Title:  Investigating Ferroelectric and Metal-insulator Phase Transition Devices for Neuromorphic Computing

Committee: 

Dr. Yu, Advisor   

Dr. Khan, Chair

Dr. Naeemi

Abstract:

The objective of the proposed research is to investigate the ferroelectric and metal-insulator phase transition(MIT) devices for neuromorphic computing. The research first focuses on ferroelectric doped HfO2 based ferroelectric field-effect transistors (FeFETs) for neuron synaptic devices. For the first time, this work proposed a 3D vertical channel NAND-like ferroelectric transistor (FeFET) array architecture feasible for both in-situ training and inference. To address the challenge of erase-by-block in 3D NAND-like structure, we proposed and experimentally demonstrated the drain erase scheme to enable the individual cell program/erase/inhibition, which is necessary for in-situ training.  For a neuromorphic system, it consists of both synapse and neuron. We fabricated a crossbar array that structurally resembles a column of the neural network. We integrate a MIT (NbO2 ) devices at the edge of the crossbar array as a compact oscillation neuron, which converts the weighted sum to an oscillation frequency. When the input vectors are loaded into multiple rows of the array, the oscillation frequency is measured to be proportional to the analog column current. This is the first experimental demonstration of an integrated crossbar array with both synapses and neurons, paving the path to fully parallel computation and processing using emerging device technologies for neuromorphic computing.