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Time-domain thermoreflectance technique using multiple delayed probe pulses for high-throughput data acquisition and

Hiroto Arima1, Yuichiro Yamashita1, Takashi Yagi1

  • 1National Metrology Institute of Japan (NMIJ), National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan.

Science and Technology of Advanced Materials
|July 16, 2025
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Summary

A new high-throughput time-domain thermoreflectance (HT-TDTR) technique rapidly measures material thermophysical properties. Machine learning further accelerates this process, enabling quick and accurate thermal characterization.

Keywords:
Time-domain thermoreflectanceinterfacial thermal resistancemachine learningmultiple delaythermal effusivitythin film

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Area of Science:

  • Materials Science
  • Condensed Matter Physics
  • Thermal Engineering

Background:

  • Understanding microscopic heat transport is vital for advancing thermal control and device performance.
  • Current methods for measuring thermophysical properties can be time-consuming.

Purpose of the Study:

  • To develop a high-throughput time-domain thermoreflectance (HT-TDTR) technique for accelerated measurement of thermophysical properties.
  • To demonstrate the application of machine learning for rapid material characterization.

Main Methods:

  • Developed HT-TDTR by decomposing supercontinuum light into multiple delayed probe pulses for simultaneous signal acquisition.
  • Applied picosecond pulsed light to heat quartz glass, SrTiO3, and sapphire.
  • Utilized machine learning algorithms to analyze thermoreflectance data with minimal delay points.

Main Results:

  • Simultaneously measured temporal temperature decrease at multiple delay times.
  • Analyzed thermal effusivities, showing consistency with literature values.
  • Demonstrated machine learning's ability to predict thermal effusivity from minimal data in under a second.

Conclusions:

  • HT-TDTR enables rapid and accurate measurement of thermophysical properties.
  • Machine learning significantly enhances the efficiency of material characterization using thermal relaxation dynamics.
  • The developed technique facilitates more efficient characterization for improved thermal management.