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Updated: Jun 24, 2026

Multimodal Nonlinear Hyperspectral Chemical Imaging Using Line-Scanning Vibrational Sum-Frequency Generation Microscopy
Published on: December 1, 2023
Hyperspectral imaging using a microelectrical-mechanical-systems-based in-plane vibratory grating scanner with a
Guangya Zhou1, Kelvin K L Cheo, Yu Du
1Department of Mechanical Engineering, National University of Singapore, Singapore. mpezgy@nus.edu.sg
A novel hyperspectral imaging system uses a microelectrical-mechanical-systems diffraction grating for rapid spatial scanning and mirrors for spectral scanning. This design enables high-speed, cost-effective imaging without performance loss from platform movement.
Area of Science:
- Optics and Photonics
- Microelectromechanical Systems (MEMS)
- Imaging Technology
Background:
- Hyperspectral imaging systems are crucial for various applications but often face challenges with speed, cost, and form factor.
- Existing systems can suffer from performance degradation due to platform instability and complex mechanical designs.
Purpose of the Study:
- To introduce a novel single-photodetector hyperspectral imaging system.
- To demonstrate a high-speed, compact, and potentially low-cost spectral imaging solution.
Main Methods:
- The system employs a microelectrical-mechanical-systems (MEMS)-driven diffraction grating for fast spatial scanning.
- Two synchronized steering mirrors are used for slow spectral scanning.
- The operational principle is validated using a prototype developed with silicon microfabrication technology.
Main Results:
- The proposed configuration achieves high-speed scanning capabilities.
- The system design mitigates optical performance degradation caused by dynamic non-rigid-body deformation.
- A functional prototype was successfully developed and demonstrated.
Conclusions:
- The developed hyperspectral imaging system offers a promising approach for high-speed, compact, and cost-effective spectral data acquisition.
- This technology has significant potential for applications requiring efficient spectral analysis.
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