Design of an ultraviolet Raman spectrometer optical system based on freeform surfaces

Lu Wang; Yiyi Zhao; Bin Xue; Jingyun Zhang; Jianfeng Yang

doi:10.1117/12.3046469

26 September 2024 Design of an ultraviolet Raman spectrometer optical system based on freeform surfaces

Lu Wang, Yiyi Zhao, Bin Xue, Jingyun Zhang, Jianfeng Yang

Proceedings Volume 13282, Second Advanced Imaging and Information Processing Conference (AIIP 2024); 132820M (2024) https://doi.org/10.1117/12.3046469
Event: Second Advanced Imaging and Information Processing Conference (AIIP 2024), 2024, Xining, China

Abstract

Ultraviolet (UV) Raman spectroscopy, compared to visible Raman spectroscopy, offers advantages of higher Raman scattering intensity and no fluorescence interference. This paper designs a Czerny-Turner type UV grating spectrometer based on freeform surfaces. By analyzing the aberration principles of the Czerny-Turner spectrometer and combining the parameters of each component, an initial structure was established. For significant astigmatism in the system, optimization using freeform surfaces in the form of XY polynomials was performed, resulting in a UV grating spectrometer with a wavelength range of 250-310 nm and an object-side numerical aperture of 0.125 with a slit width of 20 μm. The spectral resolution simulation based on the line spread function indicated that the spectral resolution across the entire wavelength range is better than 0.085 nm. The modulation transfer function (MTF) results show that the MTF in both sagittal and tangential directions is close to the diffraction limit, indicating good image quality and the elimination of astigmatism while ensuring spectral resolution and improving energy concentration.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Lu Wang, Yiyi Zhao, Bin Xue, Jingyun Zhang, and Jianfeng Yang "Design of an ultraviolet Raman spectrometer optical system based on freeform surfaces", Proc. SPIE 13282, Second Advanced Imaging and Information Processing Conference (AIIP 2024), 132820M (26 September 2024); https://doi.org/10.1117/12.3046469

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