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Abstract When a water drop is placed onto a soft polymer network, a wetting ridge develops at the drop periphery. The height of this wetting ridge is typically governed by the drop surface tension balanced by elastic restoring forces of the polymer network. However, the situation is more complex when the network is swollen with fluid, because the fluid may separate from the network at the contact line. Here we study the fluid separation and network deformation at the contact line of a soft polydimethylsiloxane (PDMS) network, swollen with silicone oil. By controlling both the degrees of crosslinking and swelling, we find that more fluid separates from the network with increasing swelling. Above a certain swelling, network deformation decreases while fluid separation increases, demonstrating synergy between network deformation and fluid separation. When the PDMS network is swollen with a fluid having a negative spreading parameter, such as hexadecane, no fluid separation is observed. A simple balance of interfacial, elastic, and mixing energies can describe this fluid separation behavior. Our results reveal that a swelling fluid, commonly found in soft networks, plays a critical role in a wetting ridge.
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Parameter Estimation and Line Width Control of Robot Guided Inkjet Deposition
In the field of inkjet deposition, there is a lack of specific knowledge to detect and change drop volume to regulate fluid placement. In this paper, we present a novel control scheme to regulate drop diameter on a surface with unknown properties. We derive a model for line width as a function of nozzle velocity, valve duty cycle, and physical properties of fluid and surface. As many of these variables are generally unknown, we present a nonlinear estimator to estimate their cumulative effects as a single variable. Next, benefiting from our estimation knowledge, a closed-loop control method is designed to track a time-varying line width. Stability of both the estimator and control are established using Lyapunov stability theory, and the control is shown to be robust to errors in the estimator. Simulations and experimental results confirm the stability and performance of the approach.
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- Award ID(s):
- 1563424
- PAR ID:
- 10161914
- Date Published:
- Journal Name:
- 2018 Annual American Control Conference (ACC)
- Page Range / eLocation ID:
- 918 to 924
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.23919/ACC.2018.8431733
