; to 0.005000000, &#34;Amplitude (V)&#34; to 5.00, &#34;Channel Mode&#34; to Duty Cycle, &#34;Wait Count&#34; to 0, &#34;Sync Source&#34; to Ch C, &#34;Polarity&#34; to Normal, &#34;Multiplexer&#34; to D, &#34;Duty Cycle On&#34; to 1, &#34;Duty Cycle Off&#34; to 1, and &#34;Gate Mode&#34; to Disabled.</li>
			<li>On Channels &#62; Ch E, click on the Enabled checkbox. Set the &#34;Delay (s)&#34; to 0.000000004, &#34;Width (s)&#34; to 0.005000000, &#34;Amplitude (V)&#34; to 5.00, &#34;Channel Mode&#34; to Normal, &#34;Wait Count&#34; to 0, &#34;Sync Source&#34; to T0, &#34;Polarity&#34; to Normal, &#34;Multiplexer&#34; to E, and &#34;Gate Mode&#34; to Disabled.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Align the fin so the laser sheet passes through one chordwise section of the fin at a selected spanwise position and secure the fin platform with the mounting hardware.</li>
	<li>Connect the power to the fin control hardware and fin motors (see Table of Materials) to begin fin flapping with the selected kinematics, and turn off all ambient lights.</li>
	<li>Press Run in the delay generator software to begin the synchronized experiments and acquire images of the intersection of the laser sheet with the fin throughout the stroke cycle. This needs to be conducted over 200+ stroke cycles.</li>
	<li>Press Stop in the delay generator software and disconnect the fin from the power source.</li>
	<li>Move the fin platform so the laser sheet crosses at a new spanwise position and perform experiments to acquire the images again. Repeat Steps 2.3.-2.6. for the number of desired measurements (eight different spanwise positions, as shown by the black dashed lines in Figure 2A).</li>
	<li>Replace the fin with additional desired fin membranes (two fin stiffnesses, PDMS 10:1 and PDMS 20:1) and repeat the experiments.</li>
</ol>
3. Image analysis
<ol>
	<li>For each experimental trial conducted in Step 2.4., locate the file where the images are stored and create a subfolder for each fin position or phase throughout the stroke cycle. Sort the image files into their corresponding subfolders.</li>
	<li>For each fin phase subfolder, read the 200+ images as pixel-value arrays (imread.m). Sum the pixel-value arrays for all the images and divide by the number of images to generate a mean image. Write the image to a new file (imwrite.m). Repeat this step for each fin position throughout the stroke cycle (30 positions).</li>
	<li>Perform a histogram enhancement on each mean image (imadjust.m) to extend the dynamic intensity range of the images to the full available range to improve the contrast between the fin and background.</li>
	<li>Set the intensity thresholds and binarize each image to obtain a black-and-white image (imbinarize.m). The resulting white shapes should correspond to pieces of the fin cross-section.</li>
	<li>Extract all white objects (fin pieces) from the binary image (bwareafilt.m), and display the image (imshow.m). Create a trace of the binary image boundary for each image to obtain a 2D shape by selecting all the fin (white) pixels that touch the background (black) pixels (bwboundaries.m). 
	NOTE: Due to imposed fin kinematics, the view of the PLIF measured cross-section in some frames may be occluded by another part of the fin. In such cases, either there is no coherent fin shape apparent from the images, or only the leading edge (LE) remains visible (Figure 6).</li>
	<li>Perform Steps 3.1.-3.5. for each fin cross-section.</li>
</ol>
4. Reconstruction of 3D deflection
<ol>
	<li>Assuming that the LE position (at least closer to the stroke axis) in the flexible cases is the same as that of the LE in a rigid fin of the same shape, line the plane cuts along their LE for the same time-step, and compare with the results from the corresponding rigid fin shape.</li>
	<li>Use a least-squares fit to approximate the resulting centerline shape of the fin cross-section for all plane cuts and reconstruct the 3D fin shape using a simplified convex-hull from these fitted profiles.</li>
	<li>Compare the resulting fin shapes with 3D FSI models (generated from their centerlines) to showcase how this process can be used as high-fidelity validation.
	<ol>
		<li>Generate a surface triangulation of the partially rigid nylon and partially flexible PDMS fin.</li>
		<li>Use a commercial structural dynamics software (see Table of Materials) to obtain the eigenmodes of the hybrid material.
		<ol>
			<li>Perform scaling studies to match the steady-state displacement obtained using uniform pressure differential on the fin surfaces.</li>
			<li>Scale the modes to match the displacement obtained from the software.</li>
		</ol>
		</li>
		<li>With the proper scale factor, use the first few dominant modes (usually 7 or 8) employed in the coupled FSI solver to simulate the unsteady flow over the flexible fin.
		<ol>
			<li>Treat the body as an embedded entity in a background mesh. 
			NOTE: The coupled solver was validated for the Turek-Hron problem of flow over a circular cylinder with a flexible sting at the back35 and extended for flapping fin simulations36.</li>
			<li>Prescribe the kinematics of the fin motion from the experiments.</li>
			<li>Monitor the time history of the force production and the shape of the fin along several plane cuts throughout the flapping cycle, and compare with experiments.</li>
		</ol>
		</li>
	</ol>
	</li>
</ol>

