# Liquid and gas mid-infrared integrated spectroscopic sensor

Sofiane Meziani, Abdelali Hammouti, Abdallah Jaafar, Loïc Bodiou, Nathalie Lorrain, Parastesh Pirasteh, Radwan Chahal, Albane Bénardais, Rémi Courson, Johann Troles, et al.

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To cite this version:

Sofiane Meziani, Abdelali Hammouti, Abdallah Jaafar, Loïc Bodiou, Nathalie Lorrain, et al. Liq-uid and gas mid-infrared integrated spectroscopic sensor. Optics Express, 2025, 33 (8), pp.17002.10.1364/OE.553730. hal-05101043

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# Liquid and gas mid-infrared integrated spectroscopic sensor

SOFIANE MEZIANI,¹ ABDELALI HAMMOUTI,¹ ABDALLAH JAAFAR,¹ LOİC BODIOU,¹ NATHALIE LORRAIN,¹ PARASTESH PIRASTEH,¹ RADWAN CHAHAL,² ALBANE BÉNARDAIS,² RÉMI COURSON,³ JOHANN TROLES,² CATHERINE BOUSSARD-PLEDEL,² VIRGINIE NAZABAL,² MOHAMMED GUENDOUZ,¹ AND JOËL CHARRIER¹,*

¹Univ Rennes, CNRS, Institut Foton-UMR 6082, 22305 Lannion, France

²CNRS UMR 6226 ISCR, Université de Rennes, 22302 Rennes, France

³Ifremer, RDT Research and Technological Development, F-29280 Plouzané, France

*joel.charrier@univ-rennes.fr

**Abstract:** Mid-infrared (mid-IR) waveguide sensors were fabricated using two platforms: chalcogenide glasses (ChGs) and porous silicon (PSi). ChGs layers were deposited through RF magnetron sputtering while PSi layers were prepared by electrochemical anodization. Ridge waveguides were patterned using standard i-line photolithography and reactive ion etching for both platforms. The ChGs waveguides exhibit a wide transparency range from $\lambda = 3.94$ to 8.95 µm, with a minimum propagation losses value of 2.5 dB/cm at $\lambda = 7.58$ µm, while PSi transparency range is from $\lambda = 3.94$ to 4.55 µm with a minimum propagation losses value of 9.1 dB/cm at $\lambda = 4.12$ µm. To validate the proposed ChGs sensor, a spectroscopic liquid sensing experiment was performed using acetonitrile and isopropanol. The results showed an estimated limit of detection (LoD) of 610 ppm at $\lambda = 4.44$ µm for acetonitrile and a LoD of 300 ppm at $\lambda = 7.25$ µm for isopropanol, enabled by the evanescent field interaction. Regarding gas sensing, CO₂ was used as the analyte. A LoD of 17000 ppm at $\lambda = 4.28$ µm was achieved using the ChGs platform. The sensing application was improved with the PSi platform. Due to the open pores, light and gas molecules interact within the internal volume, unlike the ChGs platform, where the interaction occurs with the evanescent part of the light. This results in an exalted external confinement factor, $\Gamma$, over 75 times greater for the PSi platform, achieving a LoD of 600 ppm at $\lambda = 4.26$ µm for CO₂ sensing. Estimation of concentrations from mixtures of two solutions through deconvolution of the measured spectra was also achieved with good approximations, validating the transduction capabilities in a complex environment using the ChGs platform.

Published by Optica Publishing Group under the terms of the [Creative Commons Attribution 4.0 License](https://creativecommons.org/licenses/by/4.0/). Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

## 1. Introduction

In recent years, there has been an increasing scientific focus on developing mid-IR photonic circuits specifically for optical sensing applications [1]. This interest has grown significantly due to remarkable advancements in optical sources like quantum cascade lasers (QCLs) [2], Interband cascade lasers (ICLs) [3] and supercontinuum sources [4]. The mid-IR wavelength range corresponds to the absorption bands of many toxic and pollutant molecules [5], making mid-IR spectroscopic sensors highly suitable for a wide variety of in-situ and challenging environmental applications. This level of performance has created an innovative need for materials and guiding structures. The use of integrated optical circuits as sensors presents several benefits, including lower manufacturing costs and more compact packaging, allowing for efficient
on-site measurement. However, the fabrication of these circuits requires the use of materials that are transparent in the mid-IR spectrum. Chalcogenide glasses (ChGs) and porous silicon (PSi) show great potential for the design of such circuits [6–9].

ChGs display a wide transparency window stretching from near-infrared into the mid-IR, up to 11 µm for sulfides, 15 µm for selenides, and 20 µm for tellurides [10]. They offer a range of advantageous properties for optical applications. Their refractive index can be precisely tuned by altering their composition, enabling accurate and efficient shaping of guiding structure. Furthermore, their high non-linear refractive index facilitates the occurrence of efficient non-linear phenomena, requiring lower incident powers or shorter lengths of light-matter interaction compared to silica and fluoride glasses [11,12]. Their low phonon energies also make them ideal hosts for rare-earth dopants [13]. ChGs have proven to be suitable for broadband mid-IR supercontinuum applications [14]. The potential of ChGs for designing guiding structures in integrated optics has been demonstrated in multiple studies. Propagation losses of 0.6 dB/cm were reported at wavelengths between $\lambda = 2.5$ and 3.7 µm [15], and high-quality factor ring resonators have been achieved at $\lambda = 5.2$ µm [16]. Advancements in the fabrication of ChG structures have led to a variety of sensing applications based on evanescent field spectroscopy. A rib $Ge_{1.15}As_{24}Se_{64.5}$ waveguide was used for sensing, as demonstrated with a solution of Prussian blue in Dimethyl Sulphoxide [17]. A methane gas sensor was demonstrated using a $Ge_{28}Sb_{12}Se_{60}$ waveguide [18]. Other sensing demonstrations were reported using ChGs for Isopropanol [19], $SF_6$ [20] and $CO_2$ [21].

