<p>In this paper, an acetone sensor based on a single-mode fiber (SMF) coated with cobalt oxide (Co<InlineEquation ID="IEq5"> <EquationSource Format="TEX">\(_{3}\)</EquationSource> </InlineEquation>O<InlineEquation ID="IEq6"> <EquationSource Format="TEX">\(_{4}\)</EquationSource> </InlineEquation>) nanoparticles is characterized. Different methods were explored for coating Co<InlineEquation ID="IEq7"> <EquationSource Format="TEX">\(_3\)</EquationSource> </InlineEquation>O<InlineEquation ID="IEq8"> <EquationSource Format="TEX">\(_{4}\)</EquationSource> </InlineEquation> nanoparticles on SMF, and a chemical vapor etching (CVE) method was optimized to yield a functionalized SMF. The Co<InlineEquation ID="IEq9"> <EquationSource Format="TEX">\(_3\)</EquationSource> </InlineEquation>O<InlineEquation ID="IEq10"> <EquationSource Format="TEX">\(_{4}\)</EquationSource> </InlineEquation> nanoparticles were synthesized via coprecipitation using cobalt acetate and NaOH. SEM analysis showed that CVE pretreatment created a distinct surface morphology, enabling a more uniform and homogeneous nanoparticle coating compared to the dip coating method. Extensive material characterization methods such as Fourier transform infrared (FTIR), Ultraviolet-Visible (UV-Vis) spectroscopy, dynamic Light Scattering (DLS) analysis, and scanning electron microscope (SEM), are utilized to analyze and evaluate structural stability and homogeneous distribution with optical properties of the nanoparticles and their applicability in breath analysis. A customized sensor characterization setup has been designed for acetone sensing. An optical coupler injects light into the fiber, while another directs the transmitted signal to a photodiode, which converts it into an electrical current varying with acetone concentration. This signal is processed by a microcontroller (Arduino/ESP-32). The output current increases from 0.48&#xa0;<InlineEquation ID="IEq11"> <EquationSource Format="TEX">\(\mu\)</EquationSource> </InlineEquation>A at 0.5 ppm to 2.6&#xa0;<InlineEquation ID="IEq12"> <EquationSource Format="TEX">\(\mu\)</EquationSource> </InlineEquation>A at 12 ppm, yielding a sensitivity of 0.18 <InlineEquation ID="IEq13"> <EquationSource Format="TEX">\(\mu\)</EquationSource> </InlineEquation>A/ppm with 3% non-linearity. The sensor offers a low-cost, high-performance solution for acetone detection for early diagnosis and health monitoring, supporting sustainable healthcare and innovation.</p>

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CVE-assisted Co3O4 nanoparticle-coated optical fiber sensor for acetone detection

  • Bhawani Sahu,
  • Ramkrushna Sahu,
  • Priyanshu Kumar Patro,
  • Kumar Prasannajit Sahu,
  • Anurag Das,
  • Tusharkant Panda,
  • Padmini Mishra,
  • Adarsh Nigam,
  • Pramod Martha

摘要

In this paper, an acetone sensor based on a single-mode fiber (SMF) coated with cobalt oxide (Co \(_{3}\) O \(_{4}\) ) nanoparticles is characterized. Different methods were explored for coating Co \(_3\) O \(_{4}\) nanoparticles on SMF, and a chemical vapor etching (CVE) method was optimized to yield a functionalized SMF. The Co \(_3\) O \(_{4}\) nanoparticles were synthesized via coprecipitation using cobalt acetate and NaOH. SEM analysis showed that CVE pretreatment created a distinct surface morphology, enabling a more uniform and homogeneous nanoparticle coating compared to the dip coating method. Extensive material characterization methods such as Fourier transform infrared (FTIR), Ultraviolet-Visible (UV-Vis) spectroscopy, dynamic Light Scattering (DLS) analysis, and scanning electron microscope (SEM), are utilized to analyze and evaluate structural stability and homogeneous distribution with optical properties of the nanoparticles and their applicability in breath analysis. A customized sensor characterization setup has been designed for acetone sensing. An optical coupler injects light into the fiber, while another directs the transmitted signal to a photodiode, which converts it into an electrical current varying with acetone concentration. This signal is processed by a microcontroller (Arduino/ESP-32). The output current increases from 0.48  \(\mu\) A at 0.5 ppm to 2.6  \(\mu\) A at 12 ppm, yielding a sensitivity of 0.18 \(\mu\) A/ppm with 3% non-linearity. The sensor offers a low-cost, high-performance solution for acetone detection for early diagnosis and health monitoring, supporting sustainable healthcare and innovation.