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O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Vertically+migrating+swimmers+generate+aggregation-scale+eddies+in+a+stratified+column.">Vertically migrating swimmers generate aggregation-scale eddies in a stratified column.</a> Nature. 556 (7702), 497-500 (2018).</li><li>Mohaghar, M., Webster, D. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Characterization+of+non-linear+internal+waves+using+PIV/PLIF+techniques.">Characterization of non-linear internal waves using PIV/PLIF techniques.</a> 14th International Symposium on Particle Image Velocimetry. 1 (1), (2021).</li><li>Yue, Y., Zhang, H., Zhang, Z., Chen, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tensile+properties+of+fumed+silica+filled+polydimethylsiloxane+networks.">Tensile properties of fumed silica filled polydimethylsiloxane networks.</a> Composites Part A: Applied Science and Manufacturing. 54, 20-27 (2013).</li><li>Ramamurti, R., Geder, J., Viswanath, K., Lohner, R., Soto, O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Coupled CFD, structure and control tool for simulation of flapping wing analysis. , (2019).</li><li>Geder, J. 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Fourth edition. | Boca. , (2020).</li><li>L&#246;hner, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Applied Computational Fluid Dynamics Techniques: An Introduction Based on Finite Element Methods. , (2008).</li><li>D20 Committee. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Test Method for Tensile Properties of Plastics. , (2022).</li><li>Bai, K., Katz, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=On+the+refractive+index+of+sodium+iodide+solutions+for+index+matching+in+PIV.">On the refractive index of sodium iodide solutions for index matching in PIV.</a> Experiments in Fluids. 55 (4), 1704 (2014).</li></ol>

The authors have nothing to disclose.

Planar laser-induced fluorescence is typically used to visualize aqueous flows by seeding the fluid with dye, which fluoresces when exposed to a laser sheet25,26. However, using PLIF to visualize deformations in compliant materials has not been previously reported, and this study describes an approach for obtaining time history measurements of high-resolution shape deformation in flexible solid fins using PLIF. Comparing these fin measurements with FSI simulation...

