Thermal Characterization of New 3D-Printed Bendable, Coplanar Capacitive Sensors

Area of Science:

• Materials Science
• Sensor Technology
• Additive Manufacturing

Background:

• Liquid level sensing is crucial in various industrial applications.
• Existing sensors can be costly, rigid, or lack adaptability.
• Need for low-cost, flexible, and reliable liquid level sensors.

Purpose of the Study:

• To develop and characterize a novel, low-cost, stretchable coplanar capacitive sensor.
• To assess the sensor's performance in measuring sunflower oil levels.
• To evaluate the sensor's flexibility and thermal stability for practical applications.

Main Methods:

• 3D printing using thermoplastic polyurethane (TPU) and conductive materials via fused filament fabrication (FFF).
• Testing sensor linearity, repeatability, and flexibility under bending stimuli.
• Conducting thermal characterization (10 °C to 40 °C) for oil level measurement.

Main Results:

• The sensor exhibited high linearity and good repeatability for sunflower oil level measurement.
• Negligible sensitivity to bending stimuli confirmed sensor flexibility.
• A model was developed to compensate for temperature effects on capacitance and oil level.

Conclusions:

• The 3D-printed stretchable capacitive sensor is a viable low-cost solution for liquid level sensing.
• The sensor demonstrates robustness against bending, suitable for flexible applications.
• Temperature compensation model enhances measurement accuracy in varying thermal conditions.