RESUMEN
This work aims to utilize a phase-shifting technique in a rectangular-type Sagnac interferometer (RTSI) to measure the thickness of a thin film of nickel (II) oxide (NiO) in an electron transport layer (ETL) in perovskite solar cell preparation. The NiO layer is deposited on a fluorine-doped tin oxide (FTO) glass substrate. In the RTSI setup, the signal output from the interferometer is divided into the reference and testing arms using a nonpolarizing beam splitter (NPBS). The balanced photodetectors then detect the signal, with the FTO/NiO layer placed in the testing arm and pure FTO in the reference arm. By analyzing the signal intensities at polarization settings of 0° to 180°, the phase shift and thickness of the NiO layer can be determined. The thickness values of FTO and NiO films obtained through three different phase-shifting algorithms of three-, four-, and five-steps are calculated. The obtained NiO thickness values are validated against scanning electron microscopy (SEM). Finally, by considering the NiO thickness value that exhibits the lowest percentage error compared to one from SEM, it is confirmed that the three-step algorithm is the most suitable scheme for obtaining intensities at 0°, 45°, and 90°. Therefore, the proposed setup shows promise as a replacement for SEM in thickness measurements.
RESUMEN
This work has implemented a diverse modification of the Sagnac interferometer to accommodate various measurement requirements, including phase shifting, pattern recognition, and a morphological analysis. These modifications were introduced to validate the adaptability and versatility of the system. To enable phase shifting using the multiple light reflection technique, a half-wave plate (HWP) was utilized with rotations at 0, π/8, π/4, and 3π/8 radians, generating four interference patterns. It is possible to observe a distinct circular fringe width as the polarized light experiences diffraction at the interferometer's output as it travels through a circular aperture with various diameters ranging from 0.4 to 1 mm. Further modifications were made to the setup by inserting a pure glass and a fluoride-doped tin oxide (FTO) transparent substrate into the common path. This modification aimed to detect and analyze a horizontal fringe pattern. Subsequently, the FTO substrate was replaced with a bee leg to facilitate morphology recognition. A deep learning-based image processing technique was employed to analyze the bee leg morphology. The experimental results showed that the proposed scheme succeeded in achieving the phase shift, measuring hole diameters with errors smaller than 1.6%, separating distinct transparent crystals, and acquiring the morphological view of a bee's leg. The method also has successfully achieved an accurate surface area and background segmentation with an accuracy over 87%. Overall, the outcomes demonstrated the potential of proposed interferometers for various applications, and the advantages of the optical sensors were highlighted, particularly in microscopic applications.