In nature, many fish species have evolved to use a variety of body and fin motions to achieve locomotion. Research to identify the principles of fish locomotion has helped drive the design of bioinspired propulsion systems, as biologists and engineers have worked together to develop capable next-generation propulsion and control mechanisms for underwater vehicles. Various research groups have studied fin configurations, shapes, materials, stroke parameters, and surface curvature control techniques1,2,3,4,5,6,7,8,9,10,11,12. The importance of characterizing tip vortex generation and wake inclination to understand thrust generation in single- and multi-fin systems has been documented in numerous studies, both computational and experimental13,14,15,16,17,18. For fin mechanisms made of compliant materials, shown in various studies to reduce wake inclination and increase thrust17, it is also essential to capture and accurately model their deformation time-history to pair with the flow structure analysis. These results can then be used to validate computational models, inform fin design and control, and facilitate active research areas in unsteady hydrodynamic loading on flexible materials, which need validation19. Studies have used direct high-speed image-based shape tracking in shark fins and other complex objects20,21,22, but the complex 3D fin shape often blocks optical access, making it difficult to measure. Thus, there is a pressing need for a simple and effective method to visualize flexible fin motion.
A material widely used in compliant fin mechanisms is polydimethylsiloxane (PDMS) due to its low cost, ease of use, ability to vary stiffness, and compatibility with underwater applications23, as described extensively in a review by Majidi et al.24. In addition to these benefits, PDMS is also optically transparent, which is conducive to measurements using an optical diagnostic technique such as planar laser-induced fluorescence (PLIF). Traditionally within experimental fluid mechanics25, PLIF has been used to visualize fluid flows by seeding the fluid with dye or suspended particles or taking advantage of quantum transitions from species already in the flow that fluoresce when exposed to a laser sheet26,27,28,29. This well-established technique has been used to study fundamental fluid dynamics, combustion, and ocean dynamics26,30,31,32,33.
In the present study, PLIF is used to obtain spatiotemporally resolved measurements of shape deformation in flexible fish-inspired robotic fins. Instead of seeding the fluid with dye, the underwater kinematics of a PDMS fin are visualized at various chordwise cross-sections. Although planar laser imaging can be performed on regular cast PDMS without additional fluorescence, modifying PDMS to enhance fluorescence can improve the signal-to-noise ratio (SNR) of the images by reducing the effects of background elements, such as the fin mounting hardware. PDMS can be made fluorescent by employing two methods, either by fluorescent particle seeding or pigmentation. It has been reported that, for a given part ratio, the former alters the stiffness of the resultant cast PDMS34. Therefore, a nontoxic, commercially available pigment was mixed with transparent PDMS to cast fluorescent fins for the PLIF experiments.
To provide an example of using these fin kinematics measurements for computational model validation, the experimental kinematics are then compared with values from the coupled fluid-structure interaction (FSI) models of the fin. The FSI models used in the computations are based on the first seven eigenmodes computed using the measured material properties for the fins. Successful comparisons validate fin models and provide confidence in using the computational results for fin design and control. Further, the PLIF results demonstrate that this method can be used to validate other numerical models in future studies. Additional information about these FSI models can be found in prior work35,36 and in fundamental texts of computational fluid dynamics methods37,38. Future studies can also allow for simultaneous measurements of solid deformations and fluid flows for improved experimental studies of FSI in robotic fins, bioinspired soft robots, and other applications. Furthermore, because PDMS and other compatible elastomers are widely used in various fields, including sensors and medical devices, visualizing deformations in flexible solids using this technique can benefit a larger community of researchers in engineering, physics, biology, and medicine.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>ADMET controller</td>
			<td>ADMET</td>
			<td>MTESTQuattro</td>
			<td></td>
		</tr>
		<tr>
			<td>Axon II</td>
			<td>Society of Robots</td>
			<td></td>
			<td>Microcontroller for the fin hardware</td>
		</tr>
		<tr>
			<td>Berkeley Nucleonics Delay Generator</td>
			<td>Berkeley Nucleonics Corp</td>
			<td>Model 525</td>
			<td>BNC delay generator and software</td>
		</tr>
		<tr>
			<td>BobCat Cam Config</td>
			<td>Imperx</td>
			<td></td>
			<td>Camera settings software</td>
		</tr>
		<tr>
			<td>CCD camera</td>
			<td>Imperx</td>
			<td>B2340</td>
			<td>4 MegaPixel</td>
		</tr>
		<tr>
			<td>COMSOL</td>
			<td>COMSOL Inc</td>
			<td></td>
			<td>Commercial structural dynamics software for fluid-structure interaction modeling</td>
		</tr>
		<tr>
			<td>D646WP Servo</td>
			<td>Hitec</td>
			<td>36646S</td>
			<td>32-Bit, Digital, High Torque, Waterproof Servo for the fin pitch rotation</td>
		</tr>
		<tr>
			<td>D840WP Servo</td>
			<td>Hitec</td>
			<td>36840S</td>
			<td>32-Bit, Multi Purpose, Waterproof, Steel Gear Servo for the fin stroke rotation</td>
		</tr>
		<tr>
			<td>Electric Pink fluorescent pigment</td>
			<td>Silc Pig</td>
			<td>PMS812C</td>
			<td></td>
		</tr>
		<tr>
			<td>EverGreen (532 nm dual pulsed Nd:YAG laser system)</td>
			<td>Quantel</td>
			<td>EVG00070</td>
			<td>Laser head and power supply, 70 mJ</td>
		</tr>
		<tr>
			<td>Force transducer</td>
			<td>ADMET</td>
			<td>SM-10-961</td>
			<td>10 lbf load cell</td>
		</tr>
		<tr>
			<td>FrameLink Express</td>
			<td>Imperx</td>
			<td></td>
			<td>Camera capture software</td>
		</tr>
		<tr>
			<td>Longpass fluorescence filter</td>
			<td>Edmund Optics</td>
			<td></td>
			<td>560 nm</td>
		</tr>
		<tr>
			<td>MATLAB</td>
			<td>MathWorks</td>
			<td></td>
			<td>Software for image analysis</td>
		</tr>
		<tr>
			<td>Planetary centrifugal mixer</td>
			<td>THINKY MIXER</td>
			<td>AR-100</td>
			<td></td>
		</tr>
		<tr>
			<td>Silicone rubber compounds</td>
			<td>Momentive</td>
			<td>RTV615</td>
			<td>Clear PDMS</td>
		</tr>
		<tr>
			<td>Stratasys J750</td>
			<td>Stratasys</td>
			<td></td>
			<td>3D printer, polyjet</td>
		</tr>
		<tr>
			<td>Universal testing machine</td>
			<td>ADMET</td>
			<td>eXpert 2611</td>
			<td>Table top model</td>
		</tr>
		<tr>
			<td>VeroBlack</td>
			<td>Stratasys</td>
			<td></td>
			<td>3D printer material to build the molds</td>
		</tr>
		<tr>
			<td>VeroGray</td>
			<td>Stratasys</td>
			<td></td>
			<td>3D printer material to build the molds</td>
		</tr>
	</tbody>
</table>

