Contents
2024
Volume: 45 Issue 9
7 Article(s)
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Study on Medium-Wave/ Medium-Wave Two-Color HgCdTe Materials by Molecular Beam Epitaxy
Zhen LI, Dan WANG, Wei-rong XING, Cong WANG, Rui ZHOU, and Wei-lin SHE
High-quality npn medium-wave/medium-wave two-color HgCdTe materials were prepared by molecular beam epitaxy. Fourier transform infrared spectroscopy (FTIR), secondary ion mass spectroscopy (SIMS) and X-ray double-crystal diffractometer (XRD) were used to test the material composition, thickness, element distribution, aHigh-quality npn medium-wave/medium-wave two-color HgCdTe materials were prepared by molecular beam epitaxy. Fourier transform infrared spectroscopy (FTIR), secondary ion mass spectroscopy (SIMS) and X-ray double-crystal diffractometer (XRD) were used to test the material composition, thickness, element distribution, average half-peak width and other parameters. The results show that the HgCdTe composition of the bottom n-type absorption layer is 0.318 with a thickness of 7.15 m, the composition of the p-type layer is 0.392 with a thickness of 2.47 m, and the composition of the top n-type absorption layer is 0.292 with a thickness of 4.71 m. The As doping concentration is about 3×1018 cm-3, the In doping concentration is 4×1015 cm-3, and the average half-peak width is about 95 arcsec, indicating that it has good quality. The surface defects of the HgCdTe epitaxial layer were characterized by focused ion beam (FIB), scanning electron microscope (SEM) and energy-dispersive X-ray spectrometer (EDX) tests. It is confirmed that the defects are mainly related to growth parameters such as growth temperature and Hg/Te beam-current ratio..
INFRARED
- Publication Date: Nov. 04, 2024
- Vol. 45, Issue 9, 1 (2024)
Thermal Conductivity Testing of Microbolometer Pixel Films Based on 3ω Method
Xing-tao CHAI, Long CHENG, Jie SHI, Shan DONG, and Wen-li CHEN
Thermal conductivity is one of the important parameters of microbolometer pixels, and its magnitude directly affects the response of the pixel. Thermal conductivity is related to the thermal conductivity of the thin film materials that make up the pixels. The characteristic size, temperature, and deposition process of Thermal conductivity is one of the important parameters of microbolometer pixels, and its magnitude directly affects the response of the pixel. Thermal conductivity is related to the thermal conductivity of the thin film materials that make up the pixels. The characteristic size, temperature, and deposition process of the thin film all affect the thermal conductivity. Monitoring the thermal conductivity of thin films on the production line is of great significance for the design of pixels. Based on the 3ω harmonic detection technology, a testing system for the thermal conductivity of thin films was built, and the thermal conductivity of SiNx and SiO2 thin films with a thickness of 20～100 nm was tested, including temperature and dimensional characteristics. According to the dimensional characteristics, the intrinsic thermal conductivity of SiNx is 0.747 W/(m·K), and that of SiO2 is 1.085 W/(m·K). The thermal conductivity of a titanium film with a thickness of 100 nm was tested to be 6.708 W/(m·K). Compared with the testing system based on photo-thermal method, the construction of the 3ω method testing system is simpler. This method utilizes the manufacturing process of micro-electromechanical systems (MEMS) to prepare test samples, which is an ideal solution for characterizing the thermal conductivity of micro-nano scale thin films in MEMS product design and manufacturing..
INFRARED
- Publication Date: Nov. 04, 2024
- Vol. 45, Issue 9, 7 (2024)
A Method for Measuring Infrared Focal Plane Crosstalk
Xuan LIU, and Liang WANG
As the core component of infrared imaging equipment, the performance of the infrared focal plane array (IRFPA) detector directly affects the imaging quality of the equipment. The unavoidable diffraction effect can lead to crosstalk between pixels, seriously affecting the performance of the detector. A crosstalk testingAs the core component of infrared imaging equipment, the performance of the infrared focal plane array (IRFPA) detector directly affects the imaging quality of the equipment. The unavoidable diffraction effect can lead to crosstalk between pixels, seriously affecting the performance of the detector. A crosstalk testing method based on slit optical system is proposed, which uses high-precision slit optical testing equipment to obtain the level data of the detection pixels and their horizontally adjacent pixels within the slit range, and at the same time achieves quantitative evaluation of crosstalk phenomenon. This article uses test data from medium wave 320×256 mercury cadmium telluride (30 m) detector, medium wave 320×256 mercury cadmium telluride (50 m) detector, and medium wave 320×256 indium antimonide (30 m) detector to verify the proposed crosstalk testing method. The verification results demonstrate that the proposed method can accurately describe the crosstalk phenomenon and quantitatively analyze the impact of crosstalk on detector performance. Compared with existing small light point testing methods, the proposed method is easier to focus and obtains more accurate crosstalk quantification results, achieving an improvement in testing efficiency..
