Citation

Chan, Kah Yoong and Rahman, Sk Rakibur and Ngu, Eng Eng and Chung, Gwo Chin and Pang, Wai Leong and Tan, Kar Ban and Ashraf, Muhammad Aqeel and Singh, Ajay Kumar (2026) Electrical Performance of Zn–Cu Plant-Based Cells in Aloe Vera: Leaf-Stem Comparison with Series and Parallel Scaling. Journal of Engineering Technology and Applied Physics, 8 (2). p. 150. ISSN 2682-8383

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Abstract

Plant tissue may act as a weak electrochemical battery when electrodes of various metals are introduced. However, leaf-based systems typically experience local damage and drying around the insertion site, raising questions regarding long-term usage. A single Aloe veraplant was treated with a Zn-Cuelectrode pair on a mature leaf and stem. Based on our accepted conference study's optimum leaf orientation, leaf measurements were taken horizontally along the leaf's length direction. In stem testing, horizontal positioning yielded greater current and lower effective resistance than vertical placement. The leaf and stem generated equivalent open-circuit voltages of 0.958 V and 0.943 V and short-circuit currents of 0.15 mA and 0.12 mA in a horizontal arrangement.Scaling was evaluated by combining one horizontal leaf cell and one horizontal stem cell. The obtained voltage from the series connection was 1.883 V, while the obtained current was 0.25 mA from the parallel connection. An effective resistance calculationand a simple equivalent-source model were used to verify the expected circuit behaviour.After seven days, the leaf insertion site exhibited degradation, whereas the stem site remained reasonably intact, indicating that stem implantation may retain a similar yield with enhanced durability for longer-term harvesting

Item Type:	Article
Uncontrolled Keywords:	Electrical performance- aloe vera,Leaf–stem comparison, equivalent circuit modelling, internal resistance
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1001-1841 Production of electric energy or power. Powerplants. Central stations
Divisions:	Faculty of Artificial Intelligence & Engineering (FAIE)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	12 Oct 2026 03:53
Last Modified:	12 Oct 2026 03:53
URII:	http://shdl.mmu.edu.my/id/eprint/16905

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