Abstract
Shape morphing of liquid droplets is important for advances in both medical and industrial applications. However current manipulation techniques lack methods to control shapes other than elliptical-shaped droplets. Here we propose using Long Short-Term Memory (LSTM) based model to learn and predict the evolution of the shape of a non-magnetic liquid droplet at an air-ferrofluid interface deformed with programmed sequential actuation of electromagnets. The resulting droplet shapes can be convex or concave. We can also predict the actuation sequences for a given shape sequence with an accuracy of 79.1 %. The proposed method could also be applied to a variety of other liquid droplet shape-morphing systems which utilize arrays of electromagnetic or electric actuators.
Original language | English |
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Title of host publication | 2023 International Conference on Manipulation, Automation and Robotics at Small Scales (MARSS) |
Editors | Sinan Haliyo, Mokrane Boudaoud, Mohammad A. Qasaimeh, Sergej Fatikow |
Publisher | IEEE |
Pages | 1-6 |
Number of pages | 6 |
ISBN (Electronic) | 979-8-3503-3039-7 |
ISBN (Print) | 979-8-3503-3040-3 |
DOIs | |
Publication status | Published - 13 Oct 2023 |
MoE publication type | A4 Conference publication |
Event | International Conference on Manipulation, Automation and Robotics at Small Scales - Abu Dhabi, United Arab Emirates Duration: 9 Oct 2023 → 13 Oct 2023 |
Conference
Conference | International Conference on Manipulation, Automation and Robotics at Small Scales |
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Abbreviated title | MARSS |
Country/Territory | United Arab Emirates |
City | Abu Dhabi |
Period | 09/10/2023 → 13/10/2023 |
Keywords
- Adaptation models
- Magnetic flux density
- Actuators
- Liquids
- Shape
- Atmospheric modeling
- Magnetic liquids