Porous Silicon–Based Microring Resonator for Temperature and Cancer Cell Detection

In this article, a microring resonator sensor based on porous silicon is proposed for temperature and cancer cell detection, simultaneously. The porous behavior of silicon with a large internal surface area allows external materials to interact directly with the guided modes. The resonance wavelength in the transmission spectrum of the microring resonator is very sensitive to external environmental properties such as refractive index and temperature. The transmission characteristics of the proposed sensor were numerically determined by full vectorial finite element analysis. The achieved maximum sensitivity of the proposed sensor with optimized parameters was 150 pm/°C for an operational temperature range of 20–100°C and 284.0306 nm/RIU for operational cancer cell detection, respectively. The results presented here suggest the microring resonator sensor can be used in the fields of environment sensing, temperature sensing, chemical sensing, and biosensing.

Introduction

The development of optical sensors to detect various biomolecules, viruses, and traces of hazardous gases is very important. Different kinds of optical sensors such as evanescent waveguides, Mach-Zehnder interferometers, optical fibers, slot waveguides, photonic crystals, and microring resonator–based sensors have been developed for the fast, sensitive, and selective detection of physical and chemical parameters in a surrounding medium [1–16]. Among various kinds of optical sensors, optical microring resonators (MRR) are probably the most often used photonic integrated structures used as a sensing device due to their high sensitivity, compact size, fast and accurate response, and structural simplicity [17–19]. Most of the MRR-based sensors are based on the evanescent wave detection method. The electromagnetic wave that propagates in the waveguide is accompanied by an evanescent wave that extends outside the ring and thus directly interacts with the surrounding analyte. This interaction is sensitive to changes in the refractive index (RI) of the analyte or temperature, resulting in a wavelength shift in the output spectrum of the device. This shift in wavelength can be used to detect anything that affects the optical properties of the MRR, for example, temperature or refractive index changes in the surrounding medium [20, 21]. In a practical optical sensing environment, both RI and temperature have a large effect on the wavelength shift of the transmission spectrum of the device. To date, different types of optical sensors have been established for dual parameter sensing. Shi et al. proposed a photonic crystal (PhC) sensor of two PhC nanobeam cavities as a dual parameter sensor with a refractive index sensitivity of 256.4 nm/RIU and temperature sensitivity of 30.1 pm/K, simultaneously [22]. However, the performances of these high-refractive index contrast-based planner photonic sensing devices are limited because most of the distribution of the optical field, associated with the guided mode, is propagated inside the waveguide itself.

To overcome these limitations and to enhance light-analyte interactions to improve its sensing capabilities, porous materials such as porous silicon (P-Si) have been used for MRR-based sensing devices [23–28]. Micro and nanostructured silicon is a three-dimensional porous material used to enhance molecular interactions with the guided electromagnetic fields. Because of the high specific internal surface, the number of binding sites for surface functionalization is increased, which enhances the light-analyte interactions and provides better sensing performance. Moreover, P-Si can be easily formed by the inexpensive electrochemical etching of a silicon substrate [29]. Rodriguez et al. first presented a P-Si-based MRR sensor for saltwater measurement with a sensitivity of 380 nm/RIU [30]. P-Si is very attractive because of its ultra-high internal surface and it is characterized by a very high surface-to-volume ratio. This allows the immobilization of a large amount of bioreceptors over the inner walls of the pores for the better detection of target biomolecules.

In this study, we present a P-Si MRR structure for the detection of temperature and various cancer cell types with a specific refractive index, simultaneously. By using the finite element method, we optimized the structural parameters of the structure and characterized the transmission response. Sensing performance against different temperatures and cancer cells was obtained simultaneously by measuring the wavelength shifts in the transmission spectrum of the MRR. P-Si was chosen in this study because of its large internal surface area, large surface functionalization chemistry, large achievable RI contrast between adjacent layers, and low cost compared with SOI. P-Si films can achieve a very large surface area of about 180 m²/cm³, which leads to improved sensor performance [31].

Theoretical Model and Analysis

The proposed sensing device for temperature and refractive index detection is shown in Figure 1. The P-Si ring and bus waveguide were placed on a thick silica substrate (n = 1.45). The outer and inner radii of the ring were 15 and 14.5 µm, respectively. The width of the waveguide is denoted by “w” and the distance between the bus waveguide and ring is denoted by “d.”

FIGURE 1

FIGURE 1. Cross-section of the proposed microring resonator–based temperature sensor.

