Comprehensive optimization of a-Si: H p-i-n structures for enhanced energy harvesting

Abstract Enhancing the energy conversion efficiency of hydrogenated amorphous silicon (a-Si: H) solar cells remains a key objective in advancing thin-film photovoltaic technology. This study presents a comprehensive numerical optimization of a-Si: H p-i-n solar cells using the OghmaNano simulation platform under standard AM1.5G illumination (100 mW/cm 2 ). The modeling accounts for Shockley–Read–Hall (SRH) recombination, carrier mobility, and field-dependent generation to ensure physical accuracy. The investigation focused on simultaneous optimization of the intrinsic layer thickness (100–600 nm) and bandgap tuning (1.6–1.95 eV) to determine their combined influence on device performance. Results revealed that the trade-off between open-circuit voltage (Voc) and short-circuit current (Jsc) is governed by the balance between enhanced light absorption and increased carrier recombination. An intrinsic layer thickness of 200 nm and bandgap of 1.95 eV yielded the optimal configuration, achieving a simulated efficiency of 11.27%. This value aligns with experimental benchmarks when idealized conditions are considered. The findings confirm that dual-parameter optimization combining geometrical and electronic tuning can substantially improve carrier collection and energy conversion efficiency. Compared with previous studies, the proposed design demonstrates superior performance and provides clear guidelines for the structural engineering of high-efficiency a-Si: H solar cells.

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Publication Details

Journal
Materials for Renewable and Sustainable Energy
Published
2025-11-28
DOI
https://doi.org/10.1007/s40243-025-00342-6
Citations
1
Primary Topic
Thin-Film Transistor Technologies
Type
article
Field-Weighted Citation Impact
0.73
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article

Comprehensive optimization of a-Si: H p-i-n structures for enhanced energy harvesting

Soni Prayogi, A. Muhammad
1 citations
Materials for Renewable and Sustainable Energy
Thin-Film Transistor Technologies
0.73
article

Comprehensive optimization of a-Si: H p-i-n structures for enhanced energy harvesting

Soni Prayogi, A. Muhammad
article en
1 citations

Abstract

Abstract Enhancing the energy conversion efficiency of hydrogenated amorphous silicon (a-Si: H) solar cells remains a key objective in advancing thin-film photovoltaic technology. This study presents a comprehensive numerical optimization of a-Si: H p-i-n solar cells using the OghmaNano simulation platform under standard AM1.5G illumination (100 mW/cm 2 ). The modeling accounts for Shockley–Read–Hall (SRH) recombination, carrier mobility, and field-dependent generation to ensure physical accuracy. The investigation focused on simultaneous optimization of the intrinsic layer thickness (100–600 nm) and bandgap tuning (1.6–1.95 eV) to determine their combined influence on device performance. Results revealed that the trade-off between open-circuit voltage (Voc) and short-circuit current (Jsc) is governed by the balance between enhanced light absorption and increased carrier recombination. An intrinsic layer thickness of 200 nm and bandgap of 1.95 eV yielded the optimal configuration, achieving a simulated efficiency of 11.27%. This value aligns with experimental benchmarks when idealized conditions are considered. The findings confirm that dual-parameter optimization combining geometrical and electronic tuning can substantially improve carrier collection and energy conversion efficiency. Compared with previous studies, the proposed design demonstrates superior performance and provides clear guidelines for the structural engineering of high-efficiency a-Si: H solar cells.

Materials for Renewable and Sustainable EnergyVol. 15(1)
Sepuluh Nopember Institute of Technology (ID), Pertamina (Indonesia) (ID), University of Malaya (MY), Universitas Pertamina
Openalex Percentile: Top 21%
Thin-Film Transistor Technologies
0.73
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Comprehensive optimization of a-Si: H p-i-n structures for enhanced energy harvesting — Soni Prayogi, A. Muhammad · Materials for Renewable and Sustainable Energy (2025) | TGRS Research Map | TGRS