Three-Layered Design of Electrothermal Actuators for Minimal Voltage Operation

By designing an actuator composed of thin layers with different coefficients of thermal expansion (CTE) together with an electrically conductive layer, the CTE mismatch can be utilized to produce soft electrothermal actuators (ETAs). These actuators have been typically implemented using only two layers, commonly relying on Timoshenko's analytic model that correlates the temperature to the actuator's curvature. In this study, we extend the analytic model to include the thermoelectric relation present in ETAs, that is, the conductive layer's properties with respect to the operation temperature. By applying the thermoelectric relation, a minimal voltage optimization can be applied to the analytic model. Using dimensionless analysis, we optimize the ETAs performance for both bi- and tri-layer ETAs with and without the thermal modeling. The bi-layer optimization not only predicts the maximal value for the bi-layer performance but also provides the optimal thickness of each layer for any couple of materials. We validate the tri-layer analytic model experimentally by measuring the curvature for different third layer thicknesses. Finally, we optimize the tri-layer design based on the analytic model, which can achieve an improvement in curvature per voltage of >3000% over the optimal bi-layer ETA.

Medienart:

E-Artikel

Erscheinungsjahr:

2020

Erschienen:

2020

Enthalten in:

Zur Gesamtaufnahme - volume:7

Enthalten in:

Soft robotics - 7(2020), 5 vom: 08. Okt., Seite 649-662

Sprache:

Englisch

Beteiligte Personen:

Tibi, Gal [VerfasserIn]
Sachyani Keneth, Ela [VerfasserIn]
Layani, Michael [VerfasserIn]
Magdassi, Shlomo [VerfasserIn]
Degani, Amir [VerfasserIn]

Links:

Volltext

Themen:

Electrothermal actuators
Journal Article
Minimal voltage actuation
Soft actuators
Thermal expansion actuation

Anmerkungen:

Date Revised 23.10.2020

published: Print-Electronic

Citation Status PubMed-not-MEDLINE

doi:

10.1089/soro.2018.0160

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM307483444