arXiv subjects

Sungkyu Kim

Publications and source records attributed to Sungkyu Kim.

3 recordsLinked to original sources

arXiv2025

Rapid low-temperature synthesis of graphene-coated SiC substrates for remote and van der Waals epitaxy

Non-conventional epitaxial techniques, such as van der Waals epitaxy (vdWE) and remote epitaxy, have attracted substantial attention in the semiconductor research community for their capability to repeatedly produce high-quality free-standing films from a single mother wafer. Successful implementation of these epitaxial techniques depends on creating a robust, uniform two-dimensional (2D) material surface. The conventional method for fabricating graphene on silicon carbide (SiC) is high-temperature graphitization. However, the extremely high temperature required for silicon sublimation (typically above 1500 °C) causes step-bunching of the SiC surface, forming non-uniform multilayer graphene stripes and an unfavorable surface morphology for epitaxial growth. Here, we developed a wafer-scale graphitization technique that allows fast synthesis of single-crystalline graphene at ultra-low temperatures by metal-assisted graphitization (MAG). We found annealing conditions that enable SiC dissociation while avoiding silicide formation, producing uniform single-crystalline graphene while maintaining the surface morphology of the substrate. The graphene thickness can be controlled by varying the metal thickness or annealing temperature, enabling remote epitaxy or vdWE. We successfully produced freestanding single-crystalline III-N (AlN, GaN) films on graphene/SiC via the 2D material-based layer transfer technique. Our results show that low-temperature graphene synthesis via MAG offers a promising route to producing large-scale ultra-wide bandgap free-standing crystalline membranes.

cond-mat.mtrl-sci↗

arXiv2025

CNN-based TEM image denoising from first principles

Transmission electron microscope (TEM) images are often corrupted by noise, hindering their interpretation. To address this issue, we propose a deep learning-based approach using simulated images. Using density functional theory calculations with a set of pseudo-atomic orbital basis sets, we generate highly accurate ground truth images. We introduce four types of noise into these simulations to create realistic training datasets. Each type of noise is then used to train a separate convolutional neural network (CNN) model. Our results show that these CNNs are effective in reducing noise, even when applied to images with different noise levels than those used during training. However, we observe limitations in some cases, particularly in preserving the integrity of circular shapes and avoiding visible artifacts between image patches. To overcome these challenges, we propose alternative training strategies and future research directions. This study provides a valuable framework for training deep learning models for TEM image denoising.

cond-mat.mtrl-sci↗

arXiv2022

Multiplication of freestanding semiconductor membranes from a single wafer by advanced remote epitaxy

Freestanding single-crystalline membranes are an important building block for functional electronics. Especially, compounds semiconductor membranes such as III-N and III-V offer great opportunities for optoelectronics, high-power electronics, and high-speed computing. Despite huge efforts to produce such membranes by detaching epitaxial layers from donor wafers, however, it is still challenging to harvest epitaxial layers using practical processes. Here, we demonstrate a method to grow and harvest multiple epitaxial membranes with extremely high throughput at the wafer scale. For this, 2D materials are directly formed on III-N and III-V substrates in epitaxy systems, which enables an advanced remote epitaxy scheme comprised of multiple alternating layers of 2D materials and epitaxial layers that can be formed by a single epitaxy run. Each epilayer in the multi-stack structure is then harvested by layer-by-layer peeling, producing multiple freestanding membranes with unprecedented throughput from a single wafer. Because 2D materials allow peeling at the interface without damaging the epilayer or the substrate, wafers can be reused for subsequent membrane production. Therefore, this work represents a meaningful step toward high-throughput and low-cost production of single-crystal membranes that can be heterointegrated.

physics.app-ph↗