# Micro-thermoreflectometry applied to in situ monitoring of changes in the optical properties of a MCrAlY coating during high-temperature oxidation

Joan Delpech, Damien Texier, Thomas Pottier, Thierry Sentenac

► To cite this version:

Joan Delpech, Damien Texier, Thomas Pottier, Thierry Sentenac. Micro-thermoreflectometry applied to in situ monitoring of changes in the optical properties of a MCrAlY coating during high-temperature oxidation. Thermosense: Thermal Infrared Applications XLVII, Apr 2025, Orlando, United States. pp.6, 10.1117/12.3053477. hal-05216916

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

Distributed under a Creative Commons Attribution 4.0 International License
Micro-thermoreflectometry applied to in situ monitoring of
changes in the optical properties of a MCrAlY coating during
high-temperature oxidation

Joan Delpechª, Damien Texierª, Thomas Pottierª, and Thierry Sentenacª

ªInstitut Clement Ader (ICA), Universite de Toulouse, CNRS, Mines Albi, UPS, INSA, ISAE-SUPAERO, Campus Jarlard, 81013 Albi CT Cedex 09, France

ABSTRACT

The paper deals with the characterization of the formation of high-temperature oxides formed on the surface and subsurface in MCrAlY alloys, and more generally nickel-based single-crystal superalloys, using an *in-situ* method of measuring thermo-optical properties. The suggested method, denoted micro-thermoreflectometry, involves full-field measurement of the bidirectional reflectivity at the microscale using high-resolution cameras operating in the visible and near-infrared (NIR) spectral range, with a spatial resolution of 0.625 µm. Prior to measurement, a reflectometric calibration of the thermo-reflectometry method was carried out to determine the model between the intensity delivered by each pixel and the reference value of the bidirectional reflectivity of a Lambertian surface given by a Spectralon® standard. This model was validated on Lambertian surfaces with attenuations of 80 and 50 % relative to Spectralon® by comparison with the bidirectional reflectivity measurement performed by Fourier's transform infrared spectrometer (FTIR). Both measurements are coherent and perfectly fitted for the three micro-thermoreflectometry measurement wavelengths. By measuring bidirectional reflectivity fields, the detection and the identification were performed on the various oxidation compounds that are formed either at the surface or beneath the semi-transparent Al₂O₃ -layer. A multispectral image was provided revealing differences between oxides formed at the surface and subsurface of the MCrAlY alloys.

**Keywords:** Active thermography, thermoreflectometry, radiative and optical properties, FTIR Spectroscopy, high-temperature oxidation, high-temperature coating.

# 1. INTRODUCTION

Nickel-based superalloys developed for aeronautical applications feature high mechanical strength and resistance to oxidation at high temperatures. Their ability to resist corrosive and oxidizing environments is ensured by a tailored chemical composition that promotes selective oxidation of specific metallic elements forming a dense, adherent, and slow-growing oxide layer, also known as thermally growth oxide (TGO).¹ Solid-state diffusion alters both the subsurface chemical composition and microstructure of the metallic alloy by depleting it from reactive elements.²,³ This material evolution affects the mechanical properties and integrity when exposed to an extremely harsh environment, particularly when mechanical stresses and thermal cycling are combined. Metallic overlay or aluminide diffusion coatings are generally applied as bonding layers for thermal barrier coatings (TBCs) to protect the hottest parts of the engine. These bond-coatings are intended to provide a greater reservoir of aluminium (Al) or chromium (Cr) necessary to form and stabilize the protective oxide scale⁴⁻⁶. MCrAlY coatings (where M stands for: Ni, NiCo or CoNi) are widely used as a bond coat within TBCs due to its ability to promote the growth of a protective layer of Al₂O₃ when exposed to oxidative atmosphere at high temperature.⁶

