Optoelectronically synergized MoS₂ field-effect transistor sensor for the detection of Alzheimer's disease biomarker Aβ₄₂

Early diagnosis of Alzheimer's disease (AD) relies heavily on the ultra-sensitive detection of its core biomarker, amyloid-beta 42 (Aβ₄₂). To address this critical need, this paper presents a photoelectric synergistically enhanced field-effect transistor (FET) biosensor based on two-dimensional molybdenum disulfide (MoS₂) for the highly sensitive and specific detection of Aβ₄₂.

Experimental results demonstrate that light illumination significantly amplifies the sensing current under identical gate voltages and target concentrations. This enhancement enables the device to effectively overcome the subthreshold region and smoothly transition into the linear operating regime at lower voltages, thereby substantially optimizing signal readout efficiency in low-concentration regions. Benefiting from this photoelectric synergy, the sensor exhibits a markedly enhanced signal response and an optimized dynamic range. The limit of detection decreases to 4.15 × 10^-18 g/mL, representing a 26.29% reduction compared to dark conditions. Furthermore, the relative standard deviation (RSD) of the current response under illumination improves to 2.47% (n = 3), outperforming the 4.86% recorded in the dark and indicating simultaneous enhancements in detection repeatability and device stability. Supported by Silvaco TCAD simulations, the core operating mechanism is elucidated: the specific binding of target Aβ₄₂ molecules inherently introduces localized interface charge perturbations at the MoS₂ channel. This alteration of the interfacial charge state fundamentally governs the electrical response of the device, which is synergistically amplified under light illumination to achieve ultra-high sensing sensitivity.

This study demonstrates that the photoelectric synergistic strategy offers a highly effective pathway to overcome the sensitivity and performance bottlenecks of traditional FET biosensors. Concurrently, it establishes a novel and promising paradigm for the design of high-performance, multimodal photoelectric biomedical diagnostic chips.