Research Papers

A Dynamical Model of Drop Spreading in Electrohydrodynamic Jet Printing

[+] Author and Article Information
Christopher P. Pannier

Department of Mechanical Engineering,
University of Michigan,
Ann Arbor, MI 48109
e-mail: pannier@umich.edu

Mamadou Diagne

Department of Mechanical, Aerospace, and
Nuclear Engineering,
Rensselaer Polytechnic Institute,
Troy, NY 12180

Isaac A. Spiegel, Kira Barton

Department of Mechanical Engineering,
University of Michigan,
Ann Arbor, MI 48109

David J. Hoelzle

Department of Mechanical and
Aerospace Engineering,
The Ohio State University,
Columbus, OH 43210

1Corresponding author.

Manuscript received May 18, 2017; final manuscript received July 13, 2017; published online September 13, 2017. Assoc. Editor: Zhijian J. Pei.

J. Manuf. Sci. Eng 139(11), 111008 (Sep 13, 2017) (6 pages) Paper No: MANU-17-1329; doi: 10.1115/1.4037436 History: Received May 18, 2017; Revised July 13, 2017

Electrohydrodynamic jet (e-jet) printing is a microscale additive manufacturing technique used to print microscale constructs, including next-generation biological and optical sensors. Despite the many advantages to e-jet over competing microscale additive manufacturing techniques, there do not exist validated models of build material drop formation in e-jet, relegating process design and control to be heuristic and ad hoc. This work provides a model to map deposited drop volume to final spread topography and validates this model over the drop volume range of 0.68–13.4 pL. The model couples a spherical cap volume conservation law to a molecular kinetic relationship for contact line velocity and assumes an initial contact angle of 180 deg to predict the drop shape dynamics of dynamic contact angle and dynamic base radius. For validation, the spreading of e-jet-printed drops of a viscous adhesive is captured by high-speed microscopy. Our model is validated to have a relative error less than 3% in dynamic contact angle and 1% in dynamic base radius.

Copyright © 2017 by ASME
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Fig. 1

Schematic of an e-jet printing system actuated by a pulsed voltage, with images of build material meniscus, jet, and drop

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Fig. 2

At left: cropped high-speed images of a drop of volume Ω=7.5 pL and printing parameters Vh=1200 V, Tp=2.4 ms with automatically identified θ(t) and R(t) at two different time points. At right: renderings of spherical caps describing the drops, with a 1/3 section cutaway.

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Fig. 3

The e-jet printer with a dashed white line showing a reflection axis and white rays showing the light path. Brightness and contrast have been enhanced around the nozzle.

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Fig. 4

Each of 45 shaded bins indicates a 20-drop data set collected with the plotted Vh and Tp e-jet printing inputs. Inset at top right: drop volume versus printing inputs.

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Fig. 5

Equation (5) is fitted to the collected data to obtain model parameters κ and λ using robust nonlinear least squares regression

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Fig. 6

Measured R¯(t) and simulated R*(t) are plotted for three (Vh, Tp) pairs

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Fig. 7

Relative error in the simulated θ*(t) and R*(t) is plotted for each (Vh, Tp) pair, with i = 1. Inset is the relative error averaged over all 45 (Vh, Tp) pairs with the average e(θ*) (filled circles) and the average e(R*) (filled squares) plotted for varying number of excluded initial frames i.




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