journal article·2021-04

A highly flexible, renewable and green alginate polymer for electroactive biological gel paper actuators reinforced with a double-side casting approach

Junjie Yang, Jintong Yao, Yingying Ma

Cellulose· Volume 28· Issue 6
Publisher page

Abstract

Biological gel paper actuators (BGPAs) constitute a rising class of electroactive smart artificial muscles with the advantages of large deformation and high energy density at low cost, and they are extensively used in areas such as soft robots, aerospace applications, and biomedical engineering. In this study, a double-side casting process and evaluation methods were proposed for manufacturing electroactive BGPAs and testing their output force characteristics. Furthermore, the effect and optimization mechanism of the double-side casting temperature on the output force performance and electrically activated mechanochemical behavior of a BGPA were studied in depth under single-cycle and repeated work periods. The experimental results demonstrated that when the casting temperature was 50 °C, various hydrogel membranes of BGPAs had optimal connections, with a penetration thickness of 6 μm, which reduced the interfacial contact resistance and drastically increased the quantity of interlayer hydrated ions. Moreover, the specific capacitance of this BGPA reached a maximum at 551.34 mF/g, but its elastic modulus, internal resistance and water loss rate all reached minimum values of 5.934 MPa, 1.91 Ω and 0.176%, respectively. Hence, the ideal values of the working life and output force density were similarly obtained for the BGPA, which were 891 s and 16.249 mN/g, respectively. In general, this optimized high-performance BGPA holds great value for the development and validation of natural smart polymers and engineering solutions.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Advanced Materials and Mechanics · Dielectric materials and actuators

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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