The refractive index and porosity of silicon material were obtained by the following equation [32]:

$\left(1-p\right).\frac{n_s^2-n_{ps}^2}{n_s^2+2n_{ps}^2}+\left(p-V\right).\frac{n_a^2-n_{ps}^2}{n_a^2+2n_{ps}^2}+V.\frac{n_d^2-n_{ps}^2}{n_d^2+2n_{ps}^2}=0(1)$

where p is the porosity, n_s is the refractive index of silicon, n_ps is the refractive index of porous silicon, n_a is the refractive index of air, n_d is the refractive index of the analyte filled in pores, and V is the volume fraction of the pores. The porosity of P-Si is 55%, and the corresponding refractive index of P-Si is 1.9924.

For temperature sensing, the temperature-dependent refractive index of the material was obtained from the following equation [33]:

$n=n_0+\alpha \left(T-T_0\right)(2)$

where $n_0$ is the refractive index of the medium, $\alpha$ is the thermo-optic coefficient of P-Si, T is the final temperature, and $T_0$ is the initial temperature.

Figure 2A shows the variation in the refractive index of silicon with different porosities, and Figure 2B presents the refractive index of P-Si at different temperatures.

FIGURE 2

FIGURE 2. (A) Variations in the refractive index with porosity for silicon material and (B) variations in the refractive index with temperature for the porous silicon material.

The MRR intensity transmission was obtained by the following equation:

$T\left(\lambda \right)={\left|\frac{E_t}{E_i}\right|}^2(3)$

where ${\text{E}}_{\text{t}}$ and ${\text{E}}_{\text{i}}$ are the field amplitudes of the incoming and transmitted waves. At the output end of the waveguide, resonance occurs in the transmission spectrum at λ_res according to the following equation:

${\lambda }_{res}=2\pi L{n}_{eff}/p(4)$

where “L” is the perimeter of MRR, “n_eff” is the effective refractive index of the guided mode, and “p” is an integer parameter.

The proposed sensor was simulated in two dimensions with full vectorial finite element–based COMSOL Multiphysics software. During the simulation, the cross-section of the proposed sensor structure was divided into very small parts or meshes. To absorb light radiating towards the surface, perfectly matched layer boundary conditions were used. Simulation analysis was performed in the XY-plane and light was propagated in the Z-direction. Then, a free triangular mesh with an extremely fine mesh size containing 27,402 domain elements and 1,456 boundary elements was considered for the characterization of the proposed sensor and 192,617 degrees of freedom were solved during the simulation process.

The electric field distribution of the fundamental guided mode at different wavelengths with a fixed temperature (30°C) is shown in Figure 3. Here, we observed that light was well confined in the bus and ring waveguide. Also, coupling between the bus waveguide and ring waveguide occurred as shown in Figure 3B obtained from the simulation.

FIGURE 3

FIGURE 3. Electric field distribution when the temperature is fixed at 30°C, and when the wavelength is (A) 1,542 nm, (B) 1,546 nm, or (C) 1,550 nm.

Results and Discussion

Light entered one end of the bus waveguide and was coupled into the ring by evanescent coupling. The transmission spectrum of the structure was obtained at the other end of the bus waveguide. Figure 4 shows the transmission spectrum of the sensor at different distances “d” between the ring and waveguide when the RI of the sensing analyte was set as 1, that is, air at room temperature. The values of “d” varied from 200 to 500 nm at a gap of 100 nm. From these simulation results, we can see that when d = 300 nm, the transmission spectrum of the device was regular compared with the other samples. From these simulation results, we obtained an optimized value of “d” that was used for the rest of our studies because it had less distortion in the transmission spectrum, which is useful for the sensing analysis.

FIGURE 4

FIGURE 4. Transmission curve of the device for different distances between the ring and bus waveguide varying from 200 to 500 nm by 100 nm.

After obtaining the optimized value of “d,” we considered the effect of the width “w” of the ring and waveguide on the transmission properties of the structure. Figure 5 shows the obtained transmission spectrum of the structure at fixed “d” with different values of the waveguide and ring width “w,” which varied from 500 to 800 nm by 100 nm. Figure 5A represents the simulated transmission spectrum when “w” was set at 500 nm, which had four clear dips in the transmission spectra compared with the other values. This helps to measure the shift in the transmission spectrum when the device is subjected to variations in the surrounding parameters, in our case, temperature and refractive index, which have an impact on the transmission spectrum.

FIGURE 5

FIGURE 5. Transmission curve of the sensor for different widths of the ring and waveguide varying from 500 to 800 nm by 100 nm.

