Hanyang University · Engineering
Professor Seung Hwan Lee's research lab specializes in advanced materials and manufacturing technologies, focusing on lightweight multifunctional composites, wire arc additive manufacturing (WAAM), and thin film-based optical sensors. The lab investigates the development of high-performance materials with combined electromagnetic interference (EMI) shielding and thermal conductivity for aerospace, automotive, and electronic applications, while also advancing process modeling and optimization in additive manufacturing. Additionally, the lab explores ultrafast optical phenomena and heterostructure dynamics using time-resolved x-ray diffraction, contributing to next-generation photonic and sensing devices.
Figures are computed from collected data and may differ slightly.
Lightweight dual-functional materials with high EMI shielding performance and thermal conductivity are of great importance in modern cutting-edge applications, such as mobile electronics, automotive, aerospace, and military. Unfortunately, a clear material solution has not emerged yet. Herein, we demonstrate a simple and effective way to fabricate lightweight metal-based polymer composites with dual-functional ability of excellent EMI shielding effectiveness and thermal conductivity using expand
CMT welding sources are garnering attention as alternative heat sources for wire arc additive manufacturing because of their low-heat input. A comprehensive experimental and numerical study on the multi-layer deposition of STS316L was performed to investigate effect of heat accumulation during the deposition. The numerical model which is appropriate for WAMM was developed considering the characteristics of the CMT heat source for the first time. Using a high-speed camera, the transient behavior
Wire and arc additive manufacturing (WAAM) is among the most promising additive manufacturing techniques for metals because it yields high productivity at low raw material costs. However, additional post-processing is required to remove redundant surface material from components manufactured by the WAAM process, and thus the productivity decreases. To increase productivity, multi-variable process parameters need to be optimized, including thermo-mechanical effects caused by high deposition rates
We report on the propagation of coherent acoustic wave packets in (001) surface oriented Al0.3Ga0.7As/GaAs heterostructure, generated through localized femtosecond photoexcitation of the GaAs. Transient structural changes in both the substrate and film are measured with picosecond time-resolved x-ray diffraction. The data indicate an elastic response consisting of unipolar compression pulses of a few hundred picosecond duration traveling along [001] and [001] directions that are produced by pred
Thin film-based optical sensors have been attracting increasing interest for use in developing technologies such as biometrics. Multilayered dielectric thin films with different refractive indices have been utilized to modulate the optical properties in specific wavelength bands for spectral selectivity of Thin Film Narrow Bandpass Filters (TFNBFs). Progress in TFNBF design has been made with the incorporation of metallic thin films. Narrower bandwidths with higher transmittance have been achiev
This study aimed to suggest a solidification map based on the solidification parameters G and R of each layer in the multilayer deposition for the investigation of heat accumulation on the deposit. Through the solidification map, the appropriate solidification conditions of the microstructure were determined. In order to investigate the solidification parameters, the temperature profile of the deposit was experimentally acquired during deposition. A simulation model reflecting the characteristic
In this study, microstructures of weldment produced using carbon steel A516 grade 60 were analysed via a deep learning approach to measure the fraction of acicular ferrite which considerably influences on mechanical properties of carbon steel. The fully convolutional network was used to conduct the image segmentation. Submerged arc welding was used for welding, and the dataset was constructed using optical microscope. The model was compiled with ResNet, which is the state-of-the-art classifier u
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