An Intelligent Fiber-Shaped Photodetector Array Featuring High-Linearity Opto-Mechanical Response
Abstract The rapid evolution of artificial intelligence (AI) technologies is accelerating the development of fiber-based photodetectors (FPDs), driving further transformation and progress of the electronics industry. Nevertheless, the transition of FPDs from laboratory prototypes to viable daily-use technologies necessitates extensive research on multifunctional capabilities. Addressing this gap, we pioneer a highly intelligent strain-opto dual-mode sensing platform based on MoS₂/PEDOT:PSS heterojunction FPD array for wearable applications. Circumventing traditional vertical heterostructures that focus on piezoelectric-induced intensity enhancement, our work prioritizes linearity optimization through precise interfacial engineering. A key breakthrough of this work lies in the integration of PEDOT:PSS as a conductive pathway, which endows the device with an exceptionally linear strain-dependent photocurrent response (R 2 ཞ0.93), thereby providing a reliable foundation for co-located photoelectric and mechanical sensing. First-principles calculations uncover that the higher-loaded PEDOT:PSS layer introduces uniformly distributed metal-induced gap states (MIGS) and stabilizes the Fermi level via pinning effects, ensuring that strain-induced band offsets modulate carrier transport in a strictly linear regime. Furthermore, to address the inherent signal coupling in practical wearable scenarios, a system-level AI-driven decoupling framework is implemented, enabling the resolution of complex, overlapping inputs into independent data streams with high fidelity.
Authors
- Yanfang Meng (ORCID: https://orcid.org/0000-0002-4520-650X)
- WenYao Wu
- Longwei Li
- Feng Sun
- Tianchen Ji
- Mengke Li
Institutions
- Jiangsu University (CN)
- Jiangsu Normal University Kewen College (CN)
Publication Details
- Journal
- Research Square
- Published
- 2026-11-11
- DOI
- https://doi.org/10.21203/rs.3.rs-10985119/v1
- Primary Topic
- Advanced Sensor and Energy Harvesting Materials
- Type
- preprint