PZT Ferroelectric Synapse TFT With Multi-Level of Conductance State for Neuromorphic Applications

Abstract

To fundamentally solve the bottleneck of Von Neumann’s computing architecture, a neuromorphic thin-film transistor (NTFT) employing Pb(Zr, Ti)O3 (PZT) was investigated. The indium gallium zinc oxide (IGZO) channel back gate TFT structure was chosen to solve the diffusion of atoms that form a channel layer during the annealing process for crystallization of PZT. A post-deposition process with IGZO after annealing PZT and using an oxide-based material as a channel structure can minimize the diffusion phenomenon of junction materials and oxygen together, which leads to a high and reliable performance of the NTFT. The basic operations of synapses short-term memory (STM) and long-term memory (LTM) were also analyzed to confirm the application of a neuromorphic device. The high dielectric constant and polarization properties of Pb(Zr, Ti)O3 (PZT) allow the power consumption of spike signals used in spike dependent plasticity change to be reduced to 10 pJ. Moreover, a wide dynamic range of $\text{G}_{\mathrm {max}}/\text{G}_{\mathrm {min}} \cong ~1000$ was obtained, and the channel conductance was maintained over 40000 seconds. The optimized pulse achieved multi-level states (>32), which made the learning process efficient. This study verified that the PZT-TFT structure has a high potential and merits for neuromorphic devices.

Keywords

• Ferroelectric
• synapse
• neuromorphic
• multi-level
• transistor