Regarding porous silicon, it is transparent up to 8 µm and offers a porous structure, meaning it possesses pores and silicon crystallites at the nanoscale. The volume fraction of air corresponds to the porosity of the porous layer. This porosity can be modulated based on the parameters of anodization and is directly related to the refractive index. As porosity increases, the refractive index approaches that of air. The successive fabrication of multiple porous layers with different refractive indices allows for the creation of various optical structures such as waveguides [22], microresonators [23], Bragg mirrors [24], and microcavities [25]. In addition to its compatibility with CMOS technology [26], porous silicon holds great potential for the design of integrated optical circuits in the mid-IR domain [27]. Optical multilayer Bragg reflectors have been implemented using PSi layers in the Mid-IR [28].

The advantage of having a porous layer lies in the fact that the pores allow the penetration of substances in gaseous or liquid form into the integrated optical circuit. This increases the interaction between the probed molecules and the guided optical mode [29]. Consequently, this interaction within the internal volume [30]. This provides a large specific surface area, which can reach up to 800 m2cm⁻³ [31], making it also useful as a sacrificial layer in surface micromachining [32,33]. Additionally, these porous layers can be infiltrated with a variety of media, such as liquid crystals, thus offering the possibility of modifying photonic band gaps [34,35].

The sensing application of PSi has already been demonstrated in several publications, including the detection of various molecules in the gas phase [36,37] and liquid phase [38], humidity levels [39,40] and alcohol concentration [41]. It has also been used for the immobilization of DNA strands [42–44], detection of proteins and enzymes [45,46], hydrocarbons [47] and the detection of explosive vapors after surface functionalization with polymers [48]. In this paper, we compare mid-infrared ChGs and PSi platforms for $CO_2$ sensing. The PSi platform, with its porous structure, enhances light-matter interaction, overcoming the sensitivity limits of bulk materials, albeit with higher propagation losses and a shorter wavelength transparency range. By contrast, the ChGs platform exhibited lower sensitivity for $CO_2$ sensing. However, it leverages its broad transparency window to enable, in addition to gas-phase $CO_2$ detection, the sensing of liquid-phase analytes, such as acetonitrile and isopropanol with lower propagation losses. To address the challenge of sensing in complex environments, this work experimentally demonstrates the capabilities of the
ChGs platform by quantifying the relative concentrations of isomers 1-propanol and 2-propanol in mixed liquid solutions. These results highlight the potential of the developed platforms for real-world applications requiring multiphase detection and environmental analysis of various molecules. Figure 1 illustrates the waveguide transducer configuration used for both platforms. To control light-matter interaction within the ridge waveguide during sensing measurements, a polydimethylsiloxane (PDMS) microfluidic channel was bonded to the sample.

<figure><img src="image_4.png" /><figcaption>Fig. 1. Schematic of the waveguide transducer configuration used for both platforms. In the ChGs platform, the guiding and confinement layers are composed of Ge$_{12.5}$Sb$_{25}$Se$_{62.5}$ and Ge$_{28.1}$Sb$_{6.3}$Se$_{65.6}$ respectively. In the PSi platform, the guiding and confinement layers consist of porous silicon with 60% and 73% porosity, respectively</figcaption></figure>

## 2. Materials and methods

To support single-mode light propagation, the ridge waveguide structures were designed using a commercial software (FIMMWAVE, Photon Design), which also provided the external confinement factor Γ, a parameter that evaluates the fraction of the electric field interacting with the target analyte [49]. Γ is defined as below:

$$ \Gamma = \frac{n_g}{n_{\text{superstrat}}} \frac{\iint_{\text{superstrate}} \varepsilon |\vec{E}|^2 dxdy}{\iint_{\infty} \varepsilon |\vec{E}|^2 dxdy} \quad (1) $$

With n_g the group index, n superstrate the refractive index of the active sensing area, ε the permittivity and E the electric field.

In the case of waveguide based on porous material, light and molecules interact in the inside volume due to the open pores. From Eq. (1) the value of Γ can be expressed as follows:

$$ \Gamma = n_g \left( \frac{S_{\text{air}} + \varepsilon_{\text{guide}} S_{\text{guide}} \text{Porosity}_{\text{guide}} + \varepsilon_{\text{clad}} S_{\text{clad}} \text{Porosity}_{\text{clad}}}{S_{\text{air}} + \varepsilon_{\text{guide}} S_{\text{guide}} + \varepsilon_{\text{clad}} S_{\text{clad}}} \right) \quad (2) $$

With ε guide and ε clad representing the permittivity in the guide and cladding layer, respectively, S air , S guide and S clad are the integrals of the square of the field in the air, guiding, and cladding regions, respectively.

