# Agile plasmo-photonic interferometric sensor with liquid dielectric loading for temperature sensing and thermo-optic coefficient measurements

Lamprini Damakoudi, Stelios Simos, Dimosthenis Spasopoulos, Konstantinos Fotiadis, Evangelia Chatzianagnostou, Omkar Bhalerao, Stephan Suckow, Max C Lemme, Laurent Markey, Dimitris V Bellas, et al.

<figure><img src="image_1.png" /></figure>

## ► To cite this version:

Lamprini Damakoudi, Stelios Simos, Dimosthenis Spasopoulos, Konstantinos Fotiadis, Evangelia Chatzianagnostou, et al. Agile plasmo-photonic interferometric sensor with liquid dielectric loading for temperature sensing and thermo-optic coefficient measurements. IEEE Sensors Journal, inPress, pp.1 - 1. 10.1109/JSEN.2025.3648036. hal-05474342

HAL Id: hal-05474342

https://hal.science/hal-05474342v1

Submitted on 23 Jan 2026

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<figure><img src="image_2.png" /></figure>
Agile plasmo-photonic interferometric sensor
with liquid dielectric loading for temperature
sensing and thermo-optic coefficient
measurements

Lamprini Damakoudi, Stelios Simos, Dimosthenis Spasopoulos, Konstantinos Fotiadis, Evangelia Chatzianagnostou, Omkar Bhalerao, Stephan Suckow, Max C. Lemme, Laurent Markey, Dimitris V. Bellas, Eleftheria Lampadariou, Elefterios Lidorikis, Nikos Pleros, and Konstantinos Vyrsokinos

**Abstract**— This work presents an integrated plasmo-photonic interferometric sensor providing environmental temperature and thermo-optic coefficient measurement capabilities. By exploiting extreme light field concentration on the plasmonic metal stripe, the sensor employs a liquid dielectric layer deposited on the plasmonic sensing area for refractive index changes versus temperature. Experimental characterization was conducted with four different liquids, achieving a record temperature sensitivity of +23.86 nm/°C for a 70% ethanol-water solution. Additionally, by leveraging the sensor's high sensitivity, the thermo-optic coefficient of an unknown liquid was determined with a relative error of 13.1%.

3D schematic

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Record-high sensitivity

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Thermo-optic coefficient measurement

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**Index Terms**— Bimodal, photonic integrated circuits, plasmo-photonic sensors, temperature sensors, thermo-optic coefficient sensors.

I. Introduction

FAST and precise measurement of environment's temperature is crucial in a wide variety of applications and across different industries. The ability to detect very small temperature variations is particularly important in areas requiring high thermal resolution, such as biochemical and cellular sensing,

where temperature fluctuations are typically below 1 °C. These subtle changes often reflect critical biological phenomena and carry important information about vital processes such as cell metabolism, enzymatic reactions, and neuronal activity [1],[2]. In addition, the accurate and precise measurement of liquid's thermo-optic coefficient (TOC) is very important for different applications where changes in refractive index due to

This work was supported by European projects ICT GRACED (no. 101007448) and AMBROSIA (no. 101093166). (Corresponding author: Lamprini Damakoudi.)

Lamprini Damakoudi and Konstantinos Vyrsokinos are with the Department of Physics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece, and also with the Center for Interdisciplinary Research and Innovation (CIRI-AUTH), Balkan Center, Buildings A & B, 57001 Thessaloniki, Greece (e-mail: damakoudi@auth.gr).

Stelios Simos, Konstantinos Fotiadis, Dimosthenis Spasopoulos, Evaggelia Chatzianagnostou, and Nikos Pleros are with the Department of Informatics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece, and also with the Center for Interdisciplinary Research and Innovation (CIRI-AUTH), Balkan Center, Buildings A & B, 57001 Thessaloniki, Greece.

Omkar Bhalerao and Max C. Lemme are with the AMO GmbH, Otto-Blumenthal-Str. 25, Aachen, 52074, Germany, and also with the Chair of Electronic Devices, RWTH Aachen University, Otto-Blumenthal Str. 25, Aachen, 52074, Germany.

Stephan Suckow is with the AMO GmbH, Otto-Blumenthal-Str. 25, Aachen, 52074, Germany.

Laurent Markey is with Laboratoire Interdisciplinaire Carnot de Bourgogne CNRS UMR 6303, Université Bourgogne Europe, 21000 Dijon, France.

Dimitris. V. Bellas, Eleftheria Lampadariou, and Elefterios Lidorikis are with the Department of Materials Science and Engineering, University of Ioannina, 45110 Ioannina, Greece.
temperature variations must be precisely controlled, such as in
optical communication systems, laser design, photonic devices,
and temperature-sensitive optical applications. These
measurements are performed currently by various methods such
as electrical, calorimetric, etc., but the latest trend is to employ
light due to numerous advantages, such as immunity to
electromagnetic interference, stability, multiplexing
capabilities, and resistance to harsh environments [3]-[5]. The
first light based prototypes were relying on optical fibers and
exploited their long interaction lengths with the material under
test to deliver both temperature [6] and TOC [7],[8]
measurements. A variety of sensing architectures have been
developed following this scheme, including Fabry-Perot
[9],[10] and Mach-Zehnder interferometers [11], fiber gratings
[11],[13], and multimode interference (MMI) devices [14],
demonstrating significant advancements in sensitivity, stability,
and accuracy [15]. However, the temperature sensitivity in
these schemes is still limited by the relatively low thermal
expansion coefficient and low TOC of the silica fiber. To
address these challenges various temperature sensitive
materials have been utilized as claddings to assist the sensor's
performance, such as graphene [16], PDMS [17], polymeric
materials [18], and isopropyl alcohol [19]-[21], achieving
sensitivity values up to decades or hundreds of nm/°C. Despite
these improvements, these configurations are bulky and lack the
integration ability, necessitating the need for more compact and
versatile solutions that can be integrated in mobile platforms.

