Engineered PtAgCu/MoS2 and hexagonal star-like nitrogen-doped carbon enabling highly efficient sandwich-type electrochemical immunosensing via multiple signal enhancement

Abstract

Cardiac troponin I (cTnI), recognized as the gold-standard biomarker for acute myocardial infarction (AMI), plays a crucial role in the early diagnosis and clinical management. Herein, we present a rationally designed multiple signal enhancement strategy for an ultrasensitive electrochemical immunoassay of cTnI. This work integrates the superior catalytic activity of a wrinkled MoS2-supported PtAgCu ternary alloy (PtAgCu/MoS2) with the excellent conductivity of hexagonal star-like nitrogen-doped carbon (HS-NC) modified by gold nanoparticles (Au@HS-NC). The PtAgCu alloy, featuring maximized atomic utilization and optimized d-orbital coupling, exhibits outstanding hydrogen peroxide (H2O2) electroreduction activity and a large electrochemically active surface area, thereby effectively amplifying the sensing signal. Meanwhile, the precisely designed MoS2 carrier not only offers abundant anchoring sites and facilitates charge transfer but also enriches H2O2 reactant, thereby promoting the catalytic performance of the PtAgCu alloy. Furthermore, as an ideal substrate, the morphologi-cally engineered HS-NC, enriched with nitrogen functionalities, offers a highly conductive framework with ultralarge surface area (1121.80 m2 g-1), enabling efficient immobilization of primary antibodies (Ab1) and stable, accelerated charge transfer, thereby synergistically amplifies the signal output. Benefiting from this multiple amplification strategy, the proposed immunosensor achieves a remarkably low limit of detection of 0.51 fg mL-1, and an exceptionally broad dynamic range (from 10 fg mL-1 to 100 ng mL-1), while exhibits excellent selectivity in complex matrices, maintaining high reproducibility and stability. This work demonstrates a rational multi-amplification design paradigm for constructing high-performance immunosensors and highlights its promising application in AMI early diagnosis.