Synergistic integration of few-layer thick MXenes and small Pd nanocubes for enhanced electrochemical nitrofurantoin detection: Implications in pharmaceutical pollutant monitoring
Direct electrochemical detection of clinically significant and emerging pharmaceutical pollutants, such as nitrofurantoin, is a critical challenge. Herein, we propose an efficient electroactive platform composed of Pd nanocubes (Pd NCs) embedded within partially oxidized MXenes (Ti3C2Tx-TiO2). This...
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Veröffentlicht in: | Journal of environmental chemical engineering 2023-12, Vol.11 (6), p.111152, Article 111152 |
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Sprache: | eng |
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Zusammenfassung: | Direct electrochemical detection of clinically significant and emerging pharmaceutical pollutants, such as nitrofurantoin, is a critical challenge. Herein, we propose an efficient electroactive platform composed of Pd nanocubes (Pd NCs) embedded within partially oxidized MXenes (Ti3C2Tx-TiO2). This proximity between Pd NCs, in-situ generated TiO2, and Ti3C2Tx results in a highly compact and efficient architecture, facilitating enhanced charge transfer and electrocatalytic activity, which results in an efficient cathodic reduction to NFT at a much lower-over potential of − 0.4 V. The optimal composite configuration (Pd-Ti3C2Tx-P) enabled NFT detection in a dynamic concentration range from 1 to 140 nM, with a detection sensitivity reaching down to 0.01 nM (S/N = 3) against Ag/AgCl as the reference electrode. Furthermore, the developed sensor demonstrated outstanding selectivity toward NFT while tolerating probable interfering substances such as biomolecules, drugs, and metal ions. The sensor can detect NFT selectively in complicated environmental matrices such as hospital waste effluent samples. The proposed design offers a simple route to construct advanced electrocatalytic sensors with potential applications in monitoring emerging pharmaceutical pollutants.
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•Pd NCs with partially oxidized MXenes as a synergistic electrocatalytic platform.•Redox activity from Pd NCs and conductivity from MXenes synergistically reduce NFT.•Low-overpotential-based outstanding selectivity for NFT in environmental samples. |
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ISSN: | 2213-3437 |
DOI: | 10.1016/j.jece.2023.111152 |