This readme.txt file was generated on <20211215> by Recommended citation for the data: Lauser, Kathleen T; Calabrese, Michelle A. (2022). Capillary thinning analysis. Retrieved from the Data Repository for the University of Minnesota, https://doi.org/10.13020/gkz4-8z17. ------------------- GENERAL INFORMATION ------------------- 1. Title of Dataset Capillary thinning analysis 2. Author Information Principal Investigator Contact Information Name: Michelle Calabrese Institution: University of Minnesota Address: 421 Washington Ave SE #250, Minneapolis, MN 55455, Office 306 Email: mcalab@umn.edu ORCID: 0000-0003-4577-6999 Author Contact Information Name: Kathleen Lauser Institution: University of Minnesota Address: 421 Washington Ave SE #250, Minneapolis, MN 55455, Office 336 Email: lause017@umn.edu ORCID: 0000-0001-8780-9803 3. Date published or finalized for release: 03Jan2022 4. Date of data collection (single date, range, approximate date) 2019NOV to 2021DEC 5. Geographic location of data collection (where was data collected?): Minneapolis, Minnesota 6. Information about funding sources that supported the collection of the data: This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. CON-75851, project 00074041. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation 7. Overview of the data (abstract): This collection of scripts is a package for analyzing extensional rheology data of liquid bridges. While this was created with Dripping-onto-Substrate datasets, this data analysis package may be useful for other liquid bridge thinning applications such as CaBER. Any pre-processing of images, such as binarizing, converting to png or cropping, can be completed with ImageJ. The data analysis package is composed of three distinct scripts designed to be run in Matlab with png image files. ContactAngle.m measures the contact angle of a liquid bridge and the spreading distance on the substrate for a series of images during liquid bridge thinning. Startpoint_Symmetry finds the minimum radius for a series of liquid bridge thinning images, identifies the start and end point of thinning, and gives information about the overall symmetry of the trials. EC_binning identifies the fitting region, fits and reports relaxation time for elastocapillary thinning fluids. For all three scripts, an example dataset is provided to demonstrate script functionality. -------------------------- SHARING/ACCESS INFORMATION -------------------------- 1. Licenses/restrictions placed on the data: one year of restricted access (upload to drum but ask author permission before accessing) CC0 1.0 Universal 2. Links to publications that cite or use the data: N/A 3. Was data derived from another source? Partially If yes, list source(s): https://www.mathworks.com/matlabcentral/answers/417963-how-to-clean-up-and-refine-edges-of-this-image ContactAngle.m code is partially adapted from this code (lines 89-155,410-439 are the same section of code but repeated twice, lines 507-541 is associated function used). This section is used to the Solisky Golay filter to smooth the curve and identify the boundary of the droplet. However, the determination of the contact angle and spreading distance, the application of this code, are all novel. 4. Terms of Use: Data Repository for the U of Minnesota (DRUM) By using these files, users agree to the Terms of Use. https://conservancy.umn.edu/pages/drum/policies/#terms-of-use --------------------- DATA & FILE OVERVIEW --------------------- 1. File List A. Filename: ContactAngle.m Short description: This code analyzes the contact angle and spreading of a liquid bridge for capillary thinning. Inputs needed are a folder of 8 bit images of the bottom of sphere of the liquid bridge on the substrate (substrate and actual liquid bridge should be cropped out) saved as .png images. Each image should be saved with a five-digit number in the form “00001.png” to the number of images needed. Images from trial 1 should be in a folder marked “1”, trial 2 marked “2”, etc., and this code should be saved in the directory that contains all the trial folders. Only one trial however can be analyzed at a time. This code finds the boundary of the lower hemispherical section of the liquid bridge on the substrate. A threshold parameter is adjusted by the user to properly capture the boundary. The distance on the substrate or plate is measured and reported as a function of time as the spreading difference. Then, a user inputted range of points above the contact point on the right and left side is fit to a polynomial, and a derivative and tangent line are fit. The angle between the left and right tangent line and a horizontal is reported as the contact angle. The outputs are a series of 6 figures that will automatically generate after the code is run. Two