The progress of the Silicon (Si) photonics technology in the
last twenty years enabled a new miniaturized generation of
sensors with the most advanced ones relying on the Silicon-On-
Insulator (SOI) platform allowing also the co-integration of
electronics for a complete lab on a chip solution. However, the
sensitivity of these sensors is limited to a few decades or
hundreds of pm/°C. For instance, PIC-based sensors fabricated
on 220 nm SOI platforms with periodic Bragg grating elements
have demonstrated sensitivities around 85 pm/°C [22], while
asymmetric Mach–Zehnder interferometers (MZIs) on SOI
have achieved sensitivities of about 445 pm/°C through
optimized arm design [23]. Even different platforms and
techniques have been investigated, to improve sensitivity and
thermal response. On this scheme, silicon nitride-based
cascaded MZI structures have been proposed reaching
sensitivities as high as 710 pm/°C, due to tailored geometries,

despite the material’s relatively low thermo-optic coefficient
[24]. Comparable performance has also been obtained using
femtosecond laser-written MZIs embedded in soda-lime glass,
where three-dimensional structural tuning enabled sensitivities
up to 320 pm/°C [25]. Enhanced performance was obtained by
incorporating materials with high negative TOC as the top
cladding, including polymers, TiO2, and liquid crystal (LC)
[26]–[29]. In this rationale, a Photonic Integrated Circuit (PIC)
sensor with LC-cladding has demonstrated sensitivities of
1.619 nm/°C, though this requires a sensing device length of 1.5
mm [28]. An even higher sensitivity of 1.753 nm/°C was
reported in [30], at the cost though of a large footprint due to
the cascaded MZI configuration. PICs based on various
configurations including micro-disk cavities [31],[32],
photonic crystal nanocavities [33] and microring resonators
[34],[35] have been also proposed for TOC measurement
applications, exhibiting high accuracy of up to 98%, while
featuring compact size. These devices, on the other hand require
complex techniques for the deposition of the material under
measurement, such as spin-coating and annealing, limiting the
use of the sensor to measuring the TOC of only one material at
a time, while in some cases, they also demonstrate limited
temperature sensitivity [35].

In this work, we present an experimental demonstration of an
integrated plasmo-photonic bimodal interferometric sensing
platform that can be used for temperature measurements and
TOC identification. By exploiting the extreme light field
concentration on the plasmonic metal stripe, any change in the
refractive index of the liquid dielectric loading on top of the
plasmonic sensing area can be measured with very high
accuracy through interferometry. Experimental
characterization conducted with four different liquids, revealed
a record-high temperature sensitivity of +23.86 nm/°C for a
70% weight (wt.) ethanol-water solution, that represents a more
than tenfold improvement over the previously reported highest
sensitivity of 1.753 nm/°C measured with PICs [30]. The
proposed sensor configuration can also serve as a TOC
measuring sensor for liquids succeeding in measuring the TOC
value of an unknown test material, with a relative error of
13.1%. This value can be further enhanced through an improved
calibration process. Another major advantage of the proposed
device compared to other PICs targeting thermo-optic
measurements [31]-[34], is its flexibility over a wide range of

<figure><img src="image_6.png" /><figcaption>Fig. 1. (a) 3D conceptual design and (b) side-view of the plasmo-photonic bimodal interferometric temperature sensing platform. (c) Mode profiles of the photonic (left), top SPP (middle) and bottom SPP (right) modes.</figcaption></figure>
liquids that can easily be applied to the sensor surface without any need for preparation of the sample or the device, allowing seamless switching between microfluidic channels. All these features highlight the suitability of the proposed sensing platform for temperature related liquid material analysis.

## II. PRINCIPLE OF OPERATION

A 3D conceptual schematic of the plasmo-photonic bimodal interferometric PIC acting as the proposed temperature sensor is presented in Fig. 1(a). The photonic input consists of an SU-8 polymer waveguide with a cross-section of 1.8 µm (height) × 2 µm (width), that is tapered up to a width of 7 µm before being thinned to a height of 0.9 µm along a 75 µm path. A CMOS-compatible aluminum (Al) metal stripe, with a cross-section of 80 nm (height) × 7 µm (width), is deposited on the thinned SU-8 layer. The fabrication process of the sensors used in this work follows the same procedure detailed in our previous publication [36]. The process started with the deposition of a 3 µm thermally grown SiO₂ layer on 150 nm silicon substrates. A bilayer SU-8 (SU-8 2) waveguide stack was realized through sequential spin-coating, lithography, and thermal curing, resulting in a total SU-8 thickness of 1800 nm that formed the photonic waveguide. Subsequently, an 80 nm-thick aluminum film was deposited by electron-beam evaporation and patterned using AZ 5214E photoresist and a buffered phosphoric acid wet etch. An adhesion promoter was finally processed on top of the SU8 waveguides, yielding an approximately 6 µm-thick clad with a refractive index of ~1.42 at 1.55 µm. Finally, the wafers were diced into 2 × 2 cm chips with optically smooth coupling facets. This configuration forms a plasmonic waveguide with two metal/insulator interfaces at the top and bottom surfaces of the metal stripe. A fundamental TM mode supported at the tapered photonic waveguide, once reaches the photonic-plasmonic interface, excites two SPP modes, one on each surface of the metal. These modes propagate along the metal surfaces and interfere at the photonic SU-8 waveguide's output, as can be seen in Fig. 1(b), with the profile of each mode presented in Fig. 1(c). In this way, a single-arm interferometer is realized. The photonic waveguides are coated with a polymer "Allresist" cladding layer, while the plasmonic waveguide remains exposed. The operation of the device as a refractive index sensor when aqueous solutions are used on top of the sensor is presented in detail in [36]-[38].