The ChGs samples were fabricated with a confinement layer of Ge$_{28.1}$Sb$_{6.3}$Se$_{65.6}$ with a thickness of 5 µm, and a guiding layer of composition Ge$_{12.5}$Sb$_{25}$Se$_{62.5}$. The layers were grown
on an n-type Si substrate using RF magnetron sputtering [9]. The refractive index values for the guiding and confinement layers were 2.77 and 2.49, respectively. These values remained relatively constant across the working wavelength range of $\lambda = 3.94$ to 8.95 µm.

For the PSi sample, the guiding and cladding layers were fabricated using a heavily doped P-type silicon (100) substrate with a resistivity of 5 mΩ·cm. The layers were formed by applying current densities of 50 mA/cm² and 100 mA/cm² for durations of 65 seconds and 102 seconds, respectively. The electrolyte consisted of hydrofluoric acid, ethanol, and deionized water in a 2:2:1 ratio. The refractive index was adjusted by varying the porosity, which was controlled by the applied current density [50]. As a result, two layers were produced: a 2.2 µm guiding layer with 60% porosity and a refractive index of 1.71, and a 5 µm cladding layer with 73% porosity and a refractive index of 1.48, both measured at a wavelength of 4.28 µm. The refractive index of each PSi layer was determined using FTIR reflectance spectra, with experimental spectral fringes fitted according to the Bruggeman effective medium approximation theory [51].

Following the fabrication of the thin film layers for both platforms, ChGs and PSi, single mode ridge waveguides were fabricated using a conventional i-line photolithographic process. This was followed by a dry etching procedure. For ChGs platform, the etching process utilized a gas mixture of 5 sccm CHF₃ at a pressure of 5 mTorr, with an ICP power of 75 W and an RF power of 25 W. Regarding the PSi platform, the waveguide was obtained through a dry etching step using 20 sccm of CHF₃ at a pressure of 5 mTorr, with an ICP power of 400 W and an RIE power of 25 W.

It should be noted that the dimensions of the waveguides are specifically designed for the respective operating wavelengths, in order to achieve single-mode propagation. At $\lambda = 4.28$ µm, the thickness of the ChGs guiding layer was $h = 1.2$ µm, and the width of the waveguide was $w = 6$ µm. This sample is noted “sample A” (Fig. 2(a)). For sensing measurements at a wavelength of 7.25 µm, the thickness of the ChGs guiding layer was increased to $h = 1.9$ µm, and the width of the waveguide was $w = 8$ µm. This sample is referred to as “Sample B”. PSi sample destined for CO₂ sensing is labeled “Sample C” (Fig. 2(b)), featuring a guiding layer thickness of $h = 2.2$ µm and a waveguide width of $w = 6$ µm. Table 1 summarizes the characteristics of the fabricated samples, including the corresponding external confinement factors.

<figure><img src="image_5.png" /><figcaption>Fig. 2. SEM Image of fabricated ridge waveguide using platform form a) ChGs b) PSi</figcaption></figure>

## 2.1. Mid-infrared optical bench and propagation losses

A mid-IR optical bench setup was assembled for the optical characterization of the guiding structures, as shown in Fig. 3. A tunable QCL source (MIRCAT, Daylight Solutions) was used, with an operating wavelength range from $\lambda = 3.94$ to 4.6 µm and $\lambda = 6.9$ to 11 µm. Butt coupling method was used between ChGs fiber and waveguides. At the output, the light beam from the waveguide was collimated into a detector using a ZnSe objective lens. Two detectors were used for the acquisition depending on the wavelength range: the DSS-PSE020 T, Horiba for 3.9 - 4.6
<table><caption>Table 1. Dimensions of waveguides used for operating wavelength ranges</caption><thead><tr><th>Name</th><th>Sample A</th><th>Sample B</th><th>Sample C</th></tr></thead><tbody><tr><td>Platform</td><td>ChGs</td><td>ChGs</td><td>PSi</td></tr><tr><td>Wavelength range (μm)</td><td>3.94–4.6</td><td>6.9–8.95</td><td>3.94–4.55</td></tr><tr><td>Thikness (μm)</td><td>1.2</td><td>1.9</td><td>2.2</td></tr><tr><td>Width (μm)</td><td>6</td><td>8</td><td>6</td></tr><tr><td>Γ<sub>TE</sub></td><td>9.1% (at λ= 4.28 μm)</td><td>5% (at λ= 7.25 μm)</td><td>111% (at λ= 4.26 μm)</td></tr><tr><td>Γ<sub>TM</sub></td><td>1.4% (at λ= 4.28 μm)</td><td>1.4% (at λ= 7.25 μm)</td><td>115% (at λ= 4.26 μm)</td></tr><tr><td>Sensing experiment</td><td>CO<sub>2</sub> and Acetonitrile</td><td>Isopropanol</td><td>CO<sub>2</sub></td></tr></tbody></table>

μm and the nitrogen-cooled DSS-MTC(14)-020 L, Horiba for 6.9 - 9 μm. The photolithography mask used in the fabrication included several sets of waveguides with varying lengths, allowing for the measurement of propagation losses using a non-destructive cut-back method. The QCL emission is polarized perpendicular to the base of the laser. However, since the fiber affects the mode's polarization, the coupled mode in the ridge waveguide is a random combination of the two fundamental modes. To properly perform the optical characterizations, the chalcogenide glass fiber's position must remain fixed throughout the measurements to maintain a stable coupling mode.

