The research focused on developing a deep ultraviolet (DUV) photodetector using gallium oxynitride (GaON), which is an ultrawide bandgap semiconductor, and its application in arc detection. Electrical arcs, which are a final form of gas discharge, emit ultraviolet light predominantly in the wavelength range of 200?400 nm. Detecting these emissions using a DUV photodetector enables the monitoring and assessment of arc discharges, which are critical in preventing accidents in high-voltage electrical systems. This study attempted to fabricate a GaON-based metal-semiconductor-metal (MSM) photodetector and to evaluate its performance under 254-nm UV light, while also demonstrating its application in high-voltage arc detection under sunlight conditions without the use of an optical focusing device.

GaON thin films were prepared using plasma-enhanced chemical vapor deposition (PECVD). PECVD was chosen for its ability to effectively control the incorporation of nitrogen and to optimize the bandgap, carrier mobility, and optical properties of the GaON material. The MSM structure was used for the photodetector, with gold-coated titanium electrodes included to ensure stability and performance. The material characterization of the GaON films was conducted using X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), scanning electron microscope (SEM), and atomic force microscope (AFM). These techniques were employed to confirm the crystal structures, elemental compositions, and surface morphologies of the GaON films. The photodetector performance was evaluated using a semiconductor testing equipment, which provided current-voltage (I-V) characteristics and dynamic response (I-t) curves under 254-nm UV light. Key performance metrics, including responsivity, detectivity, and response time (rise and fall time), were measured and analyzed.

The GaON thin film fabricated through PECVD demonstrates high crystalline quality, as evidenced by sharp XRD peaks and a uniform distribution of crystal grains, as shown in the SEM images. Results of XPS analysis reveal the presence of Ga, O, and N elements, thus validating the successful synthesis of GaON. AFM results indicate a smooth surface with a root-mean-square roughness of 2.92 nm, which is favorable for photodetector applications. Under 254-nm UV illumination, the photodetector exhibits excellent performance. The I-V characteristics under illumination show linear behavior, indicating ohmic contact between the GaON film and electrodes. The device achieves a high responsivity of 0.327 A/W and a detectivity of 3.19×10¹⁴ Jones at a 10-V bias voltage, highlighting its efficiency in converting UV light into electrical signals. This study also addressed the persistent photoconductivity (PPC) effect in the GaON photodetector. The PPC effect refers to a phenomenon in which the material continues to exhibit photoconductivity for a period after the illumination has stopped, which can lead to detection errors and prolonged response time in certain applications. Incorporating nitrogen into the GaON material can effectively suppress the PPC effect. Nitrogen doping introduces deep-level defects in the GaON material, which can capture and quickly recombine photogenerated carriers, thereby reducing the residual photoconductivity after the light source is removed. Experimental results show that the GaON material with nitrogen doping exhibits a significantly reduced PPC effect as compared with the undoped materials, where much shorter time is required for the photoconductivity to return to baseline levels following UV illumination. This characteristic is particularly important for applications requiring fast response and high-precision detection, such as real-time arc detection. The dynamic response of the detector is characterized by rise and fall time of 0.708 s and 0.413 s, respectively. These suggest a relatively fast response speed, which is critical for real-time arc detection applications. The device also exhibits good repeatability and stability, with consistent photocurrent peaks observed over multiple light exposure cycles, indicating reliable performance. One of the key advantages of the GaON photodetector is its ability to detect UV emissions in the range of 230?280 nm, which are absorbed by the Earth ozone layer, making the photodetector ideal for detecting UV light from arcs even in outdoor environments with sunlight interference. This feature was demonstrated through successful arc detection experiments conducted under sunlight without any optical focusing devices, confirming the detector high sensitivity and potential for practical applications in high-voltage power system monitoring and industrial safety. Compared with other recently reported DUV photodetectors, the GaON-based device shows competitive performance, particularly in terms of responsivity and detectivity. The study suggests that the GaON material wide bandgap and high structural stability, along with the use of PECVD for thin film fabrication, contributes to the superior performance.

The study successfully demonstrated the fabrication and characterization of a GaON-based MSM photodetector for deep ultraviolet light detection, particularly for arc detection. The photodetector exhibits high responsivity, fast response speeds, and excellent stability, making it a promising candidate for applications in high-voltage equipment monitoring and industrial safety. The use of PECVD in fabricating GaON thin films is essential for achieving high-quality crystalline structures with optimized optical and electrical properties. The ability to detect UV light in the range of 230?280 nm, which is absent on the Earth surface due to ozone absorption, further underscores the photodetector utility to distinguish arc emissions from background sunlight. In summary, the developed GaON-based DUV photodetector offers a robust solution for real-time, high-sensitivity arc detection, with potential wide-ranging applications in power systems and safety monitoring. Future work should focus on further optimizing the GaON material and device structure to enhance performance metrics such as response speed and noise reduction. Integration with advanced signal processing techniques to improve detection accuracy in complex environments should also be explored.