## 3 Results and Discussion
[32], as presented in Figure 11. While the model reproduces the optical response of silicon, with an increase in the responsivity and quantum efficiency as the wavelength increases, a discrepancy between the results can be observed. Once again, it is due to the presence of oxide layers on top of the photosensitive areas of the experimentally characterized photodiodes, which led to the presence of small oscillations and peaks in the quantum efficiency spectra. Moreover, the experimental values suggested that larger active areas were related to photodiodes with higher quantum efficiency. However, such results may have occurred due to experimental difficulties in accurately measuring such small optical apertures. The simulated results show that, as expected, while there are small differences between the simulated curves, the active area has no significant importance in the quantum efficiency of a photodiode. Finally, the simulation of the p+/n-well 0.7 \(\upmu\)m photodiode reported in this work presents a similar quantum efficiency maximum in comparatio  
Figure 11: Comparison between the numerical (simulated in COMSOL) and experimental (data obtained from [32]) quantum efficiency (%) of n+/p-substrate photodiodes using the 0.7 \(\upmu\)m technology. it occurs in a different region from the photodiode presented by [PERSON] et al. With respect to n-well/p-substrate and p+/n-well photodiodes, since no other n-well/p-substrate and p+/n-well photodiodes have been reported in the literature for the 0.18 \(\upmu\)m technology, these results cannot be directly compared. In order to evaluate the effect of different oxide layers on the optical behavior of photodiodes, Figure 12 presents the comparison between the quantum efficiency curves of a 100 \(\times\) 100 \(\upmu\)m\({}^{2}\) n+/p-substrate photodiode, using the 0.7 \(\upmu\)m technology, with and without oxide layers. For that purpose, the transmittance spectra of different oxide layers was evaluated, which was taken into account in the photodiode performance. To understand its influence, different simulations were performed, varying the number of oxides and their refractive index. The oxide thicknesses used correspond to the default layer thicknesses in the 0.7 \(\upmu\)m technology (660 nm and 600 nm for oxides 1 and 2, respectively), according to [1]. The refractive indexes in the simulations correspond to the refractive index of silicon dioxide (SiO\({}_{2}\)), \(n=1.45\) and silicon nitride (Si\({}_{3}\)N\({}_{4}\)), \(n\approx 2\), for comparison purposes. From the new data, it was possible to obtain the quantum efficiency curve of the n+/p-substrate photodiode in the 0.7 \(\upmu\)m technology with the effect of the oxides, as shown in the Figure 12. Comparing the results, it is verified that the obtained quantum efficiency curves have oscillation peaks similar to the experimental data available. It shows that, in fact, the presence of oxides and their characteristics (material, thickness and number of layers) affect the overall performance of the photodetector. The results show that, globally, the greater the junction depth, the lower the expected quantum efficiency. This is explained by the fact that the depth of light penetration into silicon is wavelength dependent. Thus, shallow junctions (such as the n+/p-substrate or p+/n-well structures) collect the lower wavelengths of light more efficiently, while the higher efficiency presented by the n+/p-substrate, above 500 nm, is related to the difference in doping concentrations between the n and p sides, which extends the p-side depletion area deeper [12]. Figure 12: Comparison between the numerical (simulated in COMSOL) and experimental (data obtained from [32], when it was considered 2 oxide layers) quantum efficiency (%) of n+/p-substrate photodiodes with 100 \(\times\) 100 \(\upmu\)m\({}^{2}\) using the 0.7 \(\upmu\)m technology, with and without oxide layers on top of the photodiodes. In the plots, \(n\) corresponds to the refractive index of the oxide layers.