Date of Award
Master of Science in Computer Engineering - (M.S.)
Electrical and Computer Engineering
The scalability and power efficiency of the conventional CMOS technology is steadily coming to a halt due to increasing problems and challenges in fabrication technology. Many non-volatile memory devices have emerged recently to meet the scaling challenges. Memory devices such as RRAMs or ReRAM (Resistive Random-Access Memory) have proved to be a promising candidate for analog in memory computing applications related to inference and learning in artificial intelligence. A RRAM cell has a MIM (Metal insulator metal) structure that exhibits reversible resistive switching on application of positive or negative voltage. But detailed studies on the power consumption, repeatability and retention of during multi-level operation have not been undertaken previously.
Transition metal oxide-based RRAMs, using HfO2, executes change in resistance (switching behavior) via electrochemical migration of oxygen vacancies. This thesis investigates the role of extra oxygen vacancies, introduced by plasma exposure (treated), in HfO2 to reduce the power consumption of RRAM. In addition to oxygen vacancy rich HfO2, various top metal electrodes including Ruthenium (Ru) are explored to enhance the switching behavior and power consumption. Use of Ru as a top metal reduced the switching energy of the treated HfO2 RRAM device.
Patel, Yuvraj Dineshkumar, "Treated HfO2 based rram devices with ru, tan, tin as top electrode for in-memory computing hardware" (2020). Theses. 1807.
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