flapping soft fin deformation modeling using planar laser-induced fluorescence imaging

Propulsive mechanisms inspired by the fins of various fish species have been increasingly researched, given their potential for improved maneuvering and stealth capabilities in unmanned vehicle systems. Soft materials used in the membranes of these fin mechanisms have proven effective at increasing thrust and efficiency compared with more rigid structures, but it is essential to measure and model the deformations in these soft membranes accurately. This study presents a workflow for characterizing the time-dependent shape deformation of flexible underwater flapping fins using planar laser-induced fluorescence (PLIF). Pigmented polydimethylsiloxane fin membranes with varying stiffnesses (0.38 MPa and 0.82 MPa) are fabricated and mounted to an assembly for actuation in two degrees of freedom: pitch and roll. PLIF images are acquired across a range of spanwise planes, processed to obtain fin deformation profiles, and combined to reconstruct time-varying 3D deformed fin shapes. The data are then used to provide high-fidelity validation for fluid-structure interaction simulations and improve the understanding of the performance of these complex propulsion systems.

A trapezoidal fish-inspired artificial pectoral fin was cast in two different materials (PDMS 10:1 and 20:1, both mixed with fluorescent dye) out of a mold, each with a rigid leading-edge spar inserted into the leading quarter chord (Figure 2 and Figure 3). Tensile testing of the two fin materials (Figure 3) yielded elastic moduli of 0.38 MPa and 0.82 MPa for the PDMS 20:1 and PDMS 10:1 fins, respectively, with an R2 of 0...

Watch this Scientific Journal Video about Flapping Soft Fin Deformation Modeling using Planar Laser-Induced Fluorescence Imaging at JoVE.com

Flapping Soft Fin Deformation Modeling using Planar Laser-Induced Fluorescence Imaging

The present protocol involves the measurement and characterization of 3D shape deformation in underwater flapping fins built with polydimethylsiloxane (PDMS) materials. Accurate reconstruction of these deformations is essential for understanding the propulsive performance of compliant flapping fins.

Propulsive mechanisms inspired by the fins of various fish species have been increasingly researched, given their potential for improved maneuvering and ...

flapping-soft-fin-deformation-modeling-using-planar-laser-induced

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Bioengineering

2.1K Views.  KS Research Inc. The present protocol involves the measurement and characterization of 3D shape deformation in underwater flapping fins built with polydimethylsiloxane (PDMS) materials. Accurate reconstruction of these deformations is essential for understanding the propulsive performance of compliant flapping fins.

