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Power-on-paper: Origami-inspired fabrication of 3-D microbial fuel cells

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  • Mohammadifar, M.
  • Zhang, J.
  • Yazgan, I.
  • Sadik, O.
  • Choi, S.

Abstract

We demonstrate that fabricating low-cost microbial fuel cells (MFCs) can be done efficiently by using a paper substrate and origami techniques. A 3-D MFC was developed from a 2-D sheet of paper by integrating the anode, reservoir, cation exchange membrane (CEM) and air-cathode. The cell was easily formed by folding the paper along pre-defined creases. The entirely paper-based all-printed MFC developed in this work rapidly generated power with a small amount of bacteria-containing liquid through rapid adsorption and instant attachment of the bacteria cells to the anode. A graphite-polymer composite and graphite ink with activated carbon were readily applicable as novel anodic materials on paper and enhanced performance better than a conventional graphite ink or gold anode. The hydrophobic wax-based CEM was readily built with a commercially available wax printer and using heat to control how deep the wax penetrated the paper. This work will create a novel platform for paper-based power source, stepping toward batch-fabricable flexible papertronics.

Suggested Citation

  • Mohammadifar, M. & Zhang, J. & Yazgan, I. & Sadik, O. & Choi, S., 2018. "Power-on-paper: Origami-inspired fabrication of 3-D microbial fuel cells," Renewable Energy, Elsevier, vol. 118(C), pages 695-700.
    • Handle: RePEc:eee:renene:v:118:y:2018:i:c:p:695-700
    DOI: 10.1016/j.renene.2017.11.059
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    1. ., 2012. "Electric Power," Chapters, in: Regulatory Reform of Public Utilities, chapter 3, pages 49-64, Edward Elgar Publishing.
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    1. Tang, Raymond Chong Ong & Jang, Jer-Huan & Lan, Tzu-Hsuan & Wu, Jung-Chen & Yan, Wei-Mon & Sangeetha, Thangavel & Wang, Chin-Tsan & Ong, Hwai Chyuan & Ong, Zhi Chao, 2020. "Review on design factors of microbial fuel cells using Buckingham's Pi Theorem," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).
    2. Kebir, Anouer & Woodward, Lyne & Akhrif, Ouassima, 2019. "Real-time optimization of renewable energy sources power using neural network-based anticipative extremum-seeking control," Renewable Energy, Elsevier, vol. 134(C), pages 914-926.

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