<figure><img src="image_6.png" /><figcaption>Fig. 3. Schematic diagram of the optical bench platform sensor</figcaption></figure>

To control the light-matter interaction within the ridge waveguide during the sensing test, a PDMS cell with a microchannel (500 μm thick, 5 mm wide, and 28 mm long) was bonded to the sample using O₂ plasma treatment.

The transmission of the waveguides was measured for each sample using the optical characterization bench. Sample A was used with waveguide lengths ranging from 10 to 15 mm, in 0.5 mm increments, over the wavelength range of λ = 3.9 to 4.6 μm. For sample B, the waveguide lengths ranged from 10.6 to 15.6 mm, also incremented by 0.5 mm, and measurements were performed in the wavelength range of λ = 7 to 8.95 μm. Sample C was used with waveguide lengths varying from 6.3 to 17.3 mm, with increments of 2 mm (except for the first increment of
1 mm). A decreasing exponential function was fitted to the measured signals to determine the propagation loss, for each wavelength range measurement.

Since no specific analyte is targeted during the propagation loss measurements, the contribution of absorption in the Beer-Lambert law is negligible. The behaviour of the transmitted signal can be described as follows:

$$P(\lambda) = P_0(\lambda) e^{-\alpha(\lambda) L_{\text{waveguide}}} \quad (3)$$

where $P_0$ is the input optical power, $\alpha$ are the propagation losses, and $L_{\text{waveguide}}$ is the length of the waveguide.

Figure 4 compares the propagation losses between ChGs and PSi. From $\lambda = 4$ to 4.2 µm, ChGs show lower propagation losses with Sample A, exhibiting values around 5.5 dB/cm, compared to PSi with Sample C, which exhibits higher values around 10 dB/cm. The absorption peak corresponding Se-H bond [52] in ChGs sample is visible on the propagation losses curve around $\lambda = 4.6$ µm, increasing losses up to 16 dB/cm. The drastic increase in loss values measured with the PSi sample is primarily attributed to free carrier absorption in the heavily doped bulk silicon substrate [53], scattering [54], and the adsorption of various molecules from ambient air within the pores. Additionally, silica ($SiO_2$) forms on the sample's surface due to interaction with ambient air, and its absorption in the working wavelength range further increases the propagation losses [30]. Recent work using slot waveguides [55], which enable volume interaction with the analyte, reported similar propagation losses of 10.4 dB/cm at $\lambda = 3.27$ µm. The contribution of adsorption losses from molecules present in the air was demonstrated by repeating the propagation loss measurements under nitrogen flow, which reduced the losses to 8.3 dB/cm.

<figure><img src="image_7.png" /><figcaption>Fig. 4. Propagation losses as a function of wavelength for ChGs and PSi ridge waveguides.</figcaption></figure>

Propagation losses in higher wavelength range are achieved with sample B on the ChGs platform. An average propagation losses value of 6.5 dB/cm are obtained from $\lambda = 7$ to 8.6 µm. The losses increase beyond 8.6 µm due to the waveguide dimensions not being optimized for these higher wavelengths. It can be observed that the minimum loss value of 2.5 dB/cm is obtained at $\lambda = 7.58$ µm, which aligns with the values reported in the state of the art for this wavelength range [56–59].

Propagation loss values are closely linked to the roughness of the waveguide sidewalls. Since the propagation is monomodal, the optical mode interacts strongly with the waveguide and substrate surfaces, where high roughness can lead to significant losses. Additionally, chemical residues, particularly fluoropolymers from the dry etching process, can absorb light at the working
wavelength, further increasing losses. These fluoropolymers deposit on the guiding structures during the dry etching process in the cleanroom. The influence of fluoropolymers on the ChGs platform was demonstrated by Ma et al. [60].

**3. Sensing demonstration**

Sensing tests were conducted on both platforms: using CO₂ for the PSi and using CO₂, acetonitrile, and isopropanol for the ChGs. The use of the PSi platform was limited to CO₂ due to its short transparency range, which does not cover the absorption peaks of acetonitrile and isopropanol.

**3.1. Liquid sensing tests**

For liquids analytes, we present the sensing tests performed using the ChGs platform. For wavelengths around 4 µm, nitriles are characterized by a sharp and high-intensity absorption band, corresponding to the C≡N stretching vibration between 4.42 and 4.5 µm [62]. We specifically chose acetonitrile due to its prominent absorption peak at 4.44 µm as shown in Fig.4a [63,64]. Isopropanol was also used due to its characteristic v(C-C) stretching vibrational mode at 7.25 µm [65] as shown in Fig. 4(b). A peristaltic pump was used to control the flow of analytes through the fluidic cell at a rate of 300 µL.min⁻¹. To prepare the different concentration, acetonitrile was diluted in ethanol, while isopropanol was diluted in cyclohexane, which is transparent within the working wavelength range.

