| Autor: |
Lee, Hui Jing, Gamel, Mansur Mohammed Ali, Ker, Pin Jern, Jamaludin, Md Zaini, Wong, Yew Hoong, David, John P. R. |
| Předmět: |
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| Zdroj: |
Journal of Electronic Materials; Nov2022, Vol. 51 Issue 11, p6082-6107, 26p |
| Abstrakt: |
Over the last few decades, research works have focused on elucidating the optical properties of semiconductor materials. Despite remarkable progress in the measurement and calculation of the absorption coefficient for semiconductor materials, there is a lack of comprehensive review on the comparative study of absorption coefficient properties for different types of bulk semiconductor materials and their methods for calculating the absorption coefficient. Hence, this paper summarizes the fundamentals of the various methods used to determine the absorption coefficient properties of bulk growth semiconductor crystals, and discusses their advantages and disadvantages. Furthermore, this review provides comprehensive results from recent studies and findings on the absorption properties of near- to mid-infrared (wavelengths from 800 to 7300 nm) group III-V semiconductor materials. In addition, the absorption coefficient of the conventional group IV semiconductors (silicon and Ge) were included for performance comparison. Critical analysis was done for the reviewed materials concerning their material properties, such as band gap structure, crystal quality, and the structural design of the device. The related studies on the methods to determine the absorption coefficients of semiconductors and to improve the likelihood of absorption performance were well highlighted. This review also provides an in-depth discussion on the knowledge of absorption coefficient based on a wide range of semiconductor materials and their potential for sensors, photodetectors, solar and photovoltaic application in the near to mid infrared region. Lastly, the future prospects for research on absorption coefficients are discussed and the advancement in the determination of absorption coefficients for new ternary and quaternary materials is proposed using artificial intelligence such as neural networks and genetic algorithm. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
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