In the current configuration, the plasmonic region formed on top the metallic stripe can be filled with a thermo-optically sensitive liquid material, so that any temperature change translates into a refractive index change of the liquid material depending on its TOC. A respective refractive index change takes place also at the SU-8 waveguide below the metallic stripe due to the corresponding TOC of the SU-8 material. The differing TOCs of the liquid and the SU-8 waveguide on top and below the metallic stripe, respectively, lead to a variation in the difference between the effective indices experienced by the upper and lower surface plasmon polariton (SPP) modes. This differential refractive index change alters the sensor spectral response leading to a wavelength shift of its resonance wavelengths. This shift can occur towards higher (redshift) or lower (blueshift) wavelengths, depending on the difference between the TOCs of the overlying liquid and the SU-8.

A simplified model for predicting the direction of sensor wavelength resonance shift due to TOC differences can be derived from the following expression:

$$ \lambda_{res} = \frac{n_{eff,bottom} \times L_{pl} - n_{eff,top} \times L_{pl}}{k} \quad (1) $$

, where $n_{eff,bottom}$ and $n_{eff,top}$ are the effective indices of the bottom and top SPP modes, respectively, $L_{pl}$ is the length of the plasmonic stripe and $k$ the interference order. Once the temperature changes from $T_0$ to $T_1$ the resonance wavelength will change from $\lambda_{res}$ to $\lambda'_{res}$, which will be equal to:

$$ \lambda'_{res} = \frac{n'_{eff,bottom} \times L_{pl} - n'_{eff,top} \times L_{pl}}{k} \quad (2) $$

, where $n'_{eff,bottom}$ and $n'_{eff,top}$ are the effective indices of the bottom and top SPP modes, respectively, at temperature $T_1$. The alteration of the effective index resulting from temperature changes arises from the materials' refractive index variation across all the layers where the mode is distributed. Consequently, the effective index change of the bottom mode, induced by temperature variation, can be expressed as follows:

$$ \frac{dn_{eff,bottom}}{dT} = \frac{\partial n_{eff,bottom}}{\partial n_{liquid}} \times \frac{dn_{liquid}}{dT} + \frac{\partial n_{eff,bottom}}{\partial n_{SU-8}} \times \frac{dn_{SU-8}}{dT} + \frac{\partial n_{eff,bottom}}{\partial n_{SiO_2}} \times \frac{dn_{SiO_2}}{dT} + \frac{\partial n_{eff,bottom}}{\partial n_{Si}} \times \frac{dn_{Si}}{dT} \quad (3) $$

Given that the refractive index change by temperature change is the thermo-optic coefficient of the material, the above expression can be transformed into

$$ \frac{dn_{eff,bottom}}{dT} = \frac{\partial n_{eff,bottom}}{\partial n_{liquid}} \times TOC_{liquid} + \frac{\partial n_{eff,bottom}}{\partial n_{SU-8}} \times TOC_{SU-8} + \frac{\partial n_{eff,bottom}}{\partial n_{SiO_2}} \times TOC_{SiO_2} + \frac{\partial n_{eff,bottom}}{\partial n_{Si}} \times TOC_{Si} \quad (4) $$

Similarly, for the top mode the effective index change with respect to temperature change is given by

$$ \frac{dn_{eff,top}}{dT} = \frac{\partial n_{eff,top}}{\partial n_{liquid}} \times TOC_{liquid} + \frac{\partial n_{eff,top}}{\partial n_{SU-8}} \times TOC_{SU-8} + \frac{\partial n_{eff,top}}{\partial n_{SiO_2}} \times TOC_{SiO_2} + \frac{\partial n_{eff,top}}{\partial n_{Si}} \times TOC_{Si} \quad (5) $$

Considering that the effective index change of the bottom SPP mode is primarily affected by the refractive index change of SU-8, as the mode is highly confined to this layer, the most significant term on (4) is $\frac{\partial n_{eff,bottom}}{\partial n_{SU-8}} \times TOC_{SU-8}$. Similarly, the top plasmonic mode is highly impacted by the refractive index change of the liquid placed on top of the Al stripe, and therefore the most significant term on (5) is $\frac{\partial n_{eff,top}}{\partial n_{liquid}} \times TOC_{liquid}$. Based
on that, (2) can be rewritten as:

$$ \lambda'_{res} = \frac{L_{pl}}{k} \times \left( n_{eff,bottom} + \frac{\partial n_{eff,bottom}}{\partial n_{SU-8}} \times TOC_{SU-8} \times \Delta T - \left( n_{eff,top} + \frac{\partial n_{eff,top}}{\partial n_{liquid}} \times TOC_{liquid} \times \Delta T \right) \right) \quad (6) $$