Compared to Ni-based superalloys, bond-coatings are proven to significantly improve the surface reactivity in both isothermal and thermal cycling conditions.² In addition, the growth of Al₂O₃ is possible at the bond-coating surface as long as the thermodynamical equilibrium between the Al content and the oxygen partial pressure (pO₂) remains in favor of the Al₂O₃ formation.⁷ A decrease in Al content and aluminum activity due to the depletion involved in the oxidation process induces an increase in oxygen partial pressure according to the

<footnote>Further author information: (Send correspondence to Joan Delpech)</footnote>

<footnote>Joan Delpech: E-mail: joan.delpech@mines-albi.fr</footnote>
reaction equilibrium. When the pO2 reaches a certain threshold, the Al₂O₃ is no more the most stable oxide to form and therefore the coating promotes the growth of a less stable oxide beneath the previously formed Al₂O₃ layer, e.g. chromia (Cr₂O₃) in the case of MCrAlY coatings.⁷,⁸ This mechanism, particularly encountered for thin coatings, is known as chemical failure and it can be classified either as intrinsic chemical failure (InCF) or mechanically induced chemical failure (MICF).⁹ Such failure mechanisms can also be associated with the formation of fast growing oxides and a significant evolution of the mass gain, known as breakaway.⁹

In the first case, the failure is generalized to the whole surface due to the global decrease in Al content within the coating, which happens when the depleted volume is significant in comparison of the total volume of the alloy, this phenomena is also defined as "reservoir effect".⁷ In the second case, the repeated cracking of the protective scale caused by mechanical and/or thermal damages locally increase the consumption rate of Al, since it contributes to the resorption of cracks, and therefore promote local chemical failure.¹⁰ The two mechanisms contribute to the weakening of the coating and thus promote unpredictable damage within critical parts.

Various studies have extensively investigated these mechanisms through global or local observations perform-
ing thermo-gravimetric analysis (TGA) or scanning electron microscopy (SEM) analysis, respectively. However,
none of them are able to perform *in-situ* or non-destructive monitoring of the TGO degradation through the
oxidation process. In fact, the transient oxidation phenomenon are usually observed with the TGA since it
consists in a continuous measurement of the mass variation during the duration of the oxidation. However, the
spatial distribution of the oxidation or the very local mechanisms, such as InCF, could not be detected with such
macroscopic measurements⁸. Conversely, SEM analysis offers a valuable insight at the local oxidation process,
but it cannot be compatible with *in-situ* observations since it requires the interruption of the oxidation. Indeed,
as highlighted above these oxidation mechanisms could be located below the Al₂O₃ layer, which is opaque to
the electron. This property do not allows *in-situ* measurement from the surface and requires to observe the
cross-section of the specimen after oxidation.

As mentioned in the above, the Al₂O₃ oxide presents semi-transparency properties in the VIS-NIR spectrum (from 0.7 up to 2.5 µm), allowing to observe subsurface oxidation regime changes from surface observations with optical microscopy (OM). This characteristic allows the perspective of *in-situ* monitoring of the chemical failure phenomenon. In fact, the variation in chemical nature, surface's roughness and oxide film growth influence the thermo-optical properties of the surface such as its reflectivity or emissivity¹¹. Accordingly, it becomes possible to perform *in-situ* monitoring of the oxidation mechanism by measuring the local variation in radiative properties, as long as a correlation between both quantities have been first calibrated¹². Accordingly to this statement, the article suggests an active thermography method able to perform full-field emissivity measurement at the microscale in order to observe these variations and therefore correlate them to oxidation mechanisms.

The *in-situ* determination of the emissivity is a complex endeavor particularly well-known in the context of the true temperature determination of multi-material or time-dependent surfaces.¹³ Various thermography methods have been developed in order to overcome this issues, these methods can be classified either as passive or active techniques. The first category requires assumptions on the evolution of emissivity, such as its spectral invariance. However, their application is constrained to a limited range of materials.¹⁴ In the second category, the emissivity measurement is conducted by performing the additional measurement of another quantity involved in the radiometric model. The approach detailed in this work is based on the thermoreflectometry method,¹⁵,¹⁶ which considers both temperature and reflectivity measurement at several wavelength to compute the emissivity.

