Enhanced Electrochemical Detection of Valganciclovir Using a Hierarchically Structured Lisianthus Flower-Inspired...

This study reports the development of an innovative electrochemical sensor based on organometallic framework nanostructures for detecting valganciclovir (VLCV). VLCV is employed in the treatment of cytomegalovirus retinitis in AIDS patients. Rational design of nanoarchitectures for electroactive materials is a crucial approach for boosting their electrocatalytic performance. Herein, Lisianthus flower-inspired Ni-Ce-metal-organic framework (MOF), Ni-MOF, and rod-inspired Ce-MOF were synthesized by the solvothermal method. An electrochemical sensor for VLCV was developed by employing a multilayer approach using Lisianthus flower-inspired Ni-Ce metal-organic framework/multiwall carbon nanotubes (Ni-Ce-MOF/MWCNTs) modification on a glassy carbon electrode (GCE). Incorporating a bimetallic Ni-Ce-MOF into a conventional conductive material, such as MWCNTs, significantly increases the specific surface area and improves the conductivity and catalytic properties of the MWCNTs. Relative to the rod-inspired Ce-MOF and Ni-MOF, the electrocatalytic performance of the Lisianthus flower-inspired Ni-Ce-MOF coated on MWCNTs surpasses that of the rod-inspired Ce-MOF, showcasing enhanced performance in VLCV oxidation. This superiority arises from their enhanced electrical conductivity and enlarged surface area. The Lisianthus flower-inspired Ni-Ce-MOF/MWCNTs/GCE demonstrated extensive linear ranges (ranging from 4.0 to 3800.0 nM), a lower detection limit (1.4 nM), remarkable selectivity, and sustained stability over an extended period in the context of VLCV sensing. The real samples underwent analysis through using both electrochemical and UV-vis spectrophotometry methods, and the findings from both methods exhibited no substantial difference, validating the sensor's remarkable practical performance. These results suggest that Lisianthus flower-inspired Ni-Ce-MOF/MWCNTs/GCE electrocatalysts provide a promising sensing platform for analyzing biological samples.