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Published on: May 13, 2019
Construction of NH2-MIL-125@ZnIn2S4 Z-Scheme Heterojunctions for Deep-Learning Assisted Photoelectrochemical Sensing
Leilei Diao1, Zhen Yang1, Hao Cheng1
1Anhui Laboratory of Functional Coordinated Complexes for Materials Chemistry and Application, School of Chemical and Environmental Engineering, Anhui Polytechnic University, Wuhu 241000, China.
Abstract:
Dopamine (DA) plays a pivotal role in modulating various physiological systems. Therefore, the ultrasensitive detection of DA holds substantial importance for the diagnosis and treatment of neurological disorders. Herein, a deep-learning-assisted smart PEC biosensor is designed by synthesizing an NH2-MIL-125@ZnIn2S4 Z-scheme (NH2-MIL-125@ZIS) heterostructure as a photocathode. The heterojunction, integrating a titanium-based metal-organic framework (NH2-MIL-125) with ZIS nanosheets, achieves optimized band alignment and interfacial charge transfer, which significantly improves the electron-hole separation and yields a 2.05-fold photocurrent than that of pristine NH2-MIL-125. In the ultrasensitive detection of DA, the biosensor demonstrated a broad linear detection range (0.01 μM-1 mM) and an ultralow detection limit of 2.75 × 10-9 M (S/N = 3). With the assistance of deep learning (DL), an artificial neural network was employed to achieve an intelligent analysis of DA with outstanding predictive ability (R2 = 0.9851). This work transcends conventional PEC biosensing by integrating advanced materials engineering with artificial intelligence, establishing a new paradigm for high-performance, intelligent neurotransmitter monitoring.

