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Self-heating degrades the performance of devices in advanced technology nodes. Understanding of self-heating effects is necessary to improve device performance. Heat generation in these devices occurs at nanometer scales but heat transfer is a microscopic phenomena. Hence a multi-scale modeling approach is required to study the self-heating effects. A state of the art Monte Carlo device simulator and the commercially available Giga 3D tool from Silvaco are used in our study to understand the self heating effects. The Monte Carlo device simulator solves the electrical transport and heat generation for nanometer length scales accurately while the Giga 3D tool solves for thermal transport over micrometer length scales. The approach used is to understand the self-heating effects in a test device structure, composed of a heater and a sensor, fabricated and characterized by IMEC. The heater is the Device Under Test(DUT) and the sensor is used as a probe. Therefore, the heater is biased in the saturation region and the sensor is biased in the sub-threshold regime. Both are planar MOSFETs of gate length equal to 22 nm. The simulated I-V characteristics of the sensor match with the experimental behavior at lower applied drain voltages but differ at higher applied biases.
The self-heating model assumes that the heat transport within the device follows Energy Balance model which may not be accurate. To properly study heat transport within the device, a state of the art Monte Carlo device simulator is necessary. In this regard, the Phonon Monte Carlo(PMC) simulator is developed. Phonons are treated as quasi particles that carry heat energy. Like electrons, phonons obey a corresponding Boltzmann Transport Equation(BTE) which can be used to study their transport. The direct solution of the BTE for phonons is possible, but it is difficult to incorporate all scattering mechanisms. In the Monte Carlo based solution method, it is easier to incorporate different relevant scattering mechanisms. Although the Monte Carlo method is computationally intensive, it provides good insight into the physical nature of the transport problem. Hence Monte Carlo based techniques are used in the present work for studying phonon transport. Monte Carlo simulations require calculating the scattering rates for different scattering processes. In the present work, scattering rates for three phonon interactions are calculated from different approaches presented in the literature. Optical phonons are also included in the transport problem. Finally, the temperature dependence of thermal conductivity for silicon is calculated in the range from 100K to 900K and is compared to available experimental data.
The self-heating model assumes that the heat transport within the device follows Energy Balance model which may not be accurate. To properly study heat transport within the device, a state of the art Monte Carlo device simulator is necessary. In this regard, the Phonon Monte Carlo(PMC) simulator is developed. Phonons are treated as quasi particles that carry heat energy. Like electrons, phonons obey a corresponding Boltzmann Transport Equation(BTE) which can be used to study their transport. The direct solution of the BTE for phonons is possible, but it is difficult to incorporate all scattering mechanisms. In the Monte Carlo based solution method, it is easier to incorporate different relevant scattering mechanisms. Although the Monte Carlo method is computationally intensive, it provides good insight into the physical nature of the transport problem. Hence Monte Carlo based techniques are used in the present work for studying phonon transport. Monte Carlo simulations require calculating the scattering rates for different scattering processes. In the present work, scattering rates for three phonon interactions are calculated from different approaches presented in the literature. Optical phonons are also included in the transport problem. Finally, the temperature dependence of thermal conductivity for silicon is calculated in the range from 100K to 900K and is compared to available experimental data.
ContributorsShaik, Abdul Rawoof (Author) / Vasileska, Dragica (Thesis advisor) / Ferry, David (Committee member) / Goodnick, Stephan (Committee member) / Arizona State University (Publisher)
Created2016