3445

Sensors and Materials, Vol. 36, No. 8 (2024) 3445–3452
MYU Tokyo
S & M 3743

Noncontact Temperature Measurement of Metal Surfaces
Using Reflected Laser BeamTaichi Murakami,1 Masaki Shimofuri,2 Toshiyuki Tsuchiya,2 and Shugo Miyake1*
1Setsunan University, 17-8 Ikedanakamachi, Neyagawa-shi, Osaka 572-8508, Japan
2Kyoto University, Kyotodaigakukatsura, Nishikyo-ku, Kyoto 615-8246, Japan(Received May 31, 2024; accepted June 24, 2024)

Keywords: thermoreflectance, microscale spatial resolution, metal thin film, modulation-free heating

A temperature measurement system with a reflected laser beam that does not requiretemperature modulation was developed for the thermal design of electronic devices. The system
combines a balanced photodetector and lock-in amplifier to make reflectance change
measurements possible with an extremely high signal-to-noise ratio. First, to evaluate theaccuracy of the reflectance change measurement, the reflectance change of a Ni thin film
temperature-controlled by a heater and thermocouples was measured as a function oftemperature change. To evaluate the accuracy of the temperature change measurement, thereflectance change was measured by heating a Ni thin film that imitated the wiring pattern of anelectronic circuit. The experimental results showed that the standard deviation of the ratio ofreflectance change from the reference reflectance was <1.00 × 10−5 at a constant temperature.
Moreover, the error margin of the calculated temperature change was ±1.0% for a change of 22°C or more from the reference temperature, and the performance was sufficient for theestimation of local temperature.

1.

Introduction

The electronics industry, which is central to a supersmart society, has shown remarkabledevelopment in recent years. Electronic devices are becoming more sophisticated andmultifunctional. It is extremely important to ensure the reliability of electronic devices, such as
smartphones, which have become indispensable to people in their daily lives. However, thethermal management of the heat generated during operation is becoming increasingly difficult
as components and circuits are integrated more densely. Therefore, to design optimal thermal
management at the microscale and nanoscale levels, a technology that can measure temperaturesin a small area easily and accurately is required. Temperature measurement technologies withmicroscale spatial resolutions that are currently in practical use include thermocouples, radiation
thermometers, and Raman spectroscopy.(1–3) Among them, thermoreflectance (TR) imaging,which utilizes the temperature dependence of the reflectance of metal and semiconductor
surfaces, has attracted considerable attention. TR imaging measures mainly visible light, which*Corresponding author: e-mail: shugo.miyake@setsunan.ac.jp

https://doi.org/10.18494/SAM5165

ISSN 0914-4935 © MYU K.K.
https://myukk.org/

3446

Sensors and Materials, Vol. 36, No. 8 (2024)

is noncontact and has a higher spatial resolution than that of radiation thermometers using
infrared rays. On the other hand, since Raman scattering does not occur on pure metals, this TR
method is suitable for temperature measurement. Equation (1) shows the relational equation of
the TR method.
ΔR/R = CTRΔT(1)