Considering Eq. (1), Eq. (6) can be written as follows:

$$ \lambda'_{res} = \lambda_{res} + \frac{L_{pl}}{k} \times \left( \frac{\partial n_{eff,bottom}}{\partial n_{SU-8}} \times TOC_{SU-8} - \frac{\partial n_{eff,top}}{\partial n_{liquid}} \times TOC_{liquid} \right) \times \Delta T \quad (7) $$

Assuming that the effective refractive index of the system responds equally to changes in the refractive indices of the respective materials, as shown in [39], the terms $\frac{\partial n_{eff,bottom}}{\partial n_{SU-8}}$ and $\frac{\partial n_{eff,top}}{\partial n_{liquid}}$ are equal to 1, Eq. (7) is transformed into:

$$ \lambda'_{res} = \lambda_{res} + \frac{L_{pl}}{k} \times (TOC_{SU-8} - TOC_{liquid}) \times \Delta T \quad (8) $$

or equivalently into:

$$ \Delta\lambda_{res} \propto (TOC_{SU-8} - TOC_{liquid}) \times \Delta T \quad (9) $$

Consequently, for increasing temperature ($\Delta T > 0$), if the difference of the two TOC values is negative a shift towards lower wavelength values (blueshift) will be observed, while for a positive $TOC_{SU-8} - TOC_{liquid}$ difference, there will be a redshift. Eq. (9) also reveals that the magnitude of the resonance wavelength shift depends on the absolute difference between the two TOCs. Therefore, for the same temperature change, a higher TOC difference will lead to a larger wavelength shift of the resonance peak. It is important to note that equation (9) can effectively predict only the direction of the resonance wavelength shift, but not the absolute magnitude of the shift. This limitation arises from the assumptions made to simplify the model. However, it is still useful for the unknown TOC identification measurements as will be shown in the following Section III.

### III. EXPERIMENTAL SETUP AND EXPERIMENTAL RESULTS

Fig. 2(a) illustrates the experimental setup employed for the temperature evaluation measurements. A tunable laser source (TLS, model: SANTEC TSL-570) is used to scan the wavelength range of 1480–1640 nm, with a resolution of 100 pm. The output power is recorded by a fast optical power meter (OPM, model: SANTEC MPM-211). The light is coupled to the chip via a single-mode lensed polarization maintaining fiber, while a single mode fiber collects the light at the output. The sensor is heated using a Peltier module positioned beneath the chip holder, with temperature measurements taken by a thermistor placed near the chip, at a position shown in Fig. 2(b). The temperature at the sensing area is set and controlled using a thermoelectric temperature controller. Additionally, an infrared (IR) thermal camera, is facing the chip’s surface measuring simultaneously the temperature distribution across different points, as shown in Fig. 2(c).

The temperature response of the sensor was evaluated by

placing four different liquid materials on the plasmonic surface: distilled water, 21% wt. ethanol-water solution, glycerol and 70% wt. ethanol-water solution. Each liquid was introduced and removed through a microfluidic channel, which maintains a closed environment and effectively minimizes evaporation. After each set of measurements, the microfluidic system and all the tubing parts were preconditioned and thoroughly flushed to eliminate contaminants, air bubbles, and residual particles that could alter any optical parameter. The sensor was also thoroughly cleaned using distilled water followed by isopropanol (IPA), and the next experiment was initiated only after confirming that the spectral response in air matched the response measured prior to the previous experiment. The four specific liquids were carefully selected to include a broad range of TOCs, including values both lower and higher than that of SU-8. This strategic choice enabled a systematic investigation of the device’s temperature-dependent optical response under varying TOC contrasts between the overlying liquid medium and the SU-8 waveguide layer. The TOC of the solutions are presented in TABLE I. Given the SU-8 TOC value of $-1.1 \times 10^{-4} K^{-1}$ [44], the distilled water and the 21% wt. ethanol-water solution leads to a negative TOC difference, predicting a blueshift in the resonance dip wavelength according to (9). Similarly, glycerol and 70% wt. ethanol-water solution have a positive TOC difference from SU-8, suggesting a redshift in the resonance peak. The TOC differences between SU-8 and each solution are also presented in TABLE I. This selection not only provides comprehensive TOC coverage but also allows experimental validation of the theoretically predicted directionality of the spectral shift.

The corresponding experimental results are presented in Fig. 3. The variation in the initial resonance peak position observed across the different liquids shown in Figure 3(a) and 3(d) is due

<figure><img src="image_7.png" /><figcaption>Fig. 2. (a) Schematic of the experimental setup. (b) Image of the DUT and TEC configuration. (c) Thermal images at two different temperatures demonstrating the thermal variation during the heating of the integrated sensor.</figcaption></figure>
<caption>TABLE I</caption>

Table of the liquids used for temperature sensing experiments along with the respective TOC values, TOC difference from SU-8 and the achieved sensitivity.

