<p>CuO was synthesized using various metal precursors as Cu<sup>2+</sup> sources via a combined coprecipitation and microwave-assisted hydrothermal method, and its gas-sensing performance was systematically evaluated in relation to its structural, electronic, and morphological properties. This study systematically investigates the role of precursor chemistry as a key parameter in controlling the nucleation and growth of CuO nanostructures under identical synthesis conditions. X-ray diffraction (XRD) confirmed the formation of monoclinic CuO, and the crystallite sizes calculated using the Williamson–Hall method decreased in the order CuO-Chloride &gt; CuO-Nitrate &gt; CuO-Sulfate. Scanning and transmission electron microscopy (SEM and TEM) analyses revealed that all samples were composed mainly of CuO nanorods, with slight differences in thickness and dimensions. The Cu<sup>2+</sup> oxidation state was further confirmed by X-ray photoelectron spectroscopy (XPS). The three sensors exhibited excellent NO<sub>2</sub> detection at 200&#xa0;°C, with the CuO-N sensor showing the highest response. The limit of detection (LOD) for CuO-N was 0.12 ppm, well below the safety threshold of 1 ppm, demonstrating its capability to detect low NO<sub>2</sub> concentrations. Furthermore, the CuO-N sensor maintained stable responses over four consecutive cycles of 1 ppm NO<sub>2</sub>, indicating good operational stability without degradation of its sensing performance. The sensor produced using a metallic nitrate precursor showed the best NO<sub>2</sub> detection response (58% at 200&#xa0;°C) at a low NO<sub>2</sub> concentration (1 ppm). These findings highlight the critical influence of precursor selection on the structural and functional properties of CuO nanostructures and demonstrate a general strategy that can be extended to other metal oxide semiconductors for the rational design of high-performance gas sensors.</p>

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Influence of metal precursors on the structure, morphology, and performance of CuO nanorods gas-sensing

  • Gleison Neres Marques,
  • Amanda Akemy Komorizono,
  • Roberta Yonara N. Reis,
  • Davi Souza Ferreira,
  • Ailton José Moreira,
  • Valmor Roberto Mastelaro,
  • Maria Inês Basso Bernardi,
  • Lucia Helena Mascaro

摘要

CuO was synthesized using various metal precursors as Cu2+ sources via a combined coprecipitation and microwave-assisted hydrothermal method, and its gas-sensing performance was systematically evaluated in relation to its structural, electronic, and morphological properties. This study systematically investigates the role of precursor chemistry as a key parameter in controlling the nucleation and growth of CuO nanostructures under identical synthesis conditions. X-ray diffraction (XRD) confirmed the formation of monoclinic CuO, and the crystallite sizes calculated using the Williamson–Hall method decreased in the order CuO-Chloride > CuO-Nitrate > CuO-Sulfate. Scanning and transmission electron microscopy (SEM and TEM) analyses revealed that all samples were composed mainly of CuO nanorods, with slight differences in thickness and dimensions. The Cu2+ oxidation state was further confirmed by X-ray photoelectron spectroscopy (XPS). The three sensors exhibited excellent NO2 detection at 200 °C, with the CuO-N sensor showing the highest response. The limit of detection (LOD) for CuO-N was 0.12 ppm, well below the safety threshold of 1 ppm, demonstrating its capability to detect low NO2 concentrations. Furthermore, the CuO-N sensor maintained stable responses over four consecutive cycles of 1 ppm NO2, indicating good operational stability without degradation of its sensing performance. The sensor produced using a metallic nitrate precursor showed the best NO2 detection response (58% at 200 °C) at a low NO2 concentration (1 ppm). These findings highlight the critical influence of precursor selection on the structural and functional properties of CuO nanostructures and demonstrate a general strategy that can be extended to other metal oxide semiconductors for the rational design of high-performance gas sensors.