Volume 14 Issue 3
May  2021
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LÜ Xiao-lei, ZHAO Ji-guang, DU Xiao-ping, SONG Yi-shuo, ZHANG Peng, ZHANG Jian-wei. Research progress on the modulation properties of new electro-optic materials[J]. Chinese Optics, 2021, 14(3): 503-515. doi: 10.37188/CO.2020-0039
Citation: LÜ Xiao-lei, ZHAO Ji-guang, DU Xiao-ping, SONG Yi-shuo, ZHANG Peng, ZHANG Jian-wei. Research progress on the modulation properties of new electro-optic materials[J]. Chinese Optics, 2021, 14(3): 503-515. doi: 10.37188/CO.2020-0039

Research progress on the modulation properties of new electro-optic materials

doi: 10.37188/CO.2020-0039
Funds:  Supported by National Natural Science Foundation of China (No. 61805284)
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  • Corresponding author: zhaoyy8600@163.com
  • Received Date: 2020-03-10
  • Rev Recd Date: 2020-04-14
  • Available Online: 2021-04-17
  • Publish Date: 2021-05-14
  • Polarization modulation technology based on electro-optic crystals is playing an increasingly important role in the field of three-dimensional laser imaging. Due to the low field of view and high half-wave voltage of LiNiO3 (LN) materials, it is difficult for traditional electro-optic modulation technology to further improve 3D imaging performance. As the preparation technology of perovskite-structured electro-optical materials becomes more mature, electro-optic modulation technology based on new materials will become an excellent means to create a breakthrough in the detection accuracy of laser 3D imaging. PMNT, PLZT and KTaxNb1-xO3 (KTN) three typical materials have excellent electro-optical properties and dielectric properties that might surpass the field of view and half-wave voltage limitation. However, their applications in electro-optic modulation has lead to difficulties such as a low modulation bandwidth for PMNT, poor transmission performance for PLZT, and low practical application bandwidth for KTN. Future research will focus on the practicality of this modulation technology. The electro-optic modulation performance can be improved by doping and the signal-to-noise ratio of the system can be optimized by establishing performance characterization models.
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