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Low-bias, broadband photodetection enabled by MAPbI3/black silicon dual-mode photodetector for compact optoelectronic platformsopen access

Authors
Sung, JunyeongKim, Min SeongLee, HyeonryulLee, Gil JuKim, HyeonghunKwon, Sooncheol
Issue Date
Jan-2026
Publisher
Elsevier B.V.
Keywords
Anti-reflection; Black silicon; Perovskite; Photodetector; Spectral discrimination
Citation
Chemical Engineering Journal, v.527, pp 1 - 10
Pages
10
Indexed
SCIE
SCOPUS
Journal Title
Chemical Engineering Journal
Volume
527
Start Page
1
End Page
10
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/62576
DOI
10.1016/j.cej.2025.171589
ISSN
1385-8947
1873-3212
Abstract
Compact photodetectors that can acquire spectral information without the need for external optical components have become increasingly important for next-generation optical sensing applications, including automotive imaging, environmental monitoring, and military systems. Back-to-back (BtB) diode designs have gained attention as promising options due to their inherent wavelength-selective response, which is achieved through asymmetric junction engineering. Despite these advantages, conventional BtB structures frequently demonstrate suboptimal sensitivity, primarily attributed to substantial optical reflectance and the high resistance of the photoactive layer. In the present study, we introduce a perovskite-based BtB photodetector fabricated on a black silicon (b-Si) substrate using the metal-assisted chemical etching (MACE) process. The vertically oriented nanostructures on the b-Si substrate provide pronounced anti-reflective effects, greatly improving photon absorption. Additionally, the textured surface of b-Si reduces charge carrier transport path within the resistive perovskite layer, promoting more efficient collection of charge carriers at lower bias voltages. Consequently, the device demonstrates improved wavelength discrimination and higher responsivity than previously reported BtB architectures. This work presents a promising approach to developing advanced optoelectronic platforms, addressing the demand for compact and energy-efficient devices capable of capturing diverse information from incident light in the AI-driven era. © 2025 Elsevier B.V.
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