To highlight the detection of acetonitrile in ethanol through spectral analysis, the transmission spectra of the ChGs sensor were recorded at various volume concentrations, ranging from 5% to 70%. The interaction length between the guided light and the solution was set at 7.8 mm using sample A. The transmission curves as a function of wavelength for different concentrations are shown in Fig. 5(c). For each point, the acquisition was averaged over three measurements, each lasting 300 ms at any given wavelength. Normalization of the curves was performed by dividing each transmission signal by that of the pure Ethanol. There is a strong correlation between the database spectra and our experimental measurements. A significant decrease in transmission is clearly observed at the wavelength corresponding to the absorption peak associated with the C≡N stretching vibration at λ = 4.44 µm. A secondary absorption peak at λ = 4.36 µm is also detected.

<figure><img src="image_8.png" /><figcaption>**Fig. 5.** Normalized absorption spectra from Ref. [61] for a) acetonitrile and b) isopropanol; Normalized ChGs waveguide transmission spectra for sensing of c) acetonitrile and d) isopropanol</figcaption></figure>
Two solutions of isopropanol in cyclohexane were also prepared with 10% and 20% concentrations. These measurements, shown in Fig. 5(d), were taken using Sample B, with an interaction length of 5.8 mm. A spectral signature similar to that found in the Ref. [61] for isopropanol in this wavelength range was observed. The v(C-C) stretching vibrational mode at $\lambda = 7.25$ µm is distinctly observed.

To better visualize the sensor response as a function of analyte concentration, wavelength emission was tuned to the maximum absorption peaks at 4.44 µm for acetonitrile and 7.25 µm for isopropanol. The acquisition was averaged more than 15 seconds for each concentration. These data are then plotted as a function of their respective concentrations in Fig. 6 for acetonitrile and isopropanol. The curves show good agreement with the decreasing exponential fit of the Beer-Lambert law:

$$P = P_0 e^{-(\epsilon \Gamma L C)} \quad (4)$$

With $P_0$ being the input optical power, $\epsilon$ the molar absorption coefficient of the analyte, $\Gamma$ the external confinement factor, $C$ the concentration, and $L$ the interaction length.

<figure><img src="image_9.png" /><figcaption>Fig. 6. Transmitted signal amplitude as a function of a) acetonitrile concentration diluted in ethanol for a fixed wavelength at $\lambda = 4.44$ µm with an interaction length $L = 7.8$ mm b) isopropanol concentration diluted in cyclohexane for a fixed wavelength at $\lambda = 7.25$ µm with an interaction length $L = 5.8$ mm.</figcaption></figure>

The sensitivity $S$ at the origin of each curve in Fig. 6 was firstly estimated to calculate the Limit of Detection (LoD). From Eq. (4), the sensitivity can be calculated by differentiating the signal $P$ with respect to the concentration $C$:

$$S = \frac{dP}{dC} = \epsilon \Gamma L P_{C=0} \quad (5)$$

The LoD can then be calculated using the following equation [66]:

$$LoD = 3.3 \frac{\sigma}{S} \quad (6)$$

where $\sigma$ is the standard deviation of the system noise.

From the data and of Fig. 6(a), we determined that the standard deviation of the signal at $C = 0$ mol.L$^{-1}$ was 0.68 mV. Additionally, the sensitivity of the measurement was calculated to be 96.2 nW L.mol$^{-1}$. Using these values, we estimated the LoD for acetonitrile sensing at 610 ppm (11.7 mmol.L$^{-1}$) at $\lambda = 4.44$ µm. Regarding Fig. 6(b), With a standard deviation of the signal at $C = 0$ mol.L$^{-1}$ of 48.3 µV and a sensitivity of 1.55 nW L.mol$^{-1}$, a LoD of 300 ppm (3.8 mmol.L$^{-1}$) was determined for isopropanol at $\lambda = 7.25$ µm. We note that the reduced standard deviation
observed in isopropanol sensing at 7.25 µm is directly attributed to the performance of the liquid nitrogen-cooled DSS-MCT(14)-020 L detector, which minimizes thermal noise. This detector differs from the thermoelectrically cooled DSS-PSE020 T used for acetonitrile sensing.

The performance of integrated optical sensors is generally evaluated by comparing their LoD values. However, this approach can compromise the fairness of the evaluation, particularly in terms of transduction, as it introduces biases related to the stability and resolution of both the laser source and the detector. A specific criterion focuses exclusively on the transducer part of the sensor, namely the figure of merit (FoM), which depends on two parameters of the transducer: the propagation losses α and the external confinement factor Γ:

$$FOM = \frac{\Gamma}{\alpha} \qquad (7)$$

The FoM (in cm) demonstrates that minimizing propagation losses and maximizing the external confinement factor enhances the transducer's performance, independently of the laser source and detector.

Table 2 compares the sensing characteristics of the ChGs platform with other works. It has been reported in the literature that IPA detection in acetone at a concentration of 5% was achieved using a germanium waveguide deposited on SiN at λ = 3.73 µm, with propagation losses of 7.86 dB/cm [67]. However, the high concentration in this reference can be explained by the weak absorption of isopropanol at λ = 3.73 µm compared to λ = 7.25 µm, even though the FoM achieved for this transducer is the highest in Table 2, nother study reported a diamond waveguide with losses of 5 dB/cm at λ = 7.215 µm, used for isopropanol detection with a LoD of 650 ppm [68].

