Significance  Monocrystalline silicon optical components, with their outstanding physical and optical properties, are widely used in optical systems, laser technology, and semiconductor devices. However, during the processing and use of monocrystalline silicon optical components, surface and subsurface defects are prone to occur, which have a significant impact on their optical performance, mechanical strength, and service life. Specifically, surface defects such as scratches and pockmarks can cause light scattering and diffraction, thereby reducing imaging quality and lowering the laser damage threshold. On the other hand, subsurface defects can alter the refractive index, mechanical strength, and thermal stability of materials, further affecting the long-term reliability of components. Therefore, the research on surface and subsurface defects of single-crystal silicon optical components holds significant academic value and practical significance.

Progress  This research takes the defect detection technology of monocrystalline silicon optical components as the research object and systematically sorts out the detection methods and theories applicable to monocrystalline silicon materials. Firstly, the application background and detection requirements of single-crystal silicon optical components were expounded, and the formation mechanisms, common types, and their influences on the performance of various defects were analyzed. For instance, scratches are mostly caused by hard particles during the grinding and polishing process, while subsurface microcracks are often triggered by processing stress concentration. Subsequently, the research status and application scope of several major surface/subsurface defect detection methods were reviewed, including optical microscopy imaging, laser scattering, X-ray tomography, infrared transmission, and photoacoustic imaging techniques. The differences among them in terms of sensitivity, resolution, and applicable scenarios were compared.

Conclusions and Prospects  Research has found that the detection technology for surface and subsurface defects of monocrystalline silicon optical components still faces many challenges, mainly including detection efficiency, depth resolution, and classification of complex defects. For instance, high-precision detection often sacrifices speed and is difficult to meet the demands of industrial online quality inspection. However, rapid detection methods are difficult to use for identifying deeply buried or minor defects. In addition, the morphologies of different defects are similar, resulting in a low accuracy rate of automatic recognition. Finally, the system summarized the existing detection methods, analyzed the advantages and disadvantages of different defect detection methods, and looked forward to the future development direction. It was proposed that the development of multimodal fusion detection and artificial intelligence-assisted recognition technology should be promoted to achieve high-precision, high-efficiency, and intelligent interpretation of defects, providing a theoretical basis and technical support for the high-precision manufacturing and application of monocrystalline silicon optical components.