Electrochemical Sensor for Levosulpiride Detection and Its Adsorptive Removal from Wastewater
Year: 2025
Type: article
Abstract: High Resolution Image Download MS PowerPoint Slide There is increasing apprehension regarding the harmful impacts of synthetic drugs, particularly the antipsychotic levosulpiride. Consequently, it is both an environmental and a social responsibility to create effective sensors and materials for the early detection and removal of this drug before consumption of contaminated water. The detection goal is achieved by the development of a highly sensitive and selective sensing platform, while the removal objective is achieved by the polyacrylamide hydrogel. The present study introduces a novel combination of advanced materials and green chemistry concepts for the development of an electrode modifier (functionalized MWCNTs) and an adsorbent (polyacrylamide hydrogel). Unlike conventional methods, where drug molecules slowly diffuse to the electrode surface, our technique for sensor preparation directly immobilizes these molecules on the electrode, leading to robust electrochemical signals and establishing a highly sensitive detection platform with a significantly reduced limit of detection (0.7 nM). Furthermore, while traditional adsorption processes may take hours or even days, our unique adsorbent for levosulpiride demonstrates effective removal in just 45 min, as confirmed by our experimental findings. Results revealed that adsorption occurred in accordance with the Langmuir model, while the kinetics of adsorption adhered to pseudo-second order kinetics. Thermodynamic parameters such as negative Δ G and positive Δ S revealed the spontaneous nature of the entropy-driven process of adsorption.
Source: ACS Omega
Authors: Mohsin Javed, Afzal Shah, Iltaf Shah
Institutions: Quaid-i-Azam University, United Arab Emirates University
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,935
OpenAlex ID: W4409730328
