arXiv subjects

Ju-Young Kim

Publications and source records attributed to Ju-Young Kim.

9 recordsLinked to original sources

arXiv2026

Vortex-Beam Transient Absorption Microspectroscopy Resolves Ultrafast Free-Exciton and Polaron Diffusion in 2D Perovskites

Two-dimensional (2D) Ruddlesden Popper perovskites are promising optoelectronic materials with strongly confined excitonic properties; however, probing their ultrafast carrier transport dynamics, particularly the initial nonequilibrium diffusion regime, remains challenging because conventional transient absorption microscopy requires complex spatial imaging and lacks sufficient temporal sensitivity to resolve early time diffusion dynamics. Here, we demonstrate a vortex beam based transient absorption microspectroscopy platform (VTAM) enabling imaging free measurement of carrier transport by encoding spatial diffusion information into the mode dependent pump probe signal. By employing vortex probes with different topological charges, VTAM provides mode selective spatial sensitivity to excitonic dynamics with subpicosecond temporal resolution. Using VTAM, we resolved rapid free exciton (FE) diffusion followed by relaxation toward a slower steady state transport regime. A theoretically derived time dependent diffusion model separated transient and steady state transport contributions, yielding a transient diffusion enhancement (68.84 cm2 per s) and a steady state diffusion coefficient (1.85 cm2 per s), thus providing an initial diffusion coefficient (70.69 cm2 per s), and a cooling time of 0.35 ps. Measurements at the exciton-polaron (EP) resonance revealed strongly suppressed diffusion with nearly time independent signal ratios, indicating lattice-coupled EP transport. These parameters were extracted without spatial scanning or image reconstruction, establishing V-TAM as a powerful imaging free platform for investigating carrier transport in perovskites and other semiconductor systems.

physics.optics↗

arXiv2025

SCU-CGAN: Enhancing Fire Detection through Synthetic Fire Image Generation and Dataset Augmentation

Fire has long been linked to human life, causing severe disasters and losses. Early detection is crucial, and with the rise of home IoT technologies, household fire detection systems have emerged. However, the lack of sufficient fire datasets limits the performance of detection models. We propose the SCU-CGAN model, which integrates U-Net, CBAM, and an additional discriminator to generate realistic fire images from nonfire images. We evaluate the image quality and confirm that SCU-CGAN outperforms existing models. Specifically, SCU-CGAN achieved a 41.5% improvement in KID score compared to CycleGAN, demonstrating the superior quality of the generated fire images. Furthermore, experiments demonstrate that the augmented dataset significantly improves the accuracy of fire detection models without altering their structure. For the YOLOv5 nano model, the most notable improvement was observed in the mAP@0.5:0.95 metric, which increased by 56.5%, highlighting the effectiveness of the proposed approach.

cs.CV↗

arXiv2025

Soft Inductive Bias Approach via Explicit Reasoning Perspectives in Inappropriate Utterance Detection Using Large Language Models

Recent incidents in certain online games and communities, where anonymity is guaranteed, show that unchecked inappropriate remarks frequently escalate into verbal abuse and even criminal behavior, raising significant social concerns. Consequently, there is a growing need for research on techniques that can detect inappropriate utterances within conversational texts to help build a safer communication environment. Although