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Related Experiment Video

Updated: Dec 25, 2025

The Frequency Domain Thermoreflectance Technique for Thermal Property Measurements

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Amirkoushyar Ziabari, Maryam Parsa, Yi Xuan

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Summary

This summary is machine-generated.

This study introduces a Bayesian optimization method to accurately map temperature hotspots in microelectronic devices. This non-contact thermal imaging technique achieves high resolution, improving device performance and reliability predictions.

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Area of Science:

Materials Science
Electrical Engineering
Applied Physics

Background:

Non-uniform self-heating and temperature hotspots degrade submicron electronic device performance and reliability.
Accurate temperature measurement at deep submicron scales is challenging due to artifacts and diffraction limits.
Non-contact thermal characterization offers a valuable alternative for analyzing temperature distribution.

Purpose of the Study:

To develop a novel Bayesian optimization framework for accurate full-field temperature distribution mapping.
To achieve spatial resolution significantly below the diffraction limit using thermoreflectance thermal imaging (TRI).
To reliably estimate regularization parameters for inverse problems in thermal characterization.

Main Methods:

Utilized a Bayesian optimization framework with a generalized Gaussian Markov random field (GGMRF) prior model.
Employed thermoreflectance thermal images (TRI) for temperature distribution analysis.
Integrated finite element simulations with experimental TRI data to characterize the optical system's point spread function.
Estimated regularization parameters using numerical experiments and finite element modeling for inverse problem solving.

Main Results:

Achieved accurate full-field temperature distribution of self-heated metal interconnects.
Obtained a spatial resolution 2.5 times below the Rayleigh limit for 530nm illumination.
Successfully solved a real experimental inverse problem by estimating the regularization parameter.

Conclusions:

The developed Bayesian optimization framework enables high-resolution, non-contact thermal characterization of microelectronic devices.
This method overcomes limitations of traditional techniques for hotspot analysis in submicron devices.
Accurate temperature mapping is crucial for enhancing the performance and reliability of advanced electronic and optoelectronic components.