The thermoreflectometry have been initially developed to perform true temperature measurement on multi-material surface at the macroscopic scale, consisting in centimetric field of view with a sub-millimetre spatial resolution.¹⁷,¹⁸

Based on this preliminary research, the method was adapted for microscale measurements applied to *in-situ*
monitoring of the thermo-optical properties of an oxidizing surface.

The present work details the reflectometric calibration method and presents the measurement performances at room temperature on pre-oxidized samples compared to reference measurements performed using FTIR spectrometer.
## 2. MATERIAL

MCrAlY coatings used in the present study were similar to those described in refs (8, 19). The as-received (AR) state consisted in 500 µm-thick free-standing NiCoCrAlY plates deposited by air plasma spray (APS), followed by a standard heat treatment consisting of 8 h at 1080 °C followed by 20h at 870 °C. Then, 1" diameter disk was collected from the initial AR coating and was then thinned using SiC papers down to a thickness of 150 µm. The sample was then oxidized during 50 h at 1150 °C. According to the cross-section observations, the microstructure of the oxidized coating consisted in a fine γ/β microstructure with a surface fraction of 46 % and 54 %, respectively. An oxide layer of α-Al₂O₃ of 4 µm thick is measured in average at the surface along with a β-free area within the few microns under the interface oxide/metal (fig.1). Intrusive oxidation, i.e., oxidation in the volumen, was also observed within the coating between interplats regions (volume comprised between two projected particles). This single layer oxidation morphology is observed within the majority of the sample surface and is considered as the standard protective oxidation regime usually observed in nominal conditions.

<figure><img src="image_2.png" /><figcaption>Figure 1: *MCrAlY free-standing coating cross-section after 50 h oxidation at 1150 °C (OM)*</figcaption></figure>

However, non-protective oxidation products promoted by the introduction of defects, e.g. intersplats, cracks and voids, are locally observed within some regions of the sample. The characterization of the different chemical elements constitutive of the external oxide scale was carried out by an energy-dispersion spectroscopy (EDS) analysis (see section A). The comparison of optical and electronic microscopy revealed that the areas identified as white and blue within the visible spectrum corresponded to α-Al₂O₃ and spinel oxides (NiCo)O, respectively. As expected, the Al₂O₃ is confirmed as the main oxide formed at the surface. The spinels oxide are also confirmed to be present at the surface but they also appeared to be present beneath the Al₂O₃ scale, since some blueish areas visible in OM are not observed with the SEM modality. Indeed, the SEM probes only the extreme surface of the samples and therefore could not revealed the chemical species present beneath the 4 µm-thick Al₂O₃ external layer. Similarly, dark gray areas that were clearly visible in OM could not be identified on the EDS maps. According to preliminary work (Refs. 8, 19), the dark-gray areas within MCrAlY oxidized coating are associated to InCF confirming the presence of Cr₂O₃ beneath the layer of Al₂O₃.

The aforementioned observations point that the ongoing oxidation phenomenon prompt gradients in chemical composition, microstructure and physical properties of the sample surface. These oxidation products are related to subsequent changes in the optical properties of the surface of the specimen. Consequently, these transient microstructural and chemical mechanisms are intended to be uninterruptedly characterized through *in-situ* monitoring of their optical signature, especially given the constrained capacity of the electronic microscopy to observe these transitions.

## 3. METHOD

A method for *in-situ*, full-field detection and identification of the optical properties within a heterogeneous and multimaterial oxide layer is suggested. The physical concepts underlying the measurement as well as the calibration procedure are described in the following.
<figure><img src="image_3.png" /><figcaption>Figure 2: OM observations of the sample at different scales revealing various oxidation products at the sample surface. The oxidation products have been classified in four distinct categories according their colors : black, blue, dark-gray, white/ligh-gray. The two first categories could be associated to spinel oxides, the dark-gray area are usually associated to InCF, and therefore to Cr₂O₃ formation. Finally, the white areas are associated with standard Al₂O₃ .</figcaption></figure>