figures show a visualization of boundary fitting around the droplet of the first and last image, which is helpful for troubleshooting (thresholding likely needs to be adjusted if the boundary is not fit around the droplet correctly). Figures 2 and 3 show the goodness of fit of the polynomial and the residuals of fit for the contact angle determination for the last image, also useful for troubleshooting because you can compare the effect of changing parameters such as degree of polynomial, thresholding, number of points in fit in consecutive runs. The last two figures (5 and 6) show how the spreading on the substrate and contact angle of the droplet respectively change in time. B. Filename: Startpoint_Symmetry Short description: This code measures the minimum radius of the liquid bridge as a function of time, identifies the start and endpoint of thinning, and analyzes the symmetry of a liquid bridge for capillary thinning. Inputs needed are a folder of binarized images of the liquid bridge saved as .png images. Note that Matlab interprets “0” as black and “1” as white, and assumes that the liquid bridge will be white, although user images can be easily inverted if needed. Each image should be saved with a five-digit number in the form “00001.png” to the number of images needed. Images from trial 1 should be in a folder marked “1”, trial 2 marked “2”, etc., and this code should be saved in the directory that contains all the trial folders. Multiple files can be analyzed at once. For startpoint and minimum radius analysis, the output is a R_vs_t.csv file of radius by time data that fully capture the thinning process. By automating startpoint selection, different trials begin at similar points so that different trials can be compared. Additionally, the script automatically crops so only the liquid bridge is analyzed, and the CropStaus.csv gives an output of “1” if a crop was performed and “0” if no crop was performed for a trial image set. For symmetry analysis, the output is a normalized symmetry value based on the difference of the residuals from the left and right side of the liquid bridge. This symmetry value can be used to quantitatively compare symmetry between trials and as a metric to determine which trials should be included in a dataset. C. Filename:EC_binning.m Short description:This script identifies and fits the elastocapillary (EC) thinning region. The data must have an EC region in order for this script to function. Outputs include the extensional relaxation time, and graphs that assess the goodness of fit of the script, such as residual plots. This script first reads in capillary thinning data for time and radius (can be directly take the values from R_vs_t.csv or another source.) The data is broken into bins, with each bin containing a set number of points (bin size) and a set distance between each bin (step size, bins can be overlapping). An exponential fit in the form y=a*exp(bx) (linear on a semilog scale of the form ln(y/a)=bx ) is applied to each bin. The "b" values are then plotted for each bin. For the EC regime, the b value is constant; therefore the script compares the slope of each bin to the bins around it, and groups bins together if the slope of the bin matches the bin within a user defined tolerance. The slope identifies the largest number of consecutive bins that all have the same slope within tolerance as the EC fitting region and reports the relaxation time. The number of bins graphed by the slope is also shown graphically in figure 1 so the user can determine if too few or too many bins were used and then adjust bin size and/or stepsize in subsequent runs of code. Additionally, the fit can be assessed by examining residual plot outputs (figure 4 and 6)- if there is data that is mostly above or below the fit; tolerance, step size and/or bin width can be changed in subsequent runs of the script until the data is re-binned as desired. Figure 2 shows the raw data that is identified as the EC fitting region by the code, while Figure 3 shows the same raw data with the fit, with the vertical lines representing the bins of points. Lastly, figure 5 shows the entire raw data set plotted radius by time. 2. Relationship between files: All of the scripts analyze a different component of liquid bridge thinning. -------------------------- METHODOLOGICAL INFORMATION -------------------------- 1. Description of methods used for collection/generation of data: Dripping-onto-substrate (DoS) instrument. An instrument for measuring the extensional rheology of low viscosity fluids. More information about the DoS methods can be found here:https://doi.org/10.1039/D1SM01253C 2. Methods for processing the data: : Raw images of capillary thinning were captured with a high-speed camera and saved as .DNG files. The frames per second (FPS) of the high-speed camera was recorded for each capillary thinning trial. Using an image processing program such as ImageJ, these images were converted to .png. The images were analyzed using the attached and annotated Matlab processing codes. 