<table><caption>**Table 2.** Comparison of sensing performance of the ChGs platform with literature for liquid phase molecule detection</caption><thead><tr><th>Molecules</th><th>λ (μm)</th><th>Structure</th><th>Interaction length (cm)</th><th>Losses (dB/cm)</th><th>Γ (%)</th><th>LoD (ppm)</th><th>FoM (cm)</th><th>Ref</th></tr></thead><tbody><tr><td>IPA</td><td>3.73</td><td>ChGs</td><td>0.402</td><td>7.86</td><td>12.8</td><td>50000</td><td>0.07</td><td>[67]</td></tr><tr><td>IPA</td><td>7.215</td><td>Diamond</td><td>0.5</td><td>5</td><td>-</td><td>650</td><td>-</td><td>[68]</td></tr><tr><td>IPA</td><td>7.25</td><td>ChGs</td><td>0.58</td><td>7.7</td><td>1.4 - 9.1</td><td>300</td><td>0.01-0.03</td><td>This work</td></tr><tr><td>Toluene</td><td>6.68</td><td>GOS</td><td>0.16</td><td>5</td><td>1.1</td><td>7</td><td>0.01</td><td>[5]</td></tr><tr><td>NH<sub>3</sub></td><td>9.54</td><td>GOS</td><td>0.052</td><td>1</td><td>1.2</td><td>0.4</td><td>0.05</td><td>[69]</td></tr><tr><td>Acetonitrile</td><td>4.44</td><td>ChGs</td><td>0.78</td><td>11</td><td>1.4 - 9.1</td><td>610</td><td>0.01-0.04</td><td>This work</td></tr></tbody></table>

Other studies have reported results on different liquids, such as toluene, which was detected at λ = 6.68 µm with an LoD of 7 ppm using a germanium waveguide on silicon with propagation losses of 5 dB/cm [5]. The low associated FoM suggests that this performance was achieved due to the stability of the laser source and detector used. A similar GOS platform with losses of 1 dB/cm was used for ammonia detection with an LoD of 0.4 ppm at λ = 9.54 µm [69]. The FoM calculated in [5] and [69] is closer to that of our transducer used for acetonitrile detection, with which we obtained an LoD of 610 ppm. We suppose that with the same stability of the laser and detector as in [5] and [69], our LoD for acetonitrile detection could be much lower.

## 3.2. Gas sensing tests

For CO₂ sensing, different concentrations were prepared by diluting CO₂ with nitrogen using flexible pipes that mix gas from two cylinders containing 100% N₂ and CO₂. The flow rates of the gases are regulated using a flow rate controller, with N₂ at 100 sccm (standard cubic centimeters per minute) and CO₂ at 50 sccm. The transmission spectra were measured for the two different
platforms, using ChGs sample A, and PSi sample C. The interaction lengths between the guided light and CO₂ were 10.8 mm and 8.3 mm, respectively. The maximum recorded absorption peaks correspond to the two absorption peaks listed at 4.23 µm and 4.28 µm in the HITRAN database [70], as shown in Fig. 7(a) and Fig. 7b. For the ChGs sample, transmission spectra were recorded for a CO₂ concentration of 35%, as presented in Fig. 7(c).

<figure><img src="image_10.png" /><figcaption>**Fig. 7.** a,b) Normalized CO₂ Absorption from 4.14 to 4.33 µm from HITRAN database [70]. Normalized transmission spectra for sensing of CO₂ c) using ChGs waveguide and d) using PSi waveguide.</figcaption></figure>

For the PSi sample, Fig. 7(d) shows transmission spectra for seven CO₂ concentrations ranging from 0.5% to 3.4%. A signal drop, corresponding to CO₂ absorption is observed starting at 0.5% concentration for the PSi platform. For the ChGs platform, the concentration needs to be increased to 35% to reach a comparable absorption level, using only about 20% of the detector's dynamic range. By contrast, measurements with the PSi platform show that a CO₂ concentration of just 3.4% can cover nearly the full dynamic range, demonstrating a significantly higher sensitivity compared to the ChGs platform.

In a similar approach to liquid sensing, we performed fixed wavelength measurements around the CO₂ absorption peaks. For the ChGs platform, the emission was tuned to the peak at 4.28 µm. As the signal drops quickly to the detector's noise floor at 4.28 µm or the PSi platform, we shifted the emission wavelength to 4.26 µm, and a shorter waveguide of 5.8 mm was used for fixed wavelength measurements.

Sensing experiments with the PSi platform in Fig. 8(b) show a significantly higher Beer-Lambert exponential coefficient than that with the ChGs platform (Fig. 8(a)). Taking into account the difference in absorption values at 4.28 µm and 4.26 µm, which results in a ratio of 1.86 (Fig. 7(d)), along with the difference in waveguide lengths, 0.78 cm for ChGs and 0.58 cm for PSi, the external confinement factor for PSi is 75 times greater than that of the ChGs platform. This ratio is closer to the *FIMMWAVE* simulated value of Γ for the TM mode, as summarized in Table 1.