<table><thead><tr><th>Liquid</th><th>TOC (× 10<sup>-4</sup>)</th><th>TOC difference (× 10<sup>-4</sup>)</th><th>Sensitivity (nm/°C)</th></tr></thead><tbody><tr><td>Distilled water</td><td>-0.942 [40]</td><td>-0.158</td><td>-2.24</td></tr><tr><td>20% wt. ethanol-water solution</td><td>-0.65 [42]</td><td>-0.45</td><td>-9.79</td></tr><tr><td>Glycerol</td><td>-2.3 [43]</td><td>+1.2</td><td>+8.06</td></tr><tr><td>70% wt. ethanol-water solution</td><td>-3.358 [42]</td><td>+2.258</td><td>+23.86</td></tr></tbody></table>

to differences in the refractive index of the overlying medium. As explained in Equation 1, the resonance wavelength is determined by the effective refractive index of the surface plasmon polariton modes. Any changes in the refractive index of the liquid directly affect the effective index of the top mode. In contrast, the bottom mode remains unaffected, as the refractive index of the SU-8 layer remain constant across the different measurements. This difference leads to the observed shifts in the initial resonance position across the various liquids. Fig. 3(a) presents the recorded spectra for distilled water across a temperature range of 24.951°C to 27.593°C, with a minimum step size of approximately 0.2°C. As the temperature increases, a blueshift in the resonance peak is observed, consistent with the theoretical predictions. By increasing the temperature beyond 27°C, additional losses are introduced due to fiber

misalignments. However, this does not affect the results, as our measurements rely on the detection of the resonance wavelength shift. Fig. 3(b) depicts the linear fit of the resonance peak shift, revealing an experimental sensitivity of -2.24 nm/°C. Similar measurements conducted for the 21% wt. ethanol-water solution within a temperature range from 26.267°C to 26.600°C, with a minimum step size of 0.06°C, demonstrate a more intense blueshift in the recorded spectra. The linear fit of the resonance peak shift in Fig. 3(c) yields a temperature sensitivity of -9.79 nm/°C, aligning closely with the theoretical expectations from the two TOCs. For the 70% wt. ethanol solution the chip was heated within the range of 26.090°C to 26.812°C. The results in Fig. 3(d) show an intense redshift of the wavelength resonance, due to the high TOC difference between the solution under test and the SU-8 in line with the theoretical predictions. The linear fit of the resonance peak shift in Fig. 3(e) demonstrated a record-high sensitivity of +23.86 nm/°C. Finally, glycerol was tested within a temperature range from 29.795°C to 30.197 °C, with a minimum step of 0.1°C, and a redshift of the resonance dip was observed in alignment with the theory. Fig. 3(f) illustrates the linear fit of the resonance peak shift revealing an experimental sensitivity of +8.06 nm/°C. The sensitivity results for each liquid, along with the respective TOC value and TOC difference from SU-8 are summarized in TABLE I.

The data presented in Fig. 3(b), (c), (e), and (f) further confirm that the sign of the wavelength shift in (9) is determined solely by the slope of the resonant wavelength-temperature curve. This shift can be either positive or negative, regardless of the sign of ΔT. This occurs because, when the data are plotted, the resonant wavelength at a given temperature remains the same whether ΔT is positive or negative. Another crucial parameter that should be highlighted is that the selection of the

<figure><img src="image_8.png" /><figcaption>Fig. 3. (a), (b) Spectral response of the sensor vs. temperature, when filled with distilled water and linear fit of the wavelength dip shift with the temperature change, (c) Linear fit of the wavelength dip shift with the temperature change, when filled with 21% wt. ethanol-water solution (d), (e) Spectral response of the sensor vs. temperature, when filled with 70% wt. ethanol-water solution and linear fit of the wavelength dip shift with the temperature change, (f) Linear fit of the wavelength dip shift with the temperature change, when filled with glycerol.</figcaption></figure>
material on top of the sensor greatly affects the sensitivity of the sensor. Furthermore, the physical and thermal properties of the material on top can also influence the response of the proposed sensor, enabling it to operate across diverse temperatures and varying dynamic ranges. In this work, a narrow range is used to highlight suitability for applications requiring sub-degree resolution, such as biochemical sensing. However, by selecting a different liquid loading, such as distilled water, the sensor can readily function over wider temperature ranges, maintaining a consistent response under extended ΔT conditions. This versatility allows engineers to tailor the sensor to meet the requirements of distinct applications.

The sensor's capability to accurately detect real temperature variations in the ambient environment was validated through multiple wavelength sweeps conducted with distilled water on top and over a time window of approximately 30 minutes, with each sweep lasting approximately 30 seconds. For each of the 19 in total wavelength sweeps, the resonance dip position was measured and converted into the corresponding temperature value using the sensitivity curve of distilled water. Simultaneously, an IR camera monitored the temperature on the chip surface. The results of this analysis, along with the temperature measurements recorded by the IR camera, are presented in Fig. 4. The data clearly demonstrate that the sensor successfully detects real temperature variations in the surrounding environment. The temperature trend captured by the sensor aligns closely with that recorded by the camera. The average difference between the sensor and camera readings is 0.796, with a standard deviation of 0.198. This near-constant discrepancy arises from the differences in calibration between the two devices.

