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

To fundamentally solve the bottleneck of Von Neumann&#x2019;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 <inline-formula> <tex-math notation="LaTeX">$\text{G}_{\mathrm {max}}/\text{G}_{\mathrm {min}} \cong ~1000$ </tex-math></inline-formula> was obtained, and the channel conductance was maintained over 40000 seconds. The optimized pulse achieved multi-level states (&#x003E;32), which made the learning process efficient. This study verified that the PZT-TFT structure has a high potential and merits for neuromorphic devices.