Oxidative Coupling Methods for the Spectrophotometric Determination of Vanadium (V) in Diverse Sample Matrices

Abstract

Vanadium(V) is a transition metal of growing analytical interest owing to its widespread presence in various environmental, biological, and industrial samples. Accurate and sensitive approaches are essential for the determination of vanadium (V) for environmental monitoring, metallurgical processes, and biomedical studies. This research article presents innovative oxidative coupling protocols for the determination of vanadium by the spectrophotometric method in diverse sample matrices. The proposed methods harness the power of oxidative coupling reactions, capitalizing on the unique chemical properties of vanadium(V) ions. All these methods have several advantages including simplicity, cost-effectiveness, and the ability to analyze vanadium(V) in complex sample matrices. The methodology involves the reaction of vanadium(V) ions with suitable chromogenic reagents, resulting in the formation of intensely colored complexes. The absorbance of these complexes is then measured spectrophotometrically at specific wavelengths, allowing for the quantification of vanadium(V) concentrations. Importantly, the oxidative coupling reactions employed in this study exhibit high specificity for vanadium(V) ions, minimizing interference from other species in the sample matrix. A comprehensive investigation of the analytical performance of these oxidative coupling methods was conducted. Calibration curves were constructed using standard vanadium(V) solutions, demonstrating excellent linearity over a wide concentration range, and highlighting their sensitivity. The precision and accuracy of the methods were assessed through replicate measurements and recovery studies, yielding satisfactory results. One of the key strengths of the proposed methods lies in their versatility. They were successfully applied to various sample types, including environmental water samples, soil, and plant extracts. The ability to adapt these methods to diverse matrices underscores their applicability in real-world scenarios.