UROP Proceedings 2020-21

School of Engineering Department of Electronic and Computer Engineering 160 Circuit Emulation of Bio-Inspired Dynamic and Topological Quantum Systems Supervisor: SHAO Qiming / ECE Student: ZHENG Wenhan / SENG Course: UROP1100, Summer This UROP program has a task to reproduce a memristor emulator using electronic components. In this paper, two memristor emulator is being tested. The first one is reproduced and tested with fatal problems. Various methods including changing the input, loosening the precision restriction and changing the configuration of the circuit are used. However, it cannot give acceptable output and failed to show the hysteresis loop. Using the experience in building and testing the first model, the second model proposed in the reference of the first model is constructed and tested. By changing the input frequency and modifying the circuit, the output is much more preferable and the plot shows the symbolic hysteresis loop of the memeristor. Compact Models for Circuit Design Supervisor: SHAO Qiming / ECE Student: FANG Yidong / ELEC Course: UROP1100, Fall Spin-transfer torque magnetic tunnel junction (STT-MTJ) is an emerging field for nonvolatile memories because of its fast speed, low power and perfect endurance. In this work, the STT-MTJ basic properties has been simulated through MATLAB such as the MTJ conductance, the tunneling magnetoresistance, switching probability and critical current switching via Brinkman physical model and Slonczewski model. From the results, we can find the that the conductance of MTJ is almost constant when it is in parallel state (P state) and has a quadratic character when in anti-parallel state (AP state), also the current has a more linear feature with the bias voltage when the magnetic tunnel junction is at the parallel state and non-linear when it is at anti-parallel state. The simulation results show great consistency with the experimental results from the two models mentioned above and the paper from Beihang University. Based on these characteristics, magnetic tunnel junction has becoming one of the most promising spintronic devices in academic world and is very predicting when it is used in some nonvolatile memories such as magnetic Spin-transfer torque random access memory (STT-MRAM). Compact Models for Circuit Design Supervisor: SHAO Qiming / ECE Student: NUGRAHA Ferris Prima / CPEG Course: UROP1100, Spring The objective of this research is to develop a compact model which accurately predicts the behavior of stochastic Magnetic Tunnel Junction (MTJ) with respect to the factors including external magnetic fields, anisotropy types, and the energy barrier of the nanomagnet. This project investigates the previous research papers and attempts to confirm the correlation between the relaxation time with the factors through numerical simulations and equations. This would be critical in future hardware implementation including in the non-volatile magnetic RAM (MRAM) and probabilistic computing applications along with the Binary Stochastic Neuron (BSN) in machine learning. Several phenomena to be studied involves the spin dynamics described in the Landau-Lifshitz-Gilbert (LLG) equation, Spin-Transfer Torque (STT), Spin-Orbit Torque (SOT), and stochastic thermal noise.