Here, R is the reflectance at the reference temperature, ΔR is the reflectance change from R, CTR(1/°C) is the TR coefficient and is a material specific value, ΔT is the temperature change fromthe reference temperature, and ΔT can be obtained by dividing the measured ΔR/R by CTR. CTR
depends on the wavelength of the illuminating light and material. The magnitude of CTR for
metals and semiconductors ranges from 10−3 to 10−5. Therefore, the reflectance change (ΔR/R)
that occurs in response to the temperature change (ΔT) is very small. Because CTR is constantfrom room temperature to approximately 100 °C, ΔR/R is linear with respect to ΔT. Thisfacilitates the temperature calibration of systems based on the TR method.
TR imaging can be broadly classified into two types. The first type uses LEDs as the lightsource.(4–13) TR imaging is characterized by the formation of an image on a CCD element andthe acquisition of a two-dimensional image at a time without the need for stage scanning. By
increasing the magnification of the imaging lens, measurements can be performed with a highspatial resolution. White LEDs can be used to narrow the measurement wavelength to those witha high CTR.(4–9) Therefore, preparing a separate light source is unnecessary, making it easy to
perform high-sensitivity measurements in response to sample changes. However, the signal-tonoise ratio of the CCD is low, and there is a quantization limit consisting of a finite number ofbits.(10) Therefore, it is necessary to repeat the measurements for several minutes to several hours
and perform the averaging process. The second type uses a laser as the light source.(14–19) A laser
beam is monochromatic and coherent, and its spatial resolution is in the sub-micrometer range.
Two-dimensional images can be obtained by scanning the sample stage or laser spot. The
temperature modulation of the sample and the lock-in detection of the intensity-modulated
reflected light make it possible to measure ΔR/R versus ΔT with a high signal-to-noise ratio. TR
measurement by temperature modulation is effective for devices with switching operation using
such components as transistors. However, this is not applicable to devices or circuits with DC
operation. In addition, when the heat transfer pattern from the heat source to the surroundings ofa device is being studied, nonstationary temperature modulation complicates the analysis if
nonlinear effects, such as thermal radiation, are included.
In this study, a temperature measurement system that uses a reflected laser beam that does
not require temperature modulation was developed. First, to evaluate the ΔR/R measurement
accuracy of the developed system, the change in reflectance in a Ni thin film with known CTR
was measured. Moreover, to evaluate the ΔT measurement accuracy of the system, a Ni thin filmthat imitates the wiring pattern of an electronic circuit was heated by an electric current, and thetemperature increase of the surface was measured.

Sensors and Materials, Vol. 36, No. 8 (2024)

2.

3447

Experimental Setup

Figure 1 shows the system developed in this study. The optical system is covered with aninsulated box and an optical surface plate. The temperature is kept at 22 ± 0.3 °C using aprecision air conditioner. The light source is a single-mode fiber-coupled semiconductor laser
with a wavelength of 642 nm, which is a large wavelength for visible light. The laser beam iscollimated by a collimator at the fiber exit end and emitted into free space. An objective lens—
10×, working distance (WD) = 5.5 mm, and numerical aperture (NA) = 0.25—focuses the laser
beam onto the sample surface on the stage. The focus shift is affected by thermal expansion
during heating; however, this is avoided by using a low-NA objective lens in the developed
optical system. To do so, the spot diameter (spatial resolution) measured by the knife-edge
method is 10 μm. The laser intensity used to illuminate the sample is 0.5 mW. Each laser beam,
before and after sample illumination, is bifurcated using a nonpolarizing beam splitter andinjected into a balanced photodetector (PD; Newport Model 2307). The balanced PD consists of
two photodiodes and a differential amplifier circuit. The use of a differential circuit eliminates
several percentage points of the source noise, which is much larger than that of CTR. The voltage
balance of the differential circuit is adjusted using a neutral density (ND) filter inserted on the
PD1 side. The laser intensity is modulated by the output signal of the function generator. The
modulation frequency is sinusoidal at 1 kHz. Lock-in detection at the modulation frequency
using a lock-in amplifier (Stanford Research Systems SR830) is used to measure minutereflectance changes with a high precision. The combination of a balanced PD and lock-in
amplifier makes measurement possible with a high signal-to-noise ratio.

Fig. 1.

(Color online) Temperature measurement system based on TR method.

3448

Sensors and Materials, Vol. 36, No. 8 (2024)

Figure 2 shows the temperature control system for the Ni thin film surface. In thisexperiment, Ni, which has a relatively small CTR, was used as the sample for measurement, and a
Ni thin film with a thickness of 100 nm was deposited on a 10 mm2, 1-mm-thick soda-lime glass
substrate using a DC sputtering system. The deposition conditions were as follows: power inputof 50 W, initial exhaust gas pressure of 5.0 × 10−4 Pa, argon gas pressure of 0.2 Pa, distance of
100 mm between target substrates, deposition time of 20 min, and substrate temperature of room
temperature. An alumina heater was attached to the back of the glass substrate for heating. A
Type K thermocouple was mounted approximately 2 mm from the measurement point. The inplane temperature of the Ni thin film was assumed to be constant because of the heat capacity of
the glass substrate. In addition, 10-mm-thick quartz glass was inserted between the substrate
and the sample stage to suppress thermal expansion. To confirm the repeatability of ΔR/R
measurement, a heating and cooling cycle was performed from room temperature to 100 °C, and
ΔR/R during the cycle was measured. Heating and cooling were performed every 20 °C fromroom temperature. The temperature was maintained for 300 s, and the temperature increase
and decrease were controlled at intervals of 60 s. The measurements were performed at an
ambient temperature of 22 °C under atmospheric pressure. The sampling rate of the detected
laser intensity was set to 1 s.
The Ni wiring pattern film shown in Fig. 3 was subjected to current heating. The Ni thin film
was processed into a thin wire 1 mm wide and 10 mm long on a glass substrate. As the line
width changes, the volume of the thin wire changes, and thus the heat capacity also changes. For
narrower line widths, such as a few µm, the transient temperature rise for instantaneous heating
is steeper because of the smaller heat capacity. Moreover, the measured reflectance change ismore sensitive to the displacement of the sample or laser optical axis. The measurement point
was one point at the center of the thin wire. Voltage was applied to the electrode pads at bothends of the thin wire for current heating. The temperature increase was then determined fromthe CTR of the Ni thin film. After the voltage was applied, ΔR/R was measured at 100 points afterthermal equilibrium was reached.