3.1 Physical background

The optical properties of an opaque surface at thermodynamic equilibrium is characterized in accordance with two physical quantities related through the Kirchhoff’s law$^{20,21}$ defined as follows:

$$
\epsilon^{\vec{u}_i}(\mathbf{x}_i, \lambda) = 1 - \rho^{\vec{u}_i, \cap}(\mathbf{x}_i, \lambda) \quad (1)
$$

with ε⃗uᵢ and ρ⃗uᵢ,∩ the directional emissivity and the directional-hemispheric reflectivity in the direction ⃗uᵢ,
at the surface point **x**ᵢ and at the wavelength λ. The directional-hemispheric reflectivity is usually directly
measured through specific instruments, e.g. integrating sphere capable of measuring optical properties over
the entire surrounding hemisphere. Nonetheless, these instruments are not appropriate for full-field and in-situ
measurements since their performance is limited to punctual probing.

As suggested by the thermoreflectometry method, an alternative is to solve the equation (1) through an indi-
rect determination of the directional-hemispheric reflectivity extracted from the measurement of the bidirectional
reflectivity distribution function (BRDF), according to equation (2), with cameras. The BRDF is then defined
as the ratio of the radiance dL⃗uᵣ(**x**ᵢ, λ) reflected from the surface dSᵢ toward the direction of detection (denoted
⃗uᵣ) to the irradiance dE⃗uᵢ(**x**ᵢ, λ) of the surface dSᵢ resulting of the incoming radiance within a solid angle along
the direction ⃗uᵢ.

$$
\rho^{\vec{u}_i, \vec{u}_r}(\mathbf{x}_i, \lambda) = \frac{dL_r^{\vec{u}_r}(\mathbf{x}_i, \lambda)}{dE^{\vec{u}_i}(\mathbf{x}_i, \lambda)} = \frac{dL_r^{\vec{u}_r}(\mathbf{x}_i, \lambda)}{L^{\vec{u}_i}(\mathbf{x}_i) \cos(\theta_i) d\Omega_i} \quad [sr^{-1}] \quad (2)
$$

The integration of the BRDF over all the directions of the hemisphere results in the directional-hemispheric
reflectivity (1), as recalled in equation (3).

$$
\rho^{\vec{u}_i, \cap}(\mathbf{x}_i, \lambda) = \int_{\Omega_r = 2\pi} \rho^{\vec{u}_i, \vec{u}_r}(\mathbf{x}_i, \lambda) \cos(\theta_r) d\Omega_r \quad (3)
$$

Finally, thermoreflectometry method based on a camera and multi-wavelength lighting sources (LED) mea-
sures for each pixel the bidirectional reflectivity (ρ⃗uᵢ,⃗uᵣ) which is an evaluation of the BRDF at a specific config-
uration of ⃗uᵢ and ⃗uᵣ. This measurement is used to calculate hemispherical directional reflectivity according to
the equation (3) whose integral is evaluated at π for a Lambertian surface.
<figure><img src="image_4.png" /><figcaption>Figure 3: Configuration of the bidirectional reflectivity measurements on the multilayered sample representative of the various surface heterogeneity observed on the oxidized specimen.</figcaption></figure>

## 3.2 Calibration

The reflectometric calibration process consists in defining the relationship between the reflected intensity $I_{r0}^{\vec{u}_i, \vec{u}_v}$ at each coordinate pixel $(u, v)$ from the camera and a reference physical quantity $\rho_0^{\vec{u}_i, \vec{u}_v}$ of a Lambertian reference surface, according to equation (4).

$$ K_r^{\vec{u}_i, \vec{u}_v}(u, v, \lambda) = \frac{\rho_0^{\vec{u}_i, \vec{u}_v}(\mathbf{x}_i, \lambda)}{I_{r0}^{\vec{u}_i, \vec{u}_v}(u, v, \lambda)} \quad (4) $$

where $K_r^{\vec{u}_i, \vec{u}_v}$ is the spectral calibration coefficient estimated at the pixel position $(u, v)$ and $I_{r0}^{\vec{u}_i, \vec{u}_v}$ is the spectral intensity in digital level evaluated at the pixel $(u, v)$ on a reference surface. The subscript 0 denotes reference quantities. The standard surface is supplied by Spectralon®, white, diffuse calibration target of known directional-hemispheric reflectivity (nominal Reflectance (99%)). It exhibits near perfect Lambertian surfaces independent of viewing angle.

