Light-Triggered Graphene/Black Phosphorus Heterostructure FET Platform for Ultrasensitive Detection of Alzheimer's Disease Biomarkers at the Zeptomole Level

Abstract

Due to the low concentration of amyloid-beta (Aβ) in plasma and the high content of interfering factors, the conventional detection method for the quantification of Aβ still faces the problem of insufficient limit of detection (LOD). In this work, we propose a new light-triggered graphene-black phosphorus heterostructure (G-BP) field-effect transistor (FET) biosensing platform that achieves a ​​marked​​ reduction in the LOD. The LOD for Alzheimer's disease (AD) biomarker Aβ₄₂ detection using the G-BP FET is as low as 235.1 zM (2.351 × 10^-19 M), which is the lowest value reported to date and is approximately 2 to 3 orders of magnitude lower than other reported biosensing platforms. The G-BP FET platform provides precise, real-time guidance for non-invasive early diagnosis, disease monitoring, and personalized treatment plans for AD. Moreover, this method has good scalability and potential applications in other areas, including early detection of cancer and other major chronic diseases.

Fig. 1.

Schematic diagram of G-BP FET biosensor operation procedure. (A) Schematic diagram of the Aβ₄₂ antigen. (B) Structural and principle diagram of light-triggered G-BP FET. (C) Effect of light on the detection of LOD of Aβ₄₂ protein by the G-BP FET biosensor. In the dark state, the LOD of the G-BP FET biosensor is 2.767 aM. In the light state, the LOD of the G-BP FET biosensor is 235.1 zM.

Fig. 2.

Construction and characterization of the G-BP FET biosensor. (A) Schematic diagram of G-BP FET functionalization and detection of Aβ₄₂ protein. (B) Raman spectra (1,100 to 2,800 cm⁻¹) of G-BP before and after modification of PBASE. (C) Raman spectra (330 to 490 cm⁻¹) of G-BP before and after modification of PBASE. (D) Output characteristic curve of G-BP FET during functionalization (PBASE and antibody modifications). (E) Transfer characteristic curve of G-BP FET during functionalization (V_d = 0.1 V).

Fig. 3.

Mechanism of electrostatic photogating. (A) Schematic illustration of Aβ₄₂ protein detection by G-BP FET using the electrostatic photogating mechanism. (B) Energy band changes before and after the formation of heterojunction between G and BP. (C) Energy band variation diagram of G-BP in the electrostatic gating process. (D) Energy band variation diagram of G-BP in the photogating process. (E) Energy band variation diagram of G-BP in the electrostatic photogating process.

Fig. 4.

Aβ₄₂ biomarker detection. (A) Schematic diagram of detecting Aβ₄₂ by G-BP FET. (B) The transfer characteristic curve of Aβ₄₂ was detected by G-BP FET (V_d = 0.1 V). (C) Real-time response of G-BP FET to Aβ₄₂ in 0.001× PBS in the dark state. (D) The response curve of the G-BP FET biosensor changed with time after adding Aβ₄₂ with a concentration of 0 to 100 pM to 0.001× PBS. From 20 s onwards, the device is exposed to light. (E) Relationship between Aβ₄₂ concentration and response signal. The intersection of noise level and curve is LOD. LOD is 2.767 aM in the dark and 235.1 zM in the light. (F) The response time of 10 fM Aβ₄₂ was detected in the dark state. (G) Light response time of the G-BP FET sensor under different Aβ₄₂ concentrations. (H) The performance of this work was compared with other methods for the detection of Aβ₄₂.

Fig. 5.

Specificity verification of the G-BP FET biosensor. (A) Real-time response of G-BP FET to Aβ₃₈ in 0.001× PBS. (B) Real-time response of G-BP FET to Aβ₄₀ in 0.001× PBS. (C) Real-time response of G-BP FET to mixed peptides in 0.001× PBS. (D) Response signals of PBS (0.001×), Aβ₃₈ (100 pM), Aβ₄₀ (100 pM), mixed peptides (100 pM), and Aβ₄₂ (100 pM and 100 pM + light).