The limit of detection (LoD) of the sensor was determined according to LoD = 3σ/S, where σ denotes standard deviation of the resonance drift and S represents the temperature sensitivity. Based on the experimental results obtained for a duration of 30min at room temperature, the standard deviation of the resonance drift was calculated to be σ = 0.26196 nm, resulting in a LoD equal to 0.03°C, for a temperature sensitivity S=23.86 nm/°C.

The data acquired through the experimental characterization of the device as a temperature sensor can be deployed to produce a TOC map, as shown in Fig. 5, that can be utilized for accurately measuring the TOC of an unknown liquid material. The map illustrates the relationship between the sensitivity vs. the TOC of each solution deposited on top of the plasmonic stripe. The colour of each scatter point indicates the direction of the wavelength shift (redshift or blueshift), which is clearly associated with the difference between the TOC values of SU-8 and the respective material, confirming the theoretically predicted behaviour for each liquid. The data follows a linear trend as y = ax + b, that serves as the calibration curve of the sensor. This relationship allows for the accurate determination of the TOC in a test liquid.

To determine the unknown TOC value of the test liquid, a few microliters are placed on top of the sensor, and wavelength sweeps are performed as the temperature changes. For each sweep, the resonance wavelength is recorded alongside the corresponding temperature. The data are then plotted on a graph, with the x-axis representing the temperature and the y-

axis representing the resonance wavelength. A linear fit of the data reveals the temperature sensitivity of the liquid under investigation. The calculated sensitivity is converted to the corresponding TOC value through the calibration curve of the sensor, presented in Fig. 5.

In Fig. 5, the data of three (distilled water, 21% wt. and 70% wt. ethanol-water solution) liquids were employed to calibrate the sensor, with the fourth liquid (glycerol) serving as the material with the unknown TOC. The error bars represent the standard deviation of repeated measurements for each liquid tested: 0.35293 for distilled water, 1.08244 for the 21% wt. ethanol-water solution, 1.75582 for the 70% wt. ethanol-water solution, and 1.7276 for glycerol. For water exhibiting the lowest temperature sensitivity the minimum wavelength shift between two measurements is 0.2 nm that is 2x higher than the 100 pm set resolution of the TLS. Using this calibration curve, the sensitivity of +8.06 nm/°C measured for the glycerol case is translated to a TOC value of -1.99 × 10⁻⁴ K⁻¹. This is in relatively good agreement with the real value of -2.3 × 10⁻⁴ K⁻¹ reported for glycerol in the literature [43], having an error of 13.1%. This deviation may be attributed to the limited number of calibration points, that affects TOC

<figure><img src="image_9.png" /></figure>

<figure><img src="image_10.png" /><figcaption>Fig. 4. (a) Recorded spectra of the wavelength sweeps performed during a 30-minute-long test period. (b) Temperature values recorded by the sensor and the IR camera targeting the plasmonic surface.</figcaption></figure>
<figure><img src="image_11.png" /><figcaption>Fig. 5. Sensitivity values correlated with the respective TOCs, along with the calibration curve of the sensor (linear fit) using three points for the calibration.</figcaption></figure>

measurement accuracy, and to non-uniform heating of the device during the experiment. The accuracy in the TOC calculation can be improved by increasing the number of the calibration points with additional liquids and performing the experiments in an environmental chamber under stable and repeatable climatic conditions.

Since the material on top of the sensor can be easily replaced by using a microfluidic channel, this process can be conducted for any liquid material with an unknown TOC. Consequently, the small amount required for the measurements along with the reconfigurability of the sensor provides a significant advantage over other integrated thermo-optic sensors introduced so far.

## IV. CONCLUSION

In summary, we present the experimental demonstration of an integrated plasmo-photonic bimodal interferometric sensing platform that can be used for temperature measurements and TOC identification. By leveraging the extreme light field concentration on the plasmonic metal stripe, the platform can detect minute changes in the refractive index of the liquid dielectric loading on top of the plasmonic sensing area with very high accuracy through interferometry. Experimental validation with four different liquids revealed a record-high temperature sensitivity of +23.86 nm/°C for a 70% wt. ethanol-water solution, surpassing the previously reported maximum sensitivity of 1.753 nm/°C for PICs by over tenfold. Additionally, the platform exhibited a maximum TOC measurement error of 13.1%, with potential for further improvement through extended calibration. Compared to other PICs designed for TOC measurements, this sensor offers superior flexibility across a wide range of liquids as it requires no sample or device preparation, enabling seamless switching between microfluidic channels.

## REFERENCES

[1] H. Zhu et al., "Exploring the frontiers of cell temperature measurement and thermogenesis," *Adv. Sci.*, vol. 12, no. 2402135, 2025.

[2] G. Petrini et al., "Nanodiamond-quantum sensors reveal temperature variation associated with hippocampal neurons firing," *Adv. Sci.*, vol. 9, no. 28, p. 2202014, 2022.

[3] R. K. Gangwar, A. K. Pathak, and S. Kumar, "Recent progress in

photonic crystal devices and their applications: A review," *Photonics*, vol. 10, p. 1199, 2023.

[4] Z. Ding and Y. Shi, "Demonstration of an ultra-sensitive temperature sensor using an asymmetric Mach-Zehnder interferometer," *IEEE Photonics J.*, vol. 13, no. 4, p. 1, 2021.

[5] G. Syriopoulos et al., "Photonic integrated circuit based temperature sensor for out-of-autoclave composite parts production monitoring," *Sensors*, vol. 23, p. 7765, 2023.