Fig. 2. (Color online) Temperature control system
for Ni thin film surface.

Fig. 3.

(Color online) Wiring pattern of Ni thin film.

Sensors and Materials, Vol. 36, No. 8 (2024)

3.

3449

Results and Discussion

Figure 4 shows the results of reflectance change measurements for the heating andcooling cycles. The left vertical axis shows the measured ΔR/R. ΔR/R is plotted as open
circles. The right vertical axis represents the Ni thin film surface temperature. Thistemperature is indicated by a solid line. The horizontal axis represents the measurement
time. ΔR/R decreased consistently with increasing temperature and increased consistently
with decreasing temperature. A sharp peak occurred at approximately 1800 s for bothtemperature and ΔR/R. This was because the proportional-integral-derivative temperature
control had ended. A gradual curve of spontaneous cooling from 40 °C to room temperature
was observed. At the end of the measurement, there was not sufficient time for the Ni thinfilm to cool to room temperature+1 °C. The standard deviation of ΔR/R measured during
300 s at each set temperature was <1.00 × 10 −5. The surface temperature accuracy of the Ni
thin film measured by a thermocouple was approximately 0.1 °C. Figure 5(a) shows a plot of
the average ΔR/R at each temperature setting in Fig. 4. The vertical axis represents ΔR/R

Fig. 4.

(Color online) Measured ΔR/R during heating and cooling cycles.

(a)Fig. 5.

(b)(Color online) (a) Reflectance change for each set temperature and (b) CTR calculated for each ΔR/R.

3450

Sensors and Materials, Vol. 36, No. 8 (2024)

and the horizontal axis represents the Ni thin film surface temperature. The dashed line is
the regression line of ΔR/R to temperature. The residual standard deviation was relatively
large at 8.09 × 10 −5. Hysteresis in ΔR/R was considered to have occurred before and after
heating and cooling. It was reported previously that CTR varies greatly depending on thepresence of an oxide film on the surface.(20,21) In this experiment, the Ni thin film washeated and cooled while being exposed to atmospheric pressure; thus, an oxide film may
have grown. The oxide film may weaken the linearity of ΔR/R with respect to thetemperature change in the Ni thin film.
Figure 5(b) shows CTR calculated by dividing ΔR/R in Fig. 5(a) by the temperature change
ΔT of the Ni thin film relative to the reference temperature (room temperature). The numberof plots was reduced from 9 to 8 in Fig. 5(a) because room temperature during heating wasused as the reference temperature. The dashed line shows the regression line of CTR to ΔR/R
for the heating process from room temperature to 100 ℃. The residual standard deviation isvery small at 2.17 × 10 −7 [1/℃], and the accuracy of the regression line is good. Dashed lines
with shorter intervals indicate CTR for the cooling process from 100 °C to room temperature.
All CTR values are negative on the order of 10 −5, which is consistent with literature
values.(22,23) CTR decreases with increasing temperature; however, the values differed
between the above processes. In the cooling process, CTR increased as ΔR/R approached 0.
In particular, CTR at ΔR/R = −1.97 × 10−5 was less than half that at ΔR/R = −0.75 × 10−3. In
addition, the error was extremely large, ±116%. The errors in CTR for heating processes were
±4% for ΔR/R = −0.78 × 10−3, ±1.4% for ΔR/R = −1.70 × 10−3, ±0.8% for ΔR/R = −2.73 × 10−3,
and ±0.6% for ΔR/R = −3.81 × 10−3. Therefore, to achieve an error in CTR within ±1%, ΔR/R
must decrease by more than −2.73 × 10−3.
Figure 6(a) shows the ΔR/R measurement results during the current heating of the Ni
wiring film. The vertical axis represents ΔR/R, and the horizontal axis represents the squareof applied voltage, V2. The dashed line shows the regression line of ΔR/R to the square ofapplied voltage. The residual standard deviation was 1.43 × 10 −5. ΔR/R decreased