Video: Flapping Soft Fin Deformation Modeling using Planar Laser-Induced Fluorescence Imaging

Diagnosis of Neoplasia in Barrett&#8217;s Esophagus using Vital-dye Enhanced Fluorescence Imaging

The ability to differentiate benign metaplasia in Barrett&#8217;s Esophagus (BE) from neoplasia in vivo remains difficult as both tissue types can be flat and indistinguishable with white light imaging alone. As a result, a modality that highlights glandular architecture would be useful to discriminate neoplasia from benign epithelium in the distal esophagus. VFI is a novel technique that uses an exogenous topical fluorescent contrast agent to delineate high grade dysplasia and cancer from benign epithelium. Specifically, the fluorescent images provide spatial resolution of 50 to 100 &#956;m&#160;and a field of view up to 2.5 cm,&#160;allowing endoscopists to visualize glandular morphology. Upon excitation, classic Barrett&#8217;s metaplasia appears as continuous, evenly-spaced glands and an overall homogenous morphology; in contrast, neoplastic tissue appears crowded with complete obliteration of the glandular framework. Here we provide an overview of the instrumentation and enumerate the protocol of this new technique. While VFI affords a gastroenterologist with the glandular architecture of suspicious tissue, cellular dysplasia cannot be resolved with this modality. As such, one cannot morphologically distinguish Barrett&#8217;s metaplasia from BE with Low-Grade Dysplasia via this imaging modality. By trading off a decrease in resolution with a greater field of view, this imaging system can be used at the very least as a red-flag imaging device to target and biopsy suspicious lesions; yet, if the accuracy measures are promising, VFI may become the standard imaging technique for the diagnosis of neoplasia (defined as either high grade dysplasia or cancer) in the distal esophagus.

Vital-dye enhanced fluorescence imaging (VFI) is a novel in vivo technique that combines high-resolution epithelial imaging with exogenous topical fluorescent contrast to highlight glandular morphology and delineate neoplasia (high grade dysplasia and cancer) in the distal esophagus.

The ability to differentiate benign metaplasia in Barrett&#8217;s Esophagus (BE) from neoplasia in vivo remains difficult as both tissue types can be flat ...

A Coupled Experiment-finite Element Modeling Methodology for Assessing High Strain Rate Mechanical Response of Soft Biomaterials

This study offers a combined experimental and finite element (FE) simulation approach for examining the mechanical behavior of soft biomaterials (e.g. brain, liver, tendon, fat, etc.) when exposed to high strain rates. This study utilized a Split-Hopkinson Pressure Bar (SHPB) to generate strain rates of 100-1,500 sec-1. The SHPB employed a striker bar consisting of a viscoelastic material (polycarbonate). A sample of the biomaterial was obtained shortly postmortem and prepared for SHPB testing. The specimen was interposed between the incident and transmitted bars, and the pneumatic components of the SHPB were activated to drive the striker bar toward the incident bar. The resulting impact generated a compressive stress wave (i.e. incident wave) that traveled through the incident bar. When the compressive stress wave reached the end of the incident bar, a portion continued forward through the sample and transmitted bar (i.e. transmitted wave) while another portion reversed through the incident bar as a tensile wave (i.e. reflected wave). These waves were measured using strain gages mounted on the incident and transmitted bars. The true stress-strain behavior of the sample was determined from equations based on wave propagation and dynamic force equilibrium. The experimental stress-strain response was three dimensional in nature because the specimen bulged. As such, the hydrostatic stress (first invariant) was used to generate the stress-strain response. In order to extract the uniaxial (one-dimensional) mechanical response of the tissue, an iterative coupled optimization was performed using experimental results and Finite Element Analysis (FEA), which contained an Internal State Variable (ISV) material model used for the tissue. The ISV material model used in the FE simulations of the experimental setup was iteratively calibrated (i.e. optimized) to the experimental data such that the experiment and FEA strain gage values and first invariant of stresses were in good agreement.

The current study prescribes a coupled experiment-finite element simulation methodology to obtain the uniaxial dynamic mechanical response of soft biomaterials (brain, liver, tendon, fat, etc.). The multiaxial experimental results that arose because of specimen bulging obtained from Split-Hopkinson Pressure Bar testing were rendered to a uniaxial true stress-strain behavior when simulated through iterative optimization of the finite element analysis of the biomaterial.

This study offers a combined experimental and finite element (FE) simulation approach for examining the mechanical behavior of soft biomaterials (e.g. ...