The reflected intensities, $I_{r0}^{\vec{u}_i, \vec{u}_v}$, are acquired with a low-noise back-illuminated sCMOS camera (Kinetix from Teledyne Photometrics) at three different wavelengths (450 nm, 600 nm, 750 nm, respectively) with an illumination incident angle of $\theta_{\vec{u}_i} = 45^{\circ}$ (see fig. 3). The camera is oriented normal to the surface ($\alpha_{\vec{u}_v} = 45^{\circ}$).

Image acquisition was performed at constant LED intensity but the integration time (ti) was adjusted in order to maximise the image dynamic range for each specimens. One acquisition corresponds to a time average of 10 images (normalized respectively to their ti) in order to minimize the electronic background noise. In addition, a pixel wise two points non-uniformity correction (NUC) is performed in order to correct the gain and the offset within the images. The full-frame capacity of the imaging system visualizes a field of view (FOV) of 2000 µm × 2000 µm with a spatial resolution of 0.625 µm/pixel. Nevertheless, in order to eliminate the optical defect, i.e. geometrical optical aberrations and multi-reflection, perceptible near the edges of the image, the measures are performed within a distortion-free region of interest (ROI) of 1000 µm × 1000 µm at the centre of the FOV.

Reference measurements of $\rho_0^{\vec{u}_i, \vec{u}_v}$ of white Spectralon® are carried out with a FTIR spectrometer (Brucker Vertex 70) equipped with a goniometer module capable of performing BRDF measurements within the incident plane with a minimum incidence angle in the direction $\vec{u}_i$ of 13° and a view angle in the direction $\vec{u}_r$ from 13° to 90°. BRDF measurements were performed in the same configuration as the reflectometer ($\theta_{\vec{u}_i} = 45^{\circ}$).
<figure><img src="image_5.png" /><figcaption>Figure 4: BRDF of the 99 Spectralon® measured for an illumination incident angle of $\theta_{\vec{u}_i} = 45^\circ$ at 450 nm, 600 nm and 750 nm (the minimum detection angles being limited to $\theta_{\vec{u}_r} = 13^\circ$, the BRDF between $0^\circ < \theta_{\vec{u}_r} < 13^\circ$ is extrapolated from the original dataset).</figcaption></figure>

The results presented on figure 4 depict the BRDF of the 99 Spectralon® at various wavelengths. The standard Spectralon® sample demonstrated a quasi-lambertian behavior in agreement with the assumption. The invariability of the BRDF with respect to the wavelength across the investigated spectrum in fig. 4 is also highlighted. The bidirectional reflectivity of the standard 99 Spectralon® target in the configuration of the microreflectometer ($\theta_{\vec{u}_i} = 45^\circ$ and $\theta_{\vec{u}_r} = 0^\circ$) measured at $2.8 \times 10^{-1} \text{ sr}^{-1}$ in average for the three wavelengths, is found to be consistent with the results presented in Ref. 22. Accordingly, the $K_r^{\vec{u}_i, \vec{u}_v}$ calibration coefficient is assessed from the measurement of $I_{r0}^{\vec{u}_i, \vec{u}_v}$ on a 99 Spectralon® target, and equation (4).