[6] S. Lin et al., "High-temperature measurement based on highly-sensitive miniature cascaded FPIs and the harmonic Vernier effect," *Measurement*, vol. 221, p. 113456, 2023.

[7] Y. Zhang et al., "Measurement of liquid thermo-optical coefficient based on all-fiber hybrid FPI-SPR sensor," *Sens. Actuators A Phys.*, vol. 331, p. 112954, 2021.

[8] Y. Chen, L. Fang, D. Yi, X. Li, and X. Hong, "Thermo-optic property measurement using surface plasmon resonance-based fiber optic sensor," *IEEE Sens. J.*, vol. 20, no. 19, pp. 11357-11363, 2020.

[9] C. Zhao et al., "Volatile organic compound sensor based on PDMS coated Fabry-Perot interferometer with Vernier effect," *IEEE Sens. J.*, vol. 19, no. 12, pp. 4443-4450, 2019.

[10] A. D. Gomes et al., "Optical harmonic Vernier effect: A new tool for high performance interferometric fibre sensors," *Sensors*, vol. 19, p. 5431-5438, 2019.

[11] R. Liu, R. Lv, Z. Lin, J. Zhao, H. Zheng, L. Cai, and Y. Zhao, "All-fiber high-sensitivity temperature sensor based on Mach-Zehnder interferometer with a little lateral-offset splicing for seawater," *Measurement*, vol. 247, p. 116779, 2025.

[12] X. Gao et al., "A dual-parameter fiber sensor based on few-mode fiber and fiber Bragg grating for strain and temperature sensing," *Opt. Commun.*, vol. 454, p. 124441, 2020.

[13] U. Sampath, D. Kim, H. Kim, and M. Song, "Polymer-coated FBG sensor for simultaneous temperature and strain monitoring in composite materials under cryogenic conditions," *Appl. Opt.*, vol. 57, no. 3, pp. 492-497, 2018.

[14] K. Wang et al., "Advances in optical fiber sensors based on multimode interference (MMI): A review," *IEEE Sensors Journal*, vol. 21, no. 1, pp. 132-142, Jan. 2021.

[15] S. Ma et al., "Optical fiber sensors for high-temperature monitoring: A review," *Sensors*, vol. 22, no. 15, p. 5722, 2022.

[16] Q. Sun et al., "Graphene-assisted microfiber for optical-power-based temperature sensor," *IEEE Photonics Technol. Lett.*, vol. 28, no. 4, pp. 383-386, 2016.

[17] M. Wang et al., "PDMS-assisted graphene microfiber ring resonator for temperature sensor," *Opt. Quantum Electron.*, vol. 50, no. 3, pp. 1-8, 2018.

[18] L. Yan, D. Liu, Z. Huang, K. Tian, C. Shen and P. Wang, "High sensitivity temperature sensor based on an acrylate coated no core fiber structure," *2022 20th International Conference on Optical Communications and Networks (ICOCN)*, Shenzhen, China, 2022, pp. 1-3.

[19] L. Zhao, Y. Zhang, J. Wang, and Y. Chen, "Highly sensitive temperature sensor based on an isopropanol-sealed optical microfiber coupler," *Appl. Phys. Lett.*, vol. 113, no. 11, p. 111901, 2018.

[20] C. Du, Q. Wang, Y. Zhao, and J. Li, "Highly sensitive temperature sensor based on an isopropanol-filled photonic crystal fiber long period grating," *Opt. Fiber Technol.*, vol. 34, pp. 12-15, 2017.

[21] M. Deng et al., "Highly sensitive temperature sensor based on an ultra-compact Mach-Zehnder interferometer with side-opened channels," *Opt. Lett.*, vol. 42, no. 18, pp. 3549-3552, 2017.

[22] C. Zervos, G. Syriopoulos, E. Kyriazi, M. Szaj, A. Poulimenos, J. Missinne, G. Poulopoulos, G. Van Steenberge, and H. Avramopoulos, "Integrated silicon Bragg-grating-based temperature sensor embedded in composite molds for out-of-autoclave composite parts process monitoring and optimisation," *Proc. SPIE*, vol. 12889, *Integrated Optics: Devices, Materials, and Technologies XXVIII*, 128890T, 2024.

[23] Z. Ding and Y. Shi, "Demonstration of an ultra-sensitive temperature sensor using an asymmetric Mach-Zehnder interferometer," *IEEE Photon. J.*, vol. 13, no. 4, Art. no. 6800505, 2021.

[24] L.-Y. Chen, Y.-J. Chen, D.-S. Wu, W.-H. Huang, and C.-T. Wang, "High-sensitivity silicon nitride optical temperature sensor based on cascaded Mach-Zehnder interferometers," *Opt. Mater.*, vol. 165, 117139, 2025.

[25] L. A. Tapia-Licona, J. S. S. Durán-Gómez, E. G. Trejo-Liévano, G. V. Vázquez, R. Ramírez-Alarcón, M. E. Soto-Alcaraz, and R. Castro-Beltrán, "Design and fabrication of Mach-Zehnder interferometers in
soda-lime glass for temperature sensing applications,” *Appl. Opt.*, vol. 62, pp. 1214–1220, 2023.