High-resolution Spatiotemporal Analysis of Receptor Dynamics by Single-molecule Fluorescence Microscopy

Single-molecule microscopy is emerging as a powerful approach to analyze the behavior of signaling molecules, in particular concerning those aspect (e.g., kinetics, coexistence of different states and populations, transient interactions), which are typically hidden in ensemble measurements, such as those obtained with standard biochemical or microscopy methods. Thus, dynamic events, such as receptor-receptor interactions, can be followed in real time in a living cell with high spatiotemporal resolution. This protocol describes a method based on labeling with small and bright organic fluorophores and total internal reflection fluorescence (TIRF) microscopy to directly visualize single receptors on the surface of living cells. This approach allows one to precisely localize receptors, measure the size of receptor complexes, and capture dynamic events such as transient receptor-receptor interactions. The protocol provides a detailed description of how to perform a single-molecule experiment, including sample preparation, image acquisition and image analysis. As an example, the application of this method to analyze two G-protein-coupled receptors, i.e., &#946;2-adrenergic and &#947;-aminobutyric acid type B (GABAB) receptor, is reported. The protocol can be adapted to other membrane proteins and different cell models, transfection methods and labeling strategies.

This protocol describes how to use total internal reflection fluorescence microscopy to visualize and track single receptors on the surface of living cells and thereby analyze receptor lateral mobility, size of receptor complexes as well as to visualize transient receptor-receptor interactions. This protocol can be extended to other membrane proteins.

Single-molecule microscopy is emerging as a powerful approach to analyze the behavior of signaling molecules, in particular concerning those aspect (e.g., ...

3D Orbital Tracking in a Modified Two-photon Microscope: An Application to the Tracking of Intracellular Vesicles

The objective of this video protocol is to discuss how to perform and analyze a three-dimensional fluorescent orbital particle tracking experiment using a modified two-photon microscope1. As opposed to conventional approaches (raster scan or wide field based on a stack of frames), the 3D orbital tracking allows to localize and follow with a high spatial (10 nm accuracy) and temporal resolution (50 Hz frequency response) the 3D displacement of a moving fluorescent particle on length-scales of hundreds of microns2. The method is based on a feedback algorithm that controls the hardware of a two-photon laser scanning microscope in order to perform a circular orbit around the object to be tracked: the feedback mechanism will maintain the fluorescent object in the center by controlling the displacement of the scanning beam3-5. To demonstrate the advantages of this technique, we followed a fast moving organelle, the lysosome, within a living cell6,7. Cells were plated according to standard protocols, and stained using a commercially lysosome dye. We discuss briefly the hardware configuration and in more detail the control software, to perform a 3D orbital tracking experiment inside living cells. We discuss in detail the parameters required in order to control the scanning microscope and enable the motion of the beam in a closed orbit around the particle. We conclude by demonstrating how this method can be effectively used to track the fast motion of a labeled lysosome along microtubules in 3D within a live cell. Lysosomes can move with speeds in the range of 0.4-0.5 &#181;m/sec, typically displaying a directed motion along the microtubule network8.

In this video protocol we track - at high speed and in three dimensions - fluorescently labeled lysosomes within living cells, using the orbital tracking method in a modified two-photon microscope.

The objective of this video protocol is to discuss how to perform and analyze a three-dimensional fluorescent orbital particle tracking experiment using a ...

From Fast Fluorescence Imaging to Molecular Diffusion Law on Live Cell Membranes in a Commercial Microscope

It has become increasingly evident that the spatial distribution and the motion of membrane components like lipids and proteins are key factors in the regulation of many cellular functions. However, due to the fast dynamics and the tiny structures involved, a very high spatio-temporal resolution is required to catch the real behavior of molecules. Here we present the experimental protocol for studying the dynamics of fluorescently-labeled plasma-membrane proteins and lipids in live cells with high spatiotemporal resolution. Notably, this approach doesn&#8217;t need to track each molecule, but it calculates population behavior using all molecules in a given region of the membrane. The starting point is a fast imaging of a given region on the membrane. Afterwards, a complete spatio-temporal autocorrelation function is calculated correlating acquired images at increasing time delays, for example each 2, 3, n repetitions. It is possible to demonstrate that the width of the peak of the spatial autocorrelation function increases at increasing time delay as a function of particle movement due to diffusion. Therefore, fitting of the series of autocorrelation functions enables to extract the actual protein mean square displacement from imaging (iMSD), here presented in the form of apparent diffusivity vs average displacement. This yields a quantitative view of the average dynamics of single molecules with nanometer accuracy. By using a GFP-tagged variant of the Transferrin Receptor (TfR) and an ATTO488 labeled 1-palmitoyl-2-hydroxy-sn-glycero-3-phosphoethanolamine (PPE) it is possible to observe the spatiotemporal regulation of protein and lipid diffusion on &#181;m-sized membrane regions in the micro-to-milli-second time range.

