Carbon paper/copper metal-organic framework sensor for detection of the European Union watch list substance metformin: electroanalysis and computational mechanistic insights

• A novel carbon paper (CP) sensor was developed for metformin (MET). • Layer-by-layer CP modification with Cu-BTC MOF allowed selective detection of MET. • Strong nitrogen–Cu²⁺ interaction enhances complex stability and drives MET sensing. • A Low LOD of 0.037 µM and high sensitivity 207.6±2.1 μA μM −1 cm −2 was achieved. • Recoveries of 80.0-91.3% in fish and river water show potential for in situ assays. A novel electrochemical sensor of carbon paper (CP) modified with a copper-trimesic acid metal-organic framework (Cu-BTC) was developed for determination of metformin (MET) in complex environmental matrices. MET is one of the most prescribed pharmaceuticals worldwide, posing a potential environmental risk being thus marked by the European Union as a priority contaminant for monitoring. The CP modification was performed through an environmentally friendly layer-by-layer method, and the CP/Cu-BTC sensor was characterized morphologically and structurally. Voltametric analysis revealed a well-defined and irreversible oxidation peak at 0.92 V in contrast with no peak when a bare CP was used, which highlights the importance of Cu-BTC in the detection process. This was confirmed by computational studies that revealed that MET interacts spontaneously with Cu-BTC through hydrogen bonds and van der Waals forces. The electroanalytical conditions (electrolyte pH (8), technique parameters and analyte pre-concentration, +0.4 V and 150 s) were optimized to maximize sensitivity and selectivity. The sensor showed two linear detection ranges (0.11–1.5 and 1.5–10 µM) with high sensitivities (207.6±2.1 and 170.2±4.1 μA µM⁻¹ cm⁻²) and low detection limits (0.037 and 0.52 µM), resulting in a quantification limit (0.11 µM) that is significantly below the established threshold by the European Commission Implementing Decision 2025/439. CP/Cu-BTC exhibited excellent reproducibility, selectivity, and accuracy (80.0–91.3%) in wastewater, river water and fish samples with minimum extraction steps. Overall, it offers a competitive, cost-effective, and relevant method for monitoring MET in aquatic ecosystems, with potential to compete with the currently applied techniques.