INFRARED
- Publication Date: Nov. 04, 2024
- Vol. 45, Issue 9, 17 (2024)
Study on the Preparation Method of Cadmium Zinc Telluride Crystal Samples Based on X-ray Diffraction Topography
Yan-zhang WANG, Jiang-gao LIU, Zhen-xing LI, Wei BAI, Qian LI, and Wei-lin SHE
The sample preparation method of Cadmium Zinc Telluride (CdZnTe) crystals based on traditional X-ray diffraction topography (XRT) is to grind and polish the test wafer to obtain a surface that meets the test conditions. As the size of single crystal wafers increases, the difficulty and time consumption of wafer grindinThe sample preparation method of Cadmium Zinc Telluride (CdZnTe) crystals based on traditional X-ray diffraction topography (XRT) is to grind and polish the test wafer to obtain a surface that meets the test conditions. As the size of single crystal wafers increases, the difficulty and time consumption of wafer grinding and polishing processing become higher, and it is also easy to cause wafer damage. To solve the above issues, a new method for preparing XRT samples has been obtained by studying the corrosion method of wafers after cutting and grinding. This sampling method can quickly remove surface damage from the wafer, obtain the wafer surface meeting XRT test requirements, significantly reduce sampling difficulty and shorten sampling time. The XRT image of the sample prepared by this method has uniform contrast and good signal-to-noise ratio. All types of crystal defects can be detected. This technology can be well applied to the subsequent screening and processing of large-sized cadmium zinc telluride wafers..
INFRARED
- Publication Date: Nov. 04, 2024
- Vol. 45, Issue 9, 23 (2024)
Research on Circular Cooperative Object Detection and Localization Algorithm Based on Improved YOLOv8
Fei XU, Xue-zhu LIN, Li-li GUO, Jing SUN, and Li-juan LI
Aiming at problems such as low recognition accuracy or poor localization ability of circular cooperative objects in low illumination or complex backgrounds in vision measurement, a model based on CNNs is proposed in this paper to optimize the YOLOv8 algorithm. The model designed in this paper has a total of 225 layers Aiming at problems such as low recognition accuracy or poor localization ability of circular cooperative objects in low illumination or complex backgrounds in vision measurement, a model based on CNNs is proposed in this paper to optimize the YOLOv8 algorithm. The model designed in this paper has a total of 225 layers of network, about 3 million parameters and 8.2G FLOPs of computing power. The model is trained by using the circular cooperative target data set under different conditions, and the performance index and computational efficiency of the model are monitored in real time during the training process, and the model is adjusted and optimized in detail. The experimental results show that the algorithm has a precision of 99%, a recall rate of 92% and an average accuracy of 92%. Compared with traditional feature extraction methods such as Hough transform and YOLOv3, the accuracy of the proposed algorithm is improved by 14% and 4%. Recall rates increase by 17% and 2%. The average accuracy is improved by 10% and 2%. The algorithm can significantly improve the recognition and positioning accuracy of circular cooperative targets under variable conditions such as low illumination environment, complex background or small change of target shape..
INFRARED
- Publication Date: Nov. 04, 2024
- Vol. 45, Issue 9, 29 (2024)
Analysis of Saccharin Content Based on Terahertz Time-Domain Spectroscopy and PCA-SVM Algorithm
Rui-xuan WANG, Zhi-yong TAN, and Jun-cheng CAO
Spectral analysis is an important means of studying the interaction between THz radiation and matter. The transmittance spectra of samples with different levels of saccharin are tested using an all-fiber THz-TDS system, and it is found that the characteristic absorption peaks of saccharin are located around 1.4 THz andSpectral analysis is an important means of studying the interaction between THz radiation and matter. The transmittance spectra of samples with different levels of saccharin are tested using an all-fiber THz-TDS system, and it is found that the characteristic absorption peaks of saccharin are located around 1.4 THz and 1.7 THz. PCA-SVM method is used to establish the regression model of saccharin content, and the prediction results are analyzed and compared with the GA-PLS model. Correlation coefficients and RMSE are introduced to evaluate the modeling effect, and the sample set made with a 10% content gradient is tested. The research results show that the RMSE of the prediction models established using PCA-SVM, SVM and GA-PLS methods are 1.885%, 1.926% and 2.432%, respectively. Therefore, the PCA-SVM method has the best prediction performance, and the predicted data show a good correlation with the actual data. A content regression prediction model with good performance is obtained, which provides an effective means for the detection and analysis of saccharin content..
INFRARED
- Publication Date: Nov. 04, 2024
- Vol. 45, Issue 9, 44 (2024)
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