(a)

(b)

Fig. 6. (Color online) (a) Reflectance change measured during current heating and (b) temperature change
calculated using CTR.

Sensors and Materials, Vol. 36, No. 8 (2024)

3451

proportionally to V2 , which can be regarded as the amount of heating. The minimum ΔR/R
was −1.4 × 10 −3. This current heating of the Ni thin film was the only heating process;therefore, the CTR value calculated using the high-accuracy regression line in Fig. 5(b) wasused. Figure 6(b) shows ΔR/R in Fig. 6(a) divided by CTR and converted to temperature. The
vertical axis represents the temperature, and the horizontal axis represents V2. The dashedline is the regression line of temperature to V2. The residual standard deviation was 0.39 °C.
Temperature increases of as much as 54.86 °C were observed. The errors in temperature
calculated from the accuracy of ΔR/R and CTR were ±5.3% for T = 22.90 °C, ±2.2% for T =27.22 °C, ±1.3% for T = 34.24 °C, ±0.9% for T = 43.87 °C, and ±0.6% for T = 54.86 °C.
Therefore, temperature can be determined from the error within ±1% for ΔT of more than 22°C. As opposed to 1 point temperature measurement, when using this method to obtaintemperature mapping, care should be taken to avoid focus shift during laser scanning. The inplane focus shift is caused by the flatness of the sample and the accuracy of the sample stage
movement. Moreover. the temperature mapping of different material surfaces should be
calculated from the measured reflectance change to the temperature change using materialspecific CTR.

4.

Conclusion

A temperature measurement system that uses a reflected laser beam that does not requiretemperature modulation was developed. First, to evaluate the accuracy of the measurement
reflectance change ΔR/R, a Ni thin film with a known TR coefficient CTR was subjected to atemperature-controlled heating/cooling cycle, and ΔR/R was measured with respect to thesurface temperature change ΔT. The standard deviation of ΔR/R measured during 300 s at each
set constant temperature was <1.00 × 10−5. The residual standard deviation of the regression lineof ΔR/R upon temperature change was as large as 8.09 × 10−5, indicating low linearity. The CTRvalue obtained by dividing ΔR/R by ΔT was negative, and its order was consistent with thevalues reported in the literature. The error in CTR became smaller as ΔR/R increased, and, when
ΔR/R was smaller than −2.73 × 10−3, the error was less than ±1.0%. Moreover, to evaluate theaccuracy of ΔT measurement, ΔR/R was measured against ΔT by applying electric current
heating to a Ni thin film that imitated the wiring pattern of an electronic circuit. As a result,
ΔR/R decreased proportionally to the square of the applied voltage, which can be regarded as theamount of heating. In the current heating experiment, only heating was performed. Therefore,
CTR was obtained using a high-precision regression line obtained during heating in theexperiment. ΔT was calculated by dividing the measured ΔR/R by CTR, and the error was lessthan ±1.0% when ΔT was 22 °C or higher.

Acknowledgments
Part of this research was supported by a JST Grant-in-Aid for Scientific Research (ProjectNos. 21H01261 and 24H00284).

