Dadan Hamdani, Ratna Kusuma, R. Munir, A. I. Natalisanto, Auliya Rahmatul Ummah, Andrea Tri Rian Dani
2026.6.17World Journal of Engineering
Abstract
Purpose This study aims to optimize the physical design parameters of the front interface in (p–i1–i2–n)a-Si:H thin-film solar cells. The research focuses on identifying the optimal combination of acceptor doping concentration (NA), bandgap (Eg) and p-layer thickness (dp) under varying front contact barrier potentials ( φb0φb0), which are independently examined through a parametric analysis to maximize conversion efficiency. Design/methodology/approach The research uses an integrated framework combining numerical simulation via Automat for Simulation of Heterostructures (AFORS-HET) with the Taguchi statistical Design of Experiments. A Taguchi L9 orthogonal array was used to systematically explore parameter interactions with minimal simulation runs. Main Effect Analysis and Analysis of Variance were subsequently applied to evaluate the sensitivity and contribution of each parameter to the cell’s efficiency. Findings The results identify NA as the most dominant factor, contributing 78.27% to the variation in efficiency, followed by dp (16.80%) and Eg (3.01%). The optimal configuration (NA = 1.0 × 1019 cm−3, Eg at 1.85 eV and dp at 9 nm) yielded a confirmed conversion efficiency of 9.82%. The study demonstrates that coupling numerical modeling with Taguchi-based optimization significantly enhances computational efficiency. Originality/value This work presents a systematic integration of AFORS-HET with a Taguchi statistical framework, combined with a parametric evaluation of front contact barrier potentials, to investigate performance optimization in (p–i1–i2–n)a-Si:H structures. This physics-informed framework provides a cost-effective and adaptable methodology for developing high-performance next-generation photovoltaic technologies.
Citation format
HAMDANI, Dadan, et al. Optimization of (p–i1–i2–n)a-si:h solar cell interfaces: An integrated AFORS-HET and taguchi design of experiments study. World Journal of Engineering, 2026: 1–15.