Optimal modeling of perovskite solar cell with graphene oxide as hole transport layer using L32(28) Taguchi design

Salehuddin, Fauziyah and Kaharudin, Khairil Ezwan and Ahmad Jalaludin, Nabilah and Arith, Faiz and Mohd Zain, Anis Suhaila and Ahmad, Ibrahim and Md Junos @ Yunus, Siti Aisah and Abdul Hamid, Afifah Maheran (2023) Optimal modeling of perovskite solar cell with graphene oxide as hole transport layer using L32(28) Taguchi design. International Journal of Nanoelectronics and Materials, 17 (1). pp. 20-27. ISSN 1985-5761

Text 379 Download (4kB)

Abstract

Material parameter variations are one of the main contributors affecting the performance of solar cell devices, thus, Taguchi design is employed to optimize the material parameters in attaining maximum power conversion efficiency (PCE).This paper discusses the optimal modeling of the Perovskite solar cell (PSC) with graphene oxide (GO) hole transport layer (HTL) using L32(28) Taguchi design. The device simulation is conducted using a solar cell capacitance simulator (SCAP),whereas the L32(28) Taguchi design is used for device optimization. The final results reveal that the L32(28) Taguchi design has significantly optimized the device parameters in which FTO thickness, FTO donor concentration, TiO2thickness, TiO2donor concentration, CH3NH3PbI3-xClxthickness, CH3NH3PbI3-xClxdonor concentration, GO thickness and GO acceptor concentration are predictively set to 0.1 μm, 1 x 1020 cm-3, 0.03 μm, 1 x 1020cm-3, 0.9 μm, 1 x 1020cm-3, 0.03 μm and 1 x 1020cm-3correspondingly. Analysis of variance (ANOVA) reveals thattheCH3NH3PbI3-XClX thicknessis the most dominant input parameter affecting the PCE of the device. The optimized input parameters yield the maximum attainable PCE of 35.91% with a signal-to-noise ratio (SNR) of 31.11 dB.

Item Type:	Article
Uncontrolled Keywords:	Analysis of variance, Graphene oxide, Hole transport layer, Power conversion efficiency, Signal-to-noise ratio
Divisions:	Faculty Of Electronics And Computer Technology And Engineering
Depositing User:	Sabariah Ismail
Date Deposited:	09 Oct 2024 16:11
Last Modified:	09 Oct 2024 16:11
URI:	http://eprints.utem.edu.my/id/eprint/27809
Statistic Details:	View Download Statistic

Actions (login required)

View Item