3. Instrument- or software-specific information needed to interpret the data: Matlab (required) with signal, image, curve fitting,and statistics toolboxes installed, ImageJ (recommended for image processing) This code was designed for Windows users. For macOS users, please replace the myfolder variable with myfolder=sprintf('%s/%d',pwd,foldernames); 4. Standards and calibration information, if appropriate: N/A 5. Environmental/experimental conditions: Experimental instrumentation is described here: here:https://doi.org/10.1039/D1SM01253C 6. Describe any quality-assurance procedures performed on the data: N/A 7. People involved with sample collection, processing, analysis and/or submission: Kathleen Lauser- responsible for code creation and data collection of the example data Michelle Calabrese- Principal Investigator responsible for overseeing project direction ----------------------------------------- DATA-SPECIFIC INFORMATION FOR: Contactangle.m ----------------------------------------- Images required: 8-bit .png images cropped so that only the bottom hemisphere of the liquid bridge is visibile. (see example data) Input Variable List fontSize: font size for graphs CAfolder: the folder of the trial user wants to analyze. fps: frame rate for the trial to analyze needlewidth: the width in pixels of the needle, noozle or upper plate that forms the top boundary of the liquid bridge thresholdValue:threshold value needed to detect the boundary of the image. Adjust upwards if the entire image is black, adjust downwards if the entire images is white until the liquid bridge on substrate is visible when thresholded lastimagechoice: keep this as 0 unless want to end at a different image. Ensure last image has the contact angle in the frame fitrange: number of point in the fitting range for contact angle PixelsAwayFromContactPt: starting directly at the contact point and fitting a polynomial directly above the substrates can often give issues with slope if lighting is poor. Fitting a polynomial around 5-10 pixels away from the substrate likely gives a better contact angle estimate degreeofpoly:degree of polynomial. Recommended to keep between 2-8 for robust fitting firstimage: keep this as 1 unless user wants to start at a different first image to measure contact angle and spreading ----------------------------------------- DATA-SPECIFIC INFORMATION FOR: Startpoint_Symmetry.m ----------------------------------------- Images required: Binary.png images of liquid bridge. Substrate can be included if desired, but will be automatically cropped out by the code if included. Input Variable List fontSize: font size startfolder: the first folder of the trial(s) to analyze. If startfolder=0 or 1, it will default the first folder in the directory endfolder: the last folder of the trial(s) to analyze. If endfolder=0, it will default to the last numerical folder in the directory. The startfolder and end folder can be the same if only analyzing 1 trial fps: matrix of all the frames rates, should always same size as the total number of folders in the directory, regardless of how many are currently being analyzed namethefile: gives the file name for the radius by time data a unique timestamp so user cannot save over previous versions if this code is run multiple times. Can get rid of timestamp if user wants file to overwrite itself for each run ----------------------------------------- DATA-SPECIFIC INFORMATION FOR: EC_binning.m ----------------------------------------- Images required: none Input Variable List binwidth: number of points for each bin that will be fit stepsize: where the next range of points starts.if binwidth>stepsize, bins will overlap. if binwidth=stepsize, bins will not overlap. Stepsize should not be greater than binwidth. Example: iff the binwidth is 15 and the step size is 10, the first bin is the first 15 points. The second bin has 15 points, but the first 5 points are the last 5 points in the previous bin, and the next 10 points are "new" points in the fitting/binning tol: sets the tolerances for how closely slope values must match across bins. Raise to include more points included in the fit, lower to decrease number of points vidspeed: speed of the video, number of frame rates data: input radius by time data in a matrix with time data in column 1 and normalized radius data in column 2. This can be directly copied from the Startpoint_Symmetry Code output, but must have an EC region to analyze. An example dataset using 0.5 wt.% PEO is shown for reference