Sijay Huang

Date of Award


Document Type


Degree Name

Doctor of Philosophy (PhD)


Electrical and Computer Engineering

Committee Chair

Biswajit Ray

Committee Member

James K. Baird

Committee Member

Ravi Gorur

Committee Member

Sivaguru S. Ravindran

Committee Member

B. Earl Wells


Flash memories (Computers)--Reliability, Random access memory--Reliability


Semiconductor non-volatile memory (NVM) devices are predominantly used for storing the large amount of data produced by the proliferation of the Internet of Things (IoT), mobile networks, and sensor node applications. Since data are growing at an exponential rate, future NVM solutions need to provide even higher bit densities, superior performance, better energy efficiency, and improved resilience. Technological scaling has been the primary driving force for increasing the bit density of semiconductor NVM technologies. However, the scaling leads to reliability challenges, such as endurance, data retention, and thermal noise effects. This dissertation numerically evaluates reliability issues associated with the two important classes of semiconductor memory technology: (1) electron charge-based 3D NAND flash memory and (2) electron spin-based magnetoresistive random-access memory (MRAM). A commercial device simulator (called Taurus Medici) from Synopsys has been used for the reliability analysis of the 3D NAND flash memory. The simulator solves Poisson's equation and the drift-diffusion transport equations to predict the electrical properties of the cell based on its geometry and material characteristics. A number of novel device design ideas are proposed and validated by numerical simulation, which can potentially enable further scaling of the future generation of 3D NAND technologies. MRAM reliability is studied by focusing on the magnetic tunnel junction (MTJ), which is the core component of the memory cell. A simulation framework has been developed by numerically solving the Landau–Lifshitz–Gilbert equation, which describes the dynamics of the magnetization as a function of the external magnetic field, the spin current, and the ambient thermal fluctuations. Finally, a Monte Carlo model is established to analyze the dielectric breakdown of insulating layers, which are common components in both types of semiconductor memory.



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