Hanyang University · Engineering
Professor Seongmin Park's research lab specializes in interdisciplinary applications of machine learning and advanced materials, focusing on sustainable and intelligent systems. The lab explores flexible electronics through innovative substrate designs that enhance mechanical durability, while also advancing food safety via hyperspectral imaging and machine learning for non-destructive meat quality assessment. Additionally, the lab contributes to natural language processing by developing unsupervised dialogue summarization techniques and improving sequence modeling in text generation. The research integrates data-driven methods with physical and behavioral modeling to solve real-world challenges in health, safety, and materials science.
Figures are computed from collected data and may differ slightly.
Abstract Very recently, MXene‐based wearable hydrogels have emerged as promising candidates for epidermal sensors due to their tissue‐like softness and unique electrical and mechanical properties. However, it remains a challenge to achieve MXene‐based hydrogels with reliable sensing performance and prolonged service life, because MXene inevitably oxidizes in water‐containing system of the hydrogels. Herein, catechol‐functionalized poly(vinyl alcohol) (PVA‐CA)‐based hydrogels is proposed to inhib
The schematic of CO<sub>2</sub> electrolysis to produce CO in an SOEC under the conditions of CO<sub>2</sub> gas containing H<sub>2</sub>S.
The direct use of conventional photosensitizers in photodynamic therapy (PDT) of cancer cells has been thwarted by their low solubility, poor photostability, and aggregation tendency. Hence, complex and hectic synthetic procedures, such as developing nanomaterials and subsequently loading them with photosensitizers, have become mandatory for the effective use of photosensitizers in PDT. In this study, we have avoided complex procedures and produce hematoporphyrin (HP) photosensitizer-encapsulate
We report a highly improved cathode catalyst by doping fluorine anions in oxygen sites of a Ruddlesden–Popper material for CO2 electrolysis to produce CO in solid oxide electrolysis cells (SOECs). The obtained fluorine-doped catalyst of La0.9Sr0.8Co0.4Mn0.6O3.9−δF0.1 (R.P.LSCoMnF) exhibited the higher electrochemical performance of 499 mA/cm2 at 1.3 V and 850 °C with the smaller polarization resistance of 0.853 Ω·cm2 than those of the undoped catalyst of La0.9Sr0.8Co0.4Mn0.6O4−δ (R.P.LSCoMn). Mo
Advances in mobile communication networks from 2G to 5G have brought unprecedented traffic growth, and 5G mobile communication networks are expected to be used in a variety of industries based on innovative technologies, fast not only in terms of extremely low latency but massive access devices. Various types of services, such as enhanced mobile broadband (eMBB), massive machine type communication (mMTC), and ultra-reliable and low latency communication (uRLLC), represent an increase in the numb
Flexible materials with sufficient mechanical endurance under bending or folding is essential for flexible electronic devices. Conventional rigid materials such as metals and ceramics are mostly brittle so that their properties can deteriorate under a certain amount of strain. In order to utilize high-performance, but brittle conventional materials in flexible electronics, we propose a novel flexible substrate structure with a low-modulus interlayer. The low-modulus interlayer reduces the surfac
The demand for safe and edible meat has led to the advancement of freeze-storage techniques, but falsely labeled thawed meat remains an issue. Many methods have been proposed for this purpose, but they all destroy the sample and can only be performed in the laboratory by skilled personnel. In this study, hyperspectral image data were used to construct a machine learning (ML) model to discriminate between freshly refrigerated, long-term refrigerated, and thawed beef meat samples. With four pre-pr
Herein, a new ceramic‐based catalyst with exsolved CoFe nanoparticles anchored on the support of a Ruddlesden–Popper structure (La 1.2 Sr 0.8 Co 0.12 Fe 0.88 O 4 ) is synthesized, and various physicochemical analyses are conducted to investigate its applicability as an anode of solid oxide fuel cells (SOFCs). The catalyst is fabricated by reducing La 0.6 Sr 0.4 Co 0.2 Fe 0.8 O 3 in an atmosphere of a 10% H 2 /N 2 gas mixture at 800 °C, whose condition is much milder than the typical synthesis me
Abstract This work presents an analog neuromorphic synapse device consisting of two oxide semiconductor transistors for high‐precision neural networks. One of the two transistors controls the synaptic weight by charging or discharging the storage node, which leads to a conductance change in the other transistor. The programmed weight maintains for more than 300 s as electrons in the storage node are well preserved due to the extremely low off current of the oxide transistor. Ideal synaptic behav
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