<figure><img src="image_6.png" /><figcaption>Figure 5: $K_r^{\vec{u}_i, \vec{u}_r}$ calibration coefficient map measured on 99 Spectralon® at 750 nm (a) and the distribution of $K_r^{\vec{u}_i, \vec{u}_r}$ within the map at each wavelengths (b)</figcaption></figure>

The calibration coefficient maps (fig. 5a) show the spatial non-uniformity of the standard 99 Spectralon®. Indeed such specimen are meant to be observed at macroscopic scale, they obviously appear rough at microscopic scale. Nevertheless, the coefficient values have demonstrated both skewness free and low standard deviations
(fig. 5b), allowing to consider the $K_r$ as quasi-constant with low heterogeneity. The significant shift between the peaks of the 450/600 nm and the 750 nm maps is attributed to the important variation in ti between the acquisition of each images. In fact, for iso-intensity the 750 nm LED optical power is lower than those of the 450/600 nm LEDs. Consequently the offset in optical power is compensated with the exposure time, and therefore introduced a variation within the normalized histograms.

## 3.3 Validation

Once calibrated, validation consists in calculating bidirectional reflectivity using the calibration coefficient $K_r \vec{u}_i \cdot \vec{u}_r$ determined during calibration, for the standard target 99% of Spectralon® and two targets with attenuation ratio of 80% and 50%.

For the standard target 99% of Spectralon®, figure 6 illustrates the image of its spatial distribution and its histogram for three wavelengths. The figure shows that the mean value of bidirectional reflectivity is consistent with the value obtained by Georgiev et al. in ref 22 ($\rho^{\vec{u}_i, \vec{u}_r} = 2.8 \times 10^{-1} \text{ sr}^{-1}$) and showed in figure 4. In addition, the standard deviation of bidirectional reflectivity is low (less than 0.5% of the mean value), indicating image uniformity.

<figure><img src="image_7.png" /><figcaption>Figure 6: $\rho^{\vec{u}_i, \vec{u}_r}$ map measured on 99 Spectralon® at 750 nm (a) and the distribution of $\rho^{\vec{u}_i, \vec{u}_r}$ within the map at each wavelengths (b)</figcaption></figure>

For the standard figure 7a displays the bidirectional reflectivity histogram at wavelength of 750 nm. The histograms clearly highlight the attenuation coefficient of 20% between the target at 99% and 80% of reflectivity and similarly an attenuation of 50% between the 99% and 50% targets. The mean values of each histogram are checked and consistent with the bidirectional reflectivities values measured on the spectrometer (fig. 7b). In addition, the value of the standard deviation of bidirectional reflectivity for each target remains low, proof of spatially uniform calibration.

# 4. RESULTS

Bidirectional reflectivity measurements are performed for each wavelength on the MCrAlY ROI previously studied through OM and SEM (fig. 2). The figure 8 displays both the multispectral composite image (a) and its related chromatic (pseudo-RGB) histograms (b) built from the trichromatic analysis using the different wavelengths as RGB channels with the 450 nm, 600 nm and 750 nm for the blue, green and red channels, respectively. The advantage of this specific representation is that it easily reveals the previously identified oxidized areas. It also proves the spectral sensitivity of the actual surface, since the different chemical species exhibits various behaviors in terms of bidirectional reflectivity from one wavelength to another. For instance, from the bidirectional reflectivity field and the peaks identification on the histograms, it appears that the spinel oxides are more reflective at 450 nm and at 750 nm than at 600 nm, while the ROIs presenting InCF did not exhibit particular
<figure><img src="image_8.png" /><figcaption>Figure 7: Distribution of the $\rho\vec{u}_i, \vec{u}_r$ at 750 nm for each Spectralon® target 99%, 80%, 50% measured with the reflectometry method (a) and the BRDF of each target measured with the goniometer module of the FTIR spectrometer (b).</figcaption></figure>

spectral variations. Nevertheless, these areas are identifiable since they presented a lower reflective intensity compared to the unaltered $Al_2O_3$ areas.

It is worth noticing, that the low overall bidirectional reflectivity measured at the surface, is attributed to the off-specular orientation of the reflectometer, does not prevent from identifying the optical signature of the oxide species. The actual sensing configuration, with an incidence illumination angle of $\theta_{\vec{u}_i} = 45^\circ$ and a viewing angle of $\alpha_{\vec{u}_v} = 45^\circ$, does not intercept the maximum intensity peak of reflection, resulting in a lower reflectivity. Nevertheless, the calibration procedure delineated in section 3.2 has been demonstrated to be consistent with the measurement of bidirectional reflectivity characteristic of oxides formed on and below the surface, thereby ensuring the reliability of the ensuing results.