[26] X. Guan, X. Wang, and L. H. Frandsen, “Optical temperature sensor with enhanced sensitivity by employing hybrid waveguides in a silicon Mach-Zehnder interferometer,” *Opt. Express*, vol. 24, pp. 16349–16356, 2016.

[27] J.-M. Lee, “Ultrahigh temperature-sensitive silicon MZI with titania cladding,” *Front. Mater.*, vol. 2, p. 36, 2015.

[28] L.-Y. Chiang et al., “Highly sensitive silicon photonic temperature sensor based on liquid crystal filled slot waveguide directional coupler,” *Opt. Express*, vol. 28, pp. 29345–29356, 2020.

[29] Y. Zhang et al., “High sensitivity temperature sensor based on cascaded silicon photonic crystal nanobeam cavities,” *Opt. Express*, vol. 24, pp. 23037–23043, 2016.

[30] Z. Ding, D. Dai, and Y. Shi, “Ultra-sensitive silicon temperature sensor based on cascaded Mach–Zehnder interferometers,” *Opt. Lett.*, vol. 46, pp. 2787–2790, 2021.

[31] H. S. Choi, D. Neiroukh, H. K. Hunt, and A. M. Armani, “Thermo-optic coefficient of polyisobutylene ultrathin films measured with integrated photonic devices,” *Langmuir*, vol. 28, pp. 849–854, 2012.

[32] B. A. Rose, A. J. Maker, and A. M. Armani, “Characterization of thermo-optic coefficient and material loss of high refractive index silica sol-gel films in the visible and near-IR,” *Opt. Mater. Express*, vol. 2, pp. 671–681, 2012.

[33] S. Sokolov et al., “Measurement of the linear thermo-optical coefficient of Ga0.51In0.49P using photonic crystal nanocavities,” *Appl. Opt.*, vol. 56, pp. 3219–3222, 2017.

[34] A. Arbabi and L. L. Goddard, “Measurements of the refractive indices and thermo-optic coefficients of Si3N4 and SiOx using microring resonances,” *Opt. Lett.*, vol. 38, pp. 3878–3881, 2013.

[35] P. R. Prasad, S. K. Selvaraja, and M. Varma, “Real-time compensation of errors in refractive index shift measurements of microring sensors using thermo-optic coefficients,” *Opt. Express*, vol. 26, pp. 13461–13473, 2018.

[36] O. Bhalerao et al., “High-sensitivity polymer-based bimodal plasmonic refractive index sensors with polymer cladding,” *Opt. Express*, vol. 33, pp. 9813–9824, 2025.

[37] K. Fotiadis et al., “High-sensitivity bimodal plasmo-photonic refractive index sensor,” *ACS Photonics*, vol. 10, pp. 2580–2588, 2023.

[38] K. Fotiadis et al., “Single-arm interferometric plasmonic sensor integrated on a cladded polymeric photonic platform,” in *CLEO 2024 Tech. Dig. Ser.*, Optica Publishing Group, paper SF1A.7, 2024.

[39] E. Chatzianagnostou et al., “Scaling the sensitivity of integrated plasmo-photonic interferometric sensors,” *ACS Photonics*, vol. 6, no. 7, pp. 1664–1673, Jul. 2019.

[40] M. Daimon and A. Masumura, “Measurement of the refractive index of distilled water from the near infrared region to the ultraviolet region,” *Appl. Opt.*, vol. 46, pp. 3811–3820, 2007.

[41] C.-L. Lee, H.-Y. Ho, J.-H. Gu, T.-Y. Yeh, and C.-H. Tseng, “Dualhollow core fiber-based Fabry–Perot interferometer for measuring the thermo-optic coefficients of liquids,” *Optics Letters*, vol. 40, no. 4, pp. 459–462, 2015.

[42] S. Novais, M. S. Ferreira, and J. L. Pinto, “Determination of thermo-optic coefficient of ethanol-water mixtures with optical fiber tip sensor,” *Opt. Fiber Technol.*, vol. 45, pp. 276–279, 2018.

[43] Z. Cao et al., “All-glass extrinsic Fabry–Perot interferometer thermo-optic coefficient sensor based on a capillary bridged two fiber ends,” *Appl. Opt.*, vol. 54, pp. 2371–2375, 2015.

[44] P. Rabiei, W. H. Steier, C. Zhang, and L. R. Dalton, “Polymer micro-ring filters and modulators,” *J. Lightwave Technol.*, vol. 20, pp. 1968–1975, 2002.

[45] Q. Shao, Q. Ma, M. Li, and J.-J. He, “Thermo-tuning Fourier transform spectrometer based on SU-8 waveguide,” *Polymers*, vol. 17, no. 3, p. 261, 2025, doi: 10.3390/polym17030261.

has also contributed to two European research projects related to the development of integrated circuits and sensors. Her research interests include the design, development, and experimental evaluation of integrated plasmo-photonic circuits for sensing applications.

**Lamprini Damakoudi** received the B.Sc. degree in Physics from Aristotle University of Thessaloniki (AUTH), Thessaloniki, Greece, and the M.Sc. degree in Communication Networks and Systems Security from the Department of Informatics, AUTH. She is currently pursuing the Ph.D. degree in the Department of Physics at AUTH.

Since 2023, she has been a Ph.D. student and researcher with the Wireless and Photonic Systems and Networks (WinPhos) Research Group at AUTH. She has authored seven publications in peer-reviewed international journals and conferences and holds one Greek patent. She