Hyperspectral Thermoreflectance Imaging for Thermal Mapping
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Solution Overview
Problem
Current thermoreflectance-based non-contact thermal imaging systems face challenges in achieving high spatial resolution and accuracy due to the complexity of surface materials and movement issues, particularly when dealing with electronic devices that have different thermoreflectance coefficients and surface coatings.
Innovation Solution
A hyperspectral thermoreflectance imaging method and system that calibrate the thermoreflectance coefficient for multiple wavelengths, allowing for precise temperature mapping by fitting the relative change in reflection to a mathematical function, thereby improving spatial resolution and accuracy across various materials and surfaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single illumination wavelength is used to maximize thermoreflectance coefficient, then signal to noise ratio is improved, but measurement accuracy deteriorates due to sample roughness, surface coating, and sample movement
Solution Approach 1:
The patent changes the parameter of illumination wavelength from a fixed single value to multiple wavelengths. By capturing thermoreflectance data at multiple wavelengths and fitting to a mathematical model, the system achieves both high signal-to-noise ratio (through optimal wavelength selection) and high measurement accuracy (through multi-parameter fitting that compensates for surface variations and movement)
Solution Approach 2:
The patent adds the wavelength dimension to the measurement space. Instead of measuring at a single wavelength, the system captures spectral data across multiple wavelengths, transforming a 2D spatial measurement into a 3D spectral-spatial measurement that provides additional information for accurate temperature determination
2Measurement precision
If hyperspectral multi-wavelength calibration is implemented, then spatial resolution and measurement accuracy are improved, but device complexity increases
Solution Approach 1:
The patent implements a universal calibration procedure that works across multiple wavelengths and different material types. The mathematical fitting model serves as a multi-functional tool that simultaneously handles spectral variation, surface roughness, coating effects, and movement compensation, reducing the need for separate calibration systems for different conditions
Solution Approach 2:
The system performs self-calibration through the mathematical fitting process. By fitting the multi-wavelength thermoreflectance data to the predetermined function, the system automatically determines the thermoreflectance coefficient and temperature without requiring external reference measurements or manual calibration for each wavelength, reducing operational complexity
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The method provides fully calibrated thermal images with enhanced spatial resolution and accuracy, reducing optical anomalies and improving temperature measurement precision, especially for devices with passivation layers, through the use of hyperspectral curve fitting and multi-wavelength data processing.
Implementation Method 1
Thermoreflectance-based imaging is dependent on the measurement of the relative change in the sample's surface reflectivity as a function of temperature. As the temperature of a sample changes, the refractive index, and therefore, the reflectivity also changes.
Implementation Method 2
The testing stage is configured to align the electronic device according to a set of coordinates and change the temperature of the electronic device
Data Source
AI summary
A method for providing a high spatial resolution thermal imaging of an active electronic device. The method includes placing an electronic device on a testing stage of an imaging system. The method, calibrating the imaging system by determining thermoreflectance coefficient for a plurality of pixels forming thermal images, each pixel having a coordinate (x,y) captured from the electronic device at each of a plurality of wavelengths of illumination (CTRi(x,y,λi), activating the electronic device, and determining changes in reflection for each of the plurality of pixels at each of the plurality of wavelengths (ΔR/R), determining ΔR/R vs. CTRi(x,y,λi) for each of the plurality of pixels for each of the plurality of wavelengths, fitting ΔR/R vs. CTRi(x,y,λi) to a predetermined mathematical function and use the parameters to calculate the temperature at each pixel.