<figure><img src="image_9.png" /><figcaption>Figure 8: Multispectral reflectivity cartography of the oxidized $MCrAlY$ specimen (a) and the distribution of the $\rho\vec{u}_i, \vec{u}_r$ at 450 nm, 600 nm, 750 nm within the image (b)</figcaption></figure>

In addition, the bidirectional reflectivity values of the different oxides, identified from histogram (fig. 8b) segmentation, have been represented in a ternary diagram (fig. 9). This representation relates both the bidirectional reflectivity spectral variation in the trichromatic space and reflective intensity (mean of the bidirectional
reflectivity on the three wavelengths). Two comments can be made from the observed spectral variations. i) the bidirectional reflectivity within each identified clusters varies around their barycenter promoting overleaping between the different species and ii) the barycenter of each cluster are distinctly identified from one to another. This representation allows to distinctly identify the bidirectional reflectivity shift of the different oxides with respect to the wavelength.

Moreover, the distinct reflective intensity behavior of the species identified in the bidirectional reflectivity map (fig. 8a) have been represented as color gradient in the figure 9. The combination of these two characteristics allows the identification of a unique spectral signature for each oxides. For instance, the Al₂O₃ cluster centered in the diagram is proven spectrally constant with a high reflectivity. Comparatively, InCF species located on one side of the diagram have been demonstrated to be less sensitive at 600 nm compared to the two other wavelengths and presents an overall reflectivity intensity lower than the Al₂O₃.

<figure><img src="image_10.png" /><figcaption>Figure 9: This ternary diagram represents both spectral variations and bidirectional reflectivity intensity of the different oxides species. The location of the clusters within the diagram represents the spectral shift of the oxides within the pseudo-colorimetric space. The color gradient is relative to the mean bidirectional reflectivity (average on the three wavelength) and thus indicates the reflective intensity of the species.</figcaption></figure>

## 5. CONCLUSIONS

This study described a new method for the in-situ full-field measurement of the reflectivity at the microscale in the context of the non-contact monitoring of the high temperature oxidation mechanisms. The calibration procedure at room temperature on reference targets has shown a strong correlation with the reference measurement carried out on a FTIR spectrometer. Tests performed on pre-oxidized MCrAlY specimens emphasized the ability of the method to accurately characterize the surface species from their reflective properties even beneath a consolidated layer of Al₂O₃. The spectral reflective signature of the chemical failure was identified allowing the possibility of performing in-situ detection of the oxidation mechanism at the microscale that conventional mass gain measurements cannot quantify.

Future research will focus on on-line monitoring of the growth of the various oxides during hot oxidation mechanism. the micro-thermoreflectometry will track in a full-field manner both bidirectional reflectivity to detect and identify the different oxides and temperature variations to identify oxidation state and status. A radiometric calibration will be added to measure radiance temperatures. The measured bidirectional reflectivity and radiance temperature will be the inputs to a multi-spectral system whose resolution will estimate the true temperature.
## 6. LICENSE

This research was funded, in whole or in part, by The European Research Council, project HT-S<sub>4</sub>DefOx - Grant number 948007. A [CC-BY public copyright license] has been applied by the authors to the present document and will be applied to all subsequent versions up to the Author Accepted Manuscript arising from this submission, in accordance with the grant's open access conditions.

## APPENDIX A. SEM-EDS ANALYSIS

<figure><img src="image_11.png" /><figcaption>Figure 10: SEM-EDS analysis performed at the surface confirming the presence of NiCoO spinel oxides within the Al<sub>2</sub>O<sub>3</sub> oxide scale. Some Cr<sub>2</sub>O<sub>3</sub> oxides have also been revealed at the sample surface, however, the ROI dark-gray visible in OM has not been revealed in the SEM cartography.</figcaption></figure>

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