Spatial distribution and temporal dynamics of plasma membrane proteins and lipids is a hot topic in biology. Here this issue is addressed by a spatio-temporal image fluctuation analysis that provides conceptually the same physical quantities of single particle tracking, but it uses small molecular labels and standard microscopy setups.

It has become increasingly evident that the spatial distribution and the motion of membrane components like lipids and proteins are key factors in the ...

Single Molecule Fluorescence Microscopy on Planar Supported Bilayers

In the course of a single decade single molecule microscopy has changed from being a secluded domain shared merely by physicists with a strong background in optics and laser physics to a discipline that is now enjoying vivid attention by life-scientists of all venues 1. This is because single molecule imaging has the unique potential to reveal protein behavior in situ in living cells and uncover cellular organization with unprecedented resolution below the diffraction limit of visible light 2. Glass-supported planar lipid bilayers (SLBs) are a powerful tool to bring cells otherwise growing in suspension in close enough proximity to the glass slide so that they can be readily imaged in noise-reduced Total Internal Reflection illumination mode 3,4. They are very useful to study the protein dynamics in plasma membrane-associated events as diverse as cell-cell contact formation, endocytosis, exocytosis and immune recognition. Simple procedures are presented how to generate highly mobile protein-functionalized SLBs in a reproducible manner, how to determine protein mobility within and how to measure protein densities with the use of single molecule detection. It is shown how to construct a cost-efficient single molecule microscopy system with TIRF illumination capabilities and how to operate it in the experiment.

Preparation of protein-functionalized planar glass-supported lipid bilayers, determination of protein mobility within and measurement of protein densities is shown here. A roadmap to building a noise-reduced Total Internal Reflection microscope is outlined, which allows visualizing single bilayer-resident fluorochromes with high spatiotemporal resolution.

In the course of a single decade single molecule microscopy has changed from being a secluded domain shared merely by physicists with a strong background ...

Biomechanical Characterization of Human Soft Tissues Using Indentation and Tensile Testing

Regenerative medicine aims to engineer materials to replace or restore damaged or diseased organs. The mechanical properties of such materials should mimic the human tissues they are aiming to replace; to provide the required anatomical shape, the materials must be able to sustain the mechanical forces they will experience when implanted at the defect site. Although the mechanical properties of tissue-engineered scaffolds are of great importance, many human tissues that undergo restoration with engineered materials have not been fully biomechanically characterized. Several compressive and tensile protocols are reported for evaluating materials, but with large variability it is difficult to compare results between studies. Further complicating the studies is the often destructive nature of mechanical testing. Whilst an understanding of tissue failure is important, it is also important to have knowledge of the elastic and viscoelastic properties under more physiological loading conditions.
This report aims to provide a minimally destructive protocol to evaluate the compressive and tensile properties of human soft tissues. As examples of this technique, the tensile testing of skin and the compressive testing of cartilage are described. These protocols can also be directly applied to synthetic materials to ensure that the mechanical properties are similar to the native tissue. Protocols to assess the mechanical properties of human native tissue will allow a benchmark by which to create suitable tissue-engineered substitutes.

Tissue biomechanics is important for maintaining cell shape and function and for determining phenotype. This report demonstrates non-destructive mechanical protocols for characterizing elastic and viscoelastic properties of human soft tissues, which can be directly applied to tissue-engineered substrates to allow a close matching of engineered materials to native tissue.

Regenerative medicine aims to engineer materials to replace or restore damaged or diseased organs. The mechanical properties of such materials should ...