From data of Fig. 8, a LoD of 17300 ppm at $\lambda = 4.28$ µm was estimated for the CO₂ sensing using ChGs platform. Regarding PSi platform, the estimated LoD was of 600 ppm at $\lambda = 4.26$ µm.

Table 3 compares the performance of the two CO₂ sensors developed in this work with those from the literature. In Ref. [71], a LoD of 500 ppm was reported, which is better than the 1000 ppm in [72]. However, this reference reported a higher Γ and lower propagation losses. This difference may be explained by the stability of the laser and detector used during the
<figure><img src="image_11.png" /><figcaption>**Fig. 8.** Transmitted signal amplitude as a function of CO₂ concentration using a) ChGs platform at λ = 4.28 µm with an interaction length L = 7.8 mm b) PSi platform at λ = 4.26 µm with an interaction length L = 5.8 mm.</figcaption></figure>

measurements in [71]. Additionally, the acquisition time was likely optimized to achieve such a LoD without resorting to WMS (wavelength modulation spectroscopy). The comparison criterion, which considers the transduction part of the sensor to be the FoM, highlights the performance of the suspended silicon sensor from [72] as superior to that of [71]. For our ChGs sensor, we achieved a FoM closer to that reported in Ref. [21], which is attributed to the low external confinement factor, amounting to only a few percent. Regarding the PSi sensor, its external confinement factor is the highest among the studies compared here, due to its enhanced bulk interaction. However, when comparing the FoM, its high loss values place it behind Ref. [72]. The losses in the PSi platform are high relative to other references, approaching those of the Si slot sensor mentioned in [55], which was used for CH₄ detection and achieved a LoD of only 1.54 ppm despite losses of 8.3 dB/cm. This demonstrates the effectiveness of bulk detection. In Ref. [55], the authors initially had 14 dB/cm losses but managed to reduce this to 8 dB/cm by performing an annealing process at 115°C while keeping the sample under nitrogen during measurement. The high losses observed in platforms with bulk interaction are mainly due to the adsorption of various molecules present in the ambient air within the guiding structures.

<table><caption>**Table 3.** Comparison of the characteristics of developed ChGs and PSi sensors with literature sensors for CO₂ detection</caption><thead><tr><th>Molecules</th><th>λ (μm)</th><th>Structure</th><th>Interaction length (cm)</th><th>Losses (dB/cm)</th><th>Γ (%)</th><th>LoD (ppm)</th><th>FoM (cm)</th><th>Ref</th></tr></thead><tbody><tr><td>CO₂</td><td>4.319</td><td>ChGs</td><td>1</td><td>5.1</td><td>4.6</td><td>25000</td><td>0.04</td><td>[21]</td></tr><tr><td>CO₂</td><td>4.26</td><td>Si ridge</td><td>2</td><td>3.98</td><td>14 - 16</td><td>500</td><td>0.15 - 0.17</td><td>[71]</td></tr><tr><td>CO₂</td><td>4.24</td><td>Si suspend</td><td>0.32</td><td>3</td><td>44</td><td>1000</td><td>0.64</td><td>[72]</td></tr><tr><td>CH₄</td><td>3.27</td><td>Si slot</td><td>1.15</td><td>8.3</td><td>69</td><td>1.54</td><td>0.36</td><td>[55]</td></tr><tr><td>CO₂</td><td>4.28</td><td>ChGs</td><td>1.08</td><td>6.8</td><td>1.4-9.1</td><td>17300</td><td>0.01 - 0.06</td><td>This work</td></tr><tr><td>CO₂</td><td>4.26</td><td>PSi</td><td>0.58</td><td>11.4</td><td>111 - 115</td><td>600</td><td>0.42-0.44</td><td>This work</td></tr></tbody></table>

In the case of porous silicon, free-carrier absorption in the highly doped silicon substrate and bulk scattering also increases propagation losses. Additionally, silicon oxide forms on the sample surface due to interaction with the ambient air. Despite these high losses, the FoM of the PSi platform remains significantly well placed compared to other sensors. We estimate that the
performance of the PSi sensor could be further improved by using the optimal calculated length of 4 mm, which is approximately equal to the inverse of the propagation losses.

### 3.3. Complex medium

Sensing in a complex environment within integrated optics presents a challenge, with few initiatives identified to our knowledge. As a proof of concept and to validate our sensor, we explored the deconvolution of spectra from mixtures of two distinct solutions. We began by preparing two stocks solutions by diluting 1-propanol and 2-propanol in acetonitrile with a concentration of 20%. Then, using these solutions, we prepared five mixtures with varying concentrations. Based on the spectra of these five mixtures and applying standard numerical processing using the least-squares method, we were able to approximate the concentrations of the two components (1-propanol and 2-propanol) within a mixture by leveraging the spectral fingerprints of the original solutions. Figure 9 shows the measurement obtained from a test solution prepared by mixing the two stock solutions, with a ratio of 50%.

