PdMo Bimetallene as a High-Performance Electrochemical Sensor for the Selective Detection of Dopamine
Year: 2026
Type: article
Abstract: Dopamine (DA) is a crucial catecholamine neurotransmitter, and its abnormal levels are closely associated with neurological disorders such as Parkinson’s disease. Electrochemical sensing technology offers a rapid and cost-effective platform for DA detection; however, it often suffers from interference from coexisting biomolecules such as ascorbic acid (AA) and uric acid (UA). In this study, we report a novel electrochemical biosensor based on PdMo bimetallene, a nanomaterial synthesized via a facile wet-chemical approach, aiming to enhance the detection performance and selectivity for DA. PdMo bimetallene is a highly curved, atomically thin two-dimensional nanosheet featuring abundant strained sites and a high density of active centers, enabling the selective and sensitive detection of DA. The results demonstrate that the as-prepared PdMo bimetallene-modified glassy carbon electrode (GCE) exhibits excellent electrocatalytic activity toward the oxidation of DA. The sensor displays a good linear response over the concentration range from 10 nM to 200 µM, with an ultrahigh sensitivity of 80 µA·µM−1 cm−2 and a low detection limit of 0.14 µM (S/N = 3). Owing to the synergistic electronic effect between Pd and Mo, the high density of exposed active sites, and the unique strained lattice structure of the bimetallene, the sensor enables accurate determination of DA concentrations even in the presence of interfering species such as AA and UA. In summary, the successfully fabricated PdMo bimetallene-based sensor offers the advantages of low cost, facile synthesis, a wide linear range, and high sensitivity, positioning it as a promising candidate for neurotransmitter detection applications.
DOI: 10.3390/ijms27093861
Authors: Yuting Zhong, Lei Li, Yunbing Wang
Institution: Sichuan University
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,499
Award: G687681319
OpenAlex ID: W7157320170