Projects

Research Interests

I. Thermal Trends in Microelectronic Devices

Increasing power density and more critical self-heating is observed for devices across several technologies due to several emerging trends.

• Miniaturization trend (Moore's law) provides
1. Faster switching devices (higher frequency)
2. More efficient (less energy, cheaper operation)
3. Higher productivity (more devices per wafer)
• Increased demand for power telecommunication systems, radars, automotive, and industrial applications
• 2.5D and 3D stacking technologies for faster on-chip communication and ULSI integration

Temperature affects mechanical, thermal and electrical parameters. Overheating causes:

1. Deviation from design tolerances
2. Accelerated Electro-migration failures in the back-end of ICs
3. Degradation in device performance

1. Reduction in time to failure and improved reliability
2. Accurate operation in micro-devices (ex: micro-sensors)
3. Understanding the operating mechanisms behind emerging technologies (ex: memristors)

II. Present Challenges for Characterization Techniques
A. Experimental

• Resolution:
Diffraction limited for IR to (4, 10 µm) and requires higher wavelength illumination for higher resolutions.
• Accessibility
Optical methods may be inaccessible to active regions in device (field plates, 3D stacking...)
• Accuracy and validity
Some measurement techniques require highly effective calibrations and sample preparations before testing

B. Computational

• Complex Physics:
Complexity in coupled electro-thermal physics and heat generation mechanism and profile
• Large Variation in Physical and Time Scales
Physical and time scales ranging from meso to sub-microns require non-uniform meshing
• Uncertainty in Device Thermal Parameters
Thermo-physical properties depend on fabrication and composition, vary from bulk values, and may require in-situ measurements

III. Advanced Thermal Characterization Techniques for Microelectronic Devices and Technologies

A. Thermoreflectance Imaging for High Resolution Thermal Mapping

• A device under test (DUT) is illuminated at an optimal wavelength and then activated and modulated (on/off or high/low)
• As the DUT surface temperature changes, the magnitude of reflected energy changes
• Changes in temperature and in reflectivity are related by the Coefficient of Thermal Reflectance CTR=(1/ΔT)(ΔR/R)

The method is non-contact optical method that can measure at sub-micron resolutions (0.3, 0.5 µm) and acquire quick thermal maps without need for scanning. Also TR can measure from surface of GaN, which is transparent to visible and IR illuminated, by using near-UV light. TR is also lock-in method and can detect minute signals of reflectance change.

• Device is electrically activated causing its temperature to rise by Joule heating, while the reflected light intensity (R) is acquired.
• Reflectance change field (Δ𝑅/𝑅) is captured at each pixel as the device is modulated

• A known Δ𝑇 is globaly applied to the device via a Peltier heating element
• Calibration field (𝐶𝑇𝑅) is captured at each pixel

C. Self-Adaptive Multi-grid Thermal Simulations

• Solves thermal transients over large range of spatial and temporal scales 100X faster than conventional methods
• Independent of user expertise in meshing
• Independent of materials, geometric features, and locations of heat sources
• Eliminates need for expensive convergence studies
• Enables electro-thermal concurrent design of high-performance ICs

B. Experimentally-Driven Reverse Modeling Simulations

Reverse modeling approach allows to utilize the regions that are accessible for measurements to drive the developed thermal models and optimize the input thermal parameters within a reasonable range. The combined method provides:

• Validated model that matches experimentally observed thermal response
• 3D Temperature distribution and access to imbedded features
• Accurate characterization for uncertain device parameters
• Digital twin for the actual device that can be used for parametric studies in design cycles