Using the optimized structural parameters, the present structure was used for temperature and refractive index detection. We changed the temperature of the surrounding environment from 20 to 100°C by 10°C. Figure 6A shows the simulated results of the variation in the transmission spectrum of the sensor at different temperatures. The inset of Figure 6Ashows an enlarged view of the transmission spectrum near 1,505 nm in which the corresponding dips in the transmission spectrum clearly shifts with the changes in temperature. There was a red shift in the transmission spectrum. Figure 6B depicts the simulation results of the variation in the dip wavelength around 1,505 nm with different temperatures. The dip wavelength shifted towards a higher wavelength as the temperature increased. The maximum sensitivity of the sensors subjected to temperature changes was 0.1515 nm/°C (151.5 pm/°C) for the temperature range 20–100°C with a linearity of 0.99623, which is better than previously published data [33–38]. Here, the light-matter interaction inside the pores was increased and because of this increased interaction, we obtained high sensitivity and good performance of the proposed sensor.

FIGURE 6

FIGURE 6. (A) Transmission spectra of the sensor with 55% porosity at different temperatures varying from 20 to 100°C. The inset shows the enlarged view of the transmission spectrum near the 1,505 nm wavelength. (B) Variations in the dip wavelength around 1,550 nm with different temperatures.

Next, the present sensor was tested for RI sensing. Here, we chose values of RI corresponding to different cancer cells whose refractive indexes vary between 1.380 and 1.401. Table 1 shows the refractive indexes of the different cancer cells [39].

TABLE 1

TABLE 1. Different cancer cells and their corresponding RI.

Figure 7A presents the obtained transmission spectra by the simulation of the proposed sensor when the RI of the surrounding medium was changed from 1.380 to1.401, related to the different cancer cells. When the RI of the target cells changed towards a higher value, the dip wavelength in the transmission spectrum changed from a lower wavelength to a higher wavelength; that is, a red shift occurred. We observed a shift in the dip wavelength corresponding to the different cancer cells in the inset of Figure 7A. The dip wavelengths of the transmission spectra for different target cancer cells and their corresponding RI are plotted in Figure 7B as obtained from the simulation results. By taking the slope of the plot, we obtained the sensitivity of the proposed sensor for cancer cell detection, which was approximately 284.0306 nm/RIU with a linearity of 0.97235. This high sensitivity value with very good linearity was achieved because of the porous nature of the ring that allowed the sensing material to be injected into the large volume inside the ring where most of the optical power is confined.

FIGURE 7

FIGURE 7. (A) Transmission spectra of the sensor with 55% porosity at different refractive indexes of cancer cells varying from 1.380 to 1.401. The inset shows an enlarged view of the transmission spectrum near the 1,510 nm wavelength. (B) Variations in the dip wavelength at different refractive indexes near 1,550 nm.

The present sensors can be realized experimentally in which a broadband source and optical spectrum analyzer are used. Light of different wavelengths from the broadband source will land on one end of the sensor bus waveguide with the help of conventional fibers and will then be collected by the optical spectrum analyzer at the other end. The sensing portion will be immersed in liquids with different refractive indices and the transmission characteristics of each will be observed. Shifts in the transmission spectrum will be used to determine the sensitivity of the proposed sensor.

Recently, the fabrication of a porous silicon–based microring resonator was reported by Rodriguez et al. [30]. First, the fabrication of P-Si slab waveguides was achieved by electrochemical etching. Then, a guiding layer was created by applying a current. Next, a cladding layer was etched, the samples were oxidized, and the resulting waveguides were fabricated. Rings were patterned on the fabricated waveguide using the reactive ion etching standard and electron beam lithography. Finally, different ring sizes rings were drawn. A short oxidation step was performed for the smooth sidewalls of the patterned P-Si ring resonator.

Conclusion

In conclusion, a P-Si-based MRR sensor was developed for the simultaneous sensing of different temperatures and detection of cancer cells. The sensing performance of the devices was characterized using the finite element method. The effects of various structural parameters were also investigated. Numerical results show the temperature sensitivity was 150 pm/°C for a temperature range of 20–100°C with a linearity of 0.99532 and RI sensitivity corresponding to the different cancer cells of 284.0306 nm/RIU. The enormous internal surface area of P-Si and its accompanying high light-matter interactions between the guided mode and target molecules in the pores give P-Si ring resonators a greater sensing capability than ordinary ring resonators. The proposed sensor has potential applications in the field of biosensing and the detection of multiparameters such as RI, temperature, and humidity.

Data Availability Statement

The raw data supporting the conclusion of this article will be made available by the authors, without undue reservation.

Author Contributions

RG: methodology, conceptualization, formal analysis, validation, funding acquisition, and writing—original draft. JQ: formal analysis, validation, and writing—review and editing. XW: conceptualization, formal analysis, validation, funding acquisition, supervision, and writing—review and editing.

Funding

This work was supported in part by the National Natural Science Foundation of China under Grant No. 62001010, National Key R&D Program of China under Grant No. 2021YFB2800400, and the Beijing Natural Science Foundation under Grant No. Z210004.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors, and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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