3452

Sensors and Materials, Vol. 36, No. 8 (2024)

References
1 C. Cengiz, M. Azarifar, and M. Arik: Micromachines 13 (2022) 2. https://doi.org/10.3390/mi13101615
2 L. Dupont, Y. Avenas, and P. O. Jeannin: IEEE Trans. Ind. Appl. 49 (2013) 1599. https://doi.org/10.1364/
OE.27.007945
3 B. Davaji, J. E. Richie, and C. H. Lee: Sci. Rep. 9 (2019) 6546. https://doi.org/10.1038/s41598-019-42999-w
4 D. U. Kim, K. S. Park, C. B. Jeong, G. H. Kim, and K. S. Chang: Opt. Express 24 (2016) 13906. https://doi.
org/10.1364/OE.24.013906
5 H. Zhang, S. Wen, and A. Bhaskar: Appl. Phys. Lett. 114 (2019) 151902. https://doi.org/10.1063/1.5087011
6 B. Vermeersch, J. Bahk, J. Chirstofferson, and A. Shakouri: J. Appl. Phys 113 (2013) 1. https://doi.
org/10.1063/1.4794166
7 D. Pier´sci´nska: J. Phys. D: Appl. Phys. 51 (2018) 013001. https://doi.org/10.1088/1361-6463/aa9812
8 M. Farzaneh, K. Maize, D. Lüerßen, J. A. Summers, P. M. Mayer, P. E. Raad, K. P. Pipe, A. Shakouri, R. J.
Ram, and J. A. Hudings: J. Phys. D: Appl. Phys. 42 (2009) 1. https://doi.org/10.1088/0022-3727/42/14/143001
9 Y. Gao, J. Jin, Y. Ruan, Y. Gao, L. Zhu, Z. Guo, Y. Lin, Z. Chen, and Y. Lu: Opt. Express 27 (2019) 7945.
10 R. Mckenna, D. Mickus, S. Naimi, C. Murphy, M. Mcdermott, S. Corbett, D. Mccloskey, and J. F. Donegan:
OSA Continuum 4 (2021) 1271. https://doi.org/10.1364/OSAC.422429
11 T. Zhu, D. H. Olson, P. E. Hopkins, and M. Zebarjadi: Rev. Sci. Instrum. 91 (2020) 113701. https://doi.
org/10.1063/5.0024476
12 Y. Zhang, J. Chirstofferson, A. Shakouri, D. Li, A. Majumdar, Y. Wu, R. Fan, and P. Yang: IEEE Trans.
Nanotechnol. (2006) 67. https://doi.org/10.1109/TNANO.2005.861769
13 Y. Sugihara, R. Uemura, K. Tamai, R. Kuriyama, and K. Tatsumi: The 33rd Int. Symp. Transport Phenomena(2023) 67–74.
14 D. U. Kim, C. B. Jeong, J. D. Kim, K. Lee, H. Hur, K. Nam, G. H. Kim, and K. S. Chang: Sensors 17 (2017)2774. https://doi.org/10.3390/s17122774
15 P. M. Mayer, D. Lüerßen, R. J. Ram, and J. A. Hudgings: J. Opt. Soc. Am. A 24 (2007) 1156.
16 S. Dilhaire, S. Grauby, and W. Claeys: Appl. Phys. Lett. 84 (2004) 822. https://doi.org/101063/1.1645326
17 D. Pier´sci´nska, A. Kozlowska, K. Pier´sci´nski, M. Bugajsk, J. W. Tomm, M. Ziegler, and F. Weik: J. Mater.
Sci. Mater. Electron. 19 (2008) S150–S154. https://doi.org/10.1007/s10854-008-9643-z
18 P.-L. Komarov, M. G. Burzo, and P.-E. Raad: Proc. 12th THERMINIC (2006) 12–17.
19 M. G. Burzo, P. L. Komarov, and P. E. Raad: IEEE Trans. Compon. Packag. Manuf. Technol. 28 (2005) 637–
643. https://doi.org/10.1109/TCAPT.2005.859738
20 C. Shi, X. Wang, Q. Zheng, J. Maroske, and D. Thompson: Opt. Express 32 (2024) 1003. https://doi.org/10.1364/
OE.511938
21 T. Favaloro, J.-H. Bahk, and A. Shakouri: Rev. Sci. Instrum. 86 (2015) 024903. https://doi.org/10.1063/1.4907354
22 B. Meng, Y. Ma, X. Wang, and C. Yuan: J. Appl. Phys. 134 (2023) 115102. https://doi.org/10.1063/5.0164110
23 J. Hanus, J. Feinleib, and W. Scouler: Phys. Rev. Lett. 19 (1967) 16. https://doi.org/10.1103/PhysRevLett.19.16