Research

We focus on functional thin film materials and their fabrication processes, such as atomic layer deposition (ALD). The performance of these films can be enhanced by optimizing ALD conditions and film structures. Properly optimized deposition parameters result in the desired properties, such as ferroelectricity, resistive switching, or conducting interfaces.

An ideal memory should exhibit fast operation speed, high storage density, low energy consumption, unlimited endurance, and non-volatility. However, none of the conventional memory technologies currently satisfy all these criteria simultaneously. This is why we are actively exploring emerging memory technologies that aim to fulfill as many of these requirements as possible. Furthermore, nonlinear circuit elements, such as memristors, offer significant advantages for enhancing the performance and capabilities of electronic systems. 

Conventional computing system, von Neumann architecture, encounters significant challenges with handling AI tasks. Neuromorphic computing is a next-generation computing technology inspired by the structure and operation of the human brain. A key feature of neuromorphic computing is in-memory computing, where data storage and computation occur in the same location, unlike traditional von Neumann architectures. It is an exciting interdisciplinary field involving novel devices, analog circuit design, and system architecture. Neuromorphic computing represents a step toward hardware that can think and learn like the brain.