Jiseong Im

The discovery of ferroelectricity in hafnia-based materials has revitalized interest in realizing ferroelectric field-effect transistors (FeFETs) due to its compatibility with modern microelectronics. Furthermore, low-temperature processing by atomic layer deposition...

Artificial neurons and synapses are crucial for efficiently implementing spiking neural networks (SNNs) in hardware. The distinct functional requirements of artificial neurons and synapses present significant challenges in the implementation...

Ferroelectric (FE) materials are key to advancing electronic devices owing to their non-volatile properties, rapid state-switching abilities, and low-energy consumption. FE-based devices are used in logic circuits, memory-storage devices, sensors,...

Smart healthcare systems integrated with advanced deep neural networks enable real-time health monitoring, early disease detection, and personalized treatment. In this work, a novel 3D AND-type flash memory array with...

Hardware neuromorphic systems are crucial for the energy-efficient processing of massive amounts of data. Among various candidates, hafnium oxide ferroelectric tunnel junctions (FTJs) are highly promising for artificial synaptic devices....

The elastic-to-plastic transition during the deformation of a dislocation-free nanoscale volume is accompanied by displacement bursts associated with dislocation nucleation. The dislocations that nucleate during the so-called "pop-in" burst take...

Mechanical response of metal nanowires has recently attracted a lot of interest due to their ultra-high strengths and unique deformation behaviours. Atomistic simulations have predicted that face-centered cubic metal nanowires...

We present high performance gas sensors based on an array of near single crystalline TiO(2) nanohelices fabricated by rotating oblique angle deposition (OAD). The combination of large surface-to-volume ratio, extremely...