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Development, design and applications of structural capacitors

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  • Chung, D.D.L.

Abstract

Structural capacitors are multifunctional structural materials that provide the capacitor function for the purpose of electrical energy storage. This paper reviews the development of structural capacitors and enunciates their design and applications. A structural capacitor is commonly a polymer-matrix structural composite with a dielectric film between the electrodes, which are an electronic conductor, commonly the continuous carbon fiber laminae that serve to reinforce the composite. The dielectric film is preferably small in thickness and serves to avoid short circuiting of the two electrodes. In order to maximize the capacitance by having the structural capacitor constitute capacitors in parallel, the dielectric film is preferably positioned at every interlaminar interface of the composite, such that alternating electrodes in the stack are connected to opposite polarities of the AC electric field source. A structural supercapacitor requires the matrix to be a solid electrolyte. From the viewpoints of structural performance, safety, service life and high frequency capability, structural dielectric capacitors are closer to commercialization readiness than structural supercapacitors. Structural capacitors have not yet been commercialized, but they are expected to provide an untapped, extensive, save and distributed means of energy storage, and allow aircraft, satellites, automobile, ships, wind turbines, buildings, solar panels, display panels, outdoor lighting, computers, cell phones, etc., to store energy in their structures.

Suggested Citation

  • Chung, D.D.L., 2018. "Development, design and applications of structural capacitors," Applied Energy, Elsevier, vol. 231(C), pages 89-101.
  • Handle: RePEc:eee:appene:v:231:y:2018:i:c:p:89-101
    DOI: 10.1016/j.apenergy.2018.09.132
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    Cited by:

    1. Xi, Xiang & Chung, D.D.L., 2020. "Deviceless cement-based structures as energy sources that enable structural self-powering," Applied Energy, Elsevier, vol. 280(C).
    2. Yi, Yong & Wang, Liming & Chen, Zhengying, 2021. "Adaptive global kernel interval SVR-based machine learning for accelerated dielectric constant prediction of polymer-based dielectric energy storage," Renewable Energy, Elsevier, vol. 176(C), pages 81-88.

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