<figure><img src="image_12.png" /><figcaption>**Fig. 9.** Normalized transmission of the ChGs waveguide as a function of wavelength with three different solutions in the fluidic cell: 1-propanol, 2-propanol and a mixed solution with 50% ratio of 1-propanol and 2-propanol.</figcaption></figure>

<figure><img src="image_13.png" /><figcaption>**Fig. 10.** Evaluation of correspondence between experimental and numerical concentrations.</figcaption></figure>
The developed numerical program aims to identify factors α and β such that the absorption of the combination of the two stock solutions, when scaled by these factors, closely matches the absorption of the mixed solution. This is achieved by minimizing the following function:

$$ \text{Fonction}(Abs_{mix}, Abs_{1pro}, Abs_{2pro}) = Abs_{mix} - (\alpha Abs_{1pro} + \beta Abs_{2pro}) \quad (8) $$

Where $Abs_{mix}$ represents the absorption of the mixed solution, and $Abs_{1pro}$ and $Abs_{2pro}$ are the absorptions of the stock solutions containing 20% 1-propanol and 20% 2-propanol in acetonitrile, respectively.

Table 4 summarizes both the experimental concentrations and those estimated by the numerical model for each prepared solution. These data are presented in Fig. 10. The results indicate a trend where the numerically estimated concentrations align with the experimental concentrations, even with a standard adjustment based on the least squares method. However, it is worth noting that a more sophisticated numerical treatment could further refine the results. These findings highlight promising prospects for the compatibility of evanescent wave-based optical transduction in complex environments.

<table><caption>Table 4. Comparison between the experimental concentrations of the solutions and those estimated by deconvolution model. The uncertainties in the calculated concentrations are based on a reading error of 0.05 ml, with solution volumes of 1.5 ml for solutions 1 and 2 ml for the other solutions</caption><thead><tr><th rowspan="2">Solutions</th><th colspan="2">Prepared concentrations</th><th colspan="2">Model estimation</th></tr><tr><th>1-Propanol (20%)</th><th>2-Propanol (20%)</th><th>1-Propanol (20%)</th><th>2-Propanol (20%)</th></tr></thead><tbody><tr><td>Solution 1</td><td>0.833 ± 0.066</td><td>0.167 ± 0.066</td><td>0.758 ± 0.066</td><td>0.242 ± 0.066</td></tr><tr><td>Solution 2</td><td>0.667 ± 0.050</td><td>0.333 ± 0.050</td><td>0.602 ± 0.050</td><td>0.397 ± 0.050</td></tr><tr><td>Solution 3</td><td>0.500 ± 0.050</td><td>0.500 ± 0.050</td><td>0.476 ± 0.050</td><td>0.524 ± 0.050</td></tr><tr><td>Solution 4</td><td>0.417 ± 0.050</td><td>0.583 ± 0.050</td><td>0.422 ± 0.050</td><td>0.578 ± 0.050</td></tr><tr><td>Solution 5</td><td>0.208 ± 0.050</td><td>0.792 ± 0.050</td><td>0.253 ± 0.050</td><td>0.747 ± 0.050</td></tr></tbody></table>

## 4. Conclusion

This work evaluated the performance of the two platforms, ChGs and PSi, in terms of integrated optics sensing in the mid-IR range. The ChGs waveguides exhibit a wide transparency range from $λ = 3.94$ to 8.95 µm, with a minimum propagation losses value of 2.5 dB/cm at $λ = 7.58$ µm, while PSi transparency range was from $λ = 3.94$ to 4.55 µm with a minimum propagation losses value of 9.1 dB/cm at $λ = 4.12$ µm.

Sensing measurements were conducted using Carbon dioxide to demonstrate gas phase transduction, while acetonitrile and isopropanol were used for the liquid phase. These measurements were carried out either through wavelength scans to observe the evolution of absorption spectra based on the concentration of the targeted molecules or statically by fixing the wavelength corresponding to an absorption peak of the analyte. The results showed an estimated LoD of 610 ppm at $λ = 4.44$ µm for acetonitrile and 300 ppm at $λ = 7.25$ µm for isopropanol, enabled by the evanescent field interaction. Regarding gas sensing, $CO_2$ was detected with a LoD of 17000 ppm at $λ = 4.28$ µm using ChGs platform. The sensing application was improved with PSi platform. Enhancement of the external confinement factor was experimentally observed during $CO_2$ sensing, exceeding 75 times ChGs platform. Due to the open pores, light and gas molecules interact within the internal volume, unlike ChGs platform where the interaction occurs with the evanescent part of the light. This volume interaction leads to a LoD of 600 ppm at $λ = 4.26$ µm for $CO_2$ sensing. To introduce sensing in complex environment, the extraction of concentrations from mixtures of two solutions was performed through deconvolution of
the measured spectra, yielding good approximations. These results validate the transduction
capabilities of the developed platforms in complex environments. Further expertise in signal
processing could enhance the analysis and improve transduction performance in the environment
with multiple analytes.

**Funding.** HORIZON EUROPE Framework Programme (101092723, IBAIA); Agence Nationale de la Recherche (ANR-21-CE04-011, AQUAE); Région Bretagne; Lannion-Trégor Communauté.

**Acknowledgments.** The ChGs layers fabrication was performed Thanks to Institut des Sciences Chimiques de Rennes (ISCR) and the technological processing of ridge waveguides was performed in the Centre Commun Lannionnais d'Optique (CCLO)-technological platforms which is supported by the French RENATECH + network.

**Disclosures.** The authors declare no conflicts of interest.

**Data availability.** Data underlying the results presented in this paper are not publicly available but may be obtained
from the authors upon reasonable request.

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