InGaAs NIR photodetectors are widely used due to their high responsivity, low noise, low dark current, fast response time, and large spectral range, which covers a range of 900 to 1700 nm and can be extended up to a 2600 nm cutoff. However, thermal drift is a major challenge that can affect the responsivity of these photodetectors, especially in miniaturized systems, where the thermal management problem is challenging. InGaAs photodetectors exhibit a highly nonlinear increase in responsivity near the cutoff, with an increase of about 4%/°C and a nonlinear reduction of about 0.25%/°C in the middle of the spectral range. This nonlinear drift cannot be corrected by common pre-processing methods used in spectroscopy. The change in responsivity near the cutoff is due to thermal-assisted bandgap reduction, while the change in responsivity in the middle of the spectral range is not well described in the literature. To address this issue, we applied the Urbach tail formula to model the nonlinear reduction of responsivity in the middle of the spectral range. The model showed an accuracy of approximately 90% compared to experimental thermal drift, allowing us to deduce the root causes of this phenomenon. Finally, we proposed compensation methods for the thermal drift, which were investigated using MOEMS FTIR spectral sensors as a case study. Some of these methods successfully reduced the drift that occurs due to a 60°C temperature change to less than 3%.
Diffuse reflectance infrared spectroscopy has gained traction in many industrial applications in the recent years due to the emergence of new generation of low cost handheld spectrometers that did not exist a decade ago. Real-time monitoring puts a limit on the sample preparation process especially with inhomogeneous samples in the food industry, like grains, hay, wheat and corn. The heterogeneity of the samples and the pseudo-random spatial arrangement of the grains in front of the optical interface, leads to prediction errors. The spatial variations depend also on the spot size of the diffuse-reflected scattered light from the sample that is collected by the spectrometer. A larger spot size leads to simultaneous averaging of a larger amount of spectrospatial information from different locations on the sample, leading to better repeatability and better prediction accuracy. Up to date, the Microelectromechanical (MEMS) based spectrometers reported in the literature have limited optical spot size, usually smaller than 3 mm in diameter. We report MEMS based FTIR spectral sensors with optical spot sizes of 6 mm, 10 mm and 20 mm working across the spectral range of 1350 nm to 2500 nm. The core spectral engine comprises monolithic MEMS chip, micro-optics for light coupling and a single photodetector in a tiny package. The optical head combines several miniaturized filament- based lamps and reflective optics for illumination. The sensors are compared and the 10-mm sensor gives an optimal performance with a Signal to Noise Ratio (SNR) of 4000:1 and spectrospatial photometric repeatability down to 0.02 absorbance units.
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