Stiffness Measurement of Soft Silicone Substrates for Mechanobiology Studies Using a Widefield Fluorescence Microscope

Soft tissues in the human body typically have stiffness in the kilopascal (kPa) range. Accordingly, silicone and hydrogel flexible substrates have been proven to be useful substrates for culturing cells in a physical microenvironment that partially mimics in vivo conditions. Here, we present a simple protocol for characterizing the Young's moduli of isotropic linear elastic substrates typically used for mechanobiology studies. The protocol consists of preparing a soft silicone substrate on a Petri dish or stiff silicone, coating the top surface of the silicone substrate with fluorescent beads, using a millimeter-scale sphere to indent the top surface (by gravity), imaging the fluorescent beads on the indented silicone surface using a fluorescence microscope, and analyzing the resultant images to calculate the Young's modulus of the silicone substrate. Coupling the substrate's top surface with a moduli extracellular matrix protein (in addition to the fluorescent beads) allows the silicone substrate to be readily used for cell plating and subsequent studies using traction force microscopy experiments. The use of stiff silicone, instead of a Petri dish, as the base of the soft silicone, enables the use of mechanobiology studies involving external stretch. A specific advantage of this protocol is that a widefield fluorescence microscope, which is commonly available in many labs, is the major equipment necessary for this procedure. We demonstrate this protocol by measuring the Young's modulus of soft silicone substrates of different elastic moduli.

Substrates with stiffness in the kilopascal-range are useful to study the response of cells to physiologically relevant micro-environment stiffness. Using just a widefield fluorescence microscope, the Young's modulus of soft silicone gels can be determined using an indentation with a suitable sphere.

Soft tissues in the human body typically have stiffness in the kilopascal (kPa) range. Accordingly, silicone and hydrogel flexible substrates have been ...

Visualizing Adhesion Formation in Cells by Means of Advanced Spinning Disk-Total Internal Reflection Fluorescence Microscopy

In living cells, processes such as adhesion formation involve extensive structural changes in the plasma membrane and the cell interior. In order to visualize these highly dynamic events, two complementary light microscopy techniques that allow fast imaging of live samples were combined: spinning disk microscopy (SD) for fast and high-resolution volume recording and total internal reflection fluorescence (TIRF) microscopy for precise localization and visualization of the plasma membrane. A comprehensive and complete imaging protocol will be shown for guiding through sample preparation, microscope calibration, image formation and acquisition, resulting in multi-color SD-TIRF live imaging series with high spatio-temporal resolution. All necessary image post-processing steps to generate multi-dimensional live imaging datasets, i.e. registration and combination of the individual channels, are provided in a self-written macro for the open source software ImageJ. The imaging of fluorescent proteins during initiation and maturation of adhesion complexes, as well as the formation of the actin cytoskeletal network, was used as a proof of principle for this novel approach. The combination of high resolution 3D microscopy and TIRF provided a detailed description of these complex processes within the cellular environment and, at the same time, precise localization of the membrane-associated molecules detected with a high signal-to-background ratio.

An advanced microscope that permit fast and high-resolution imaging of both, the isolated plasma membrane and the surrounding intracellular volume, will be presented. The integration of spinning disk and total internal reflection fluorescence microscopy in one setup allows live imaging experiments at high acquisition rates up to 3.5 s per image stack.

In living cells, processes such as adhesion formation involve extensive structural changes in the plasma membrane and the cell interior. In order to ...

3D Imaging of Soft-Tissue Samples using an X-ray Specific Staining Method and Nanoscopic Computed Tomography

We demonstrate a laboratory-based method combining X-ray microCT and nanoCT with a specific X-ray stain, which targets the cell cytoplasm. The described protocol is easy to apply, fast and suitable for larger soft-tissue samples. The presented methodology enables the characterization of crucial tissue structures in three dimensions and is demonstrated on a whole mouse kidney. The multiscale approach allows to image the entire mouse kidney and supports the selection of further volumes of interest, which are acquired with higher resolutions ranging into the nanometer range. Thereby, soft-tissue morphology with a similar detail level as the corresponding histological light microscopy images is reproduced. Deeper insights into the 3D configuration of tissue structures are achieved without impeding further investigations through histological methods.

A protocol for 3D visualization of microscopic tissue structures by using an X-ray specific staining method designed for X-ray computed tomography is presented.

We demonstrate a laboratory-based method combining X-ray microCT and nanoCT with a specific X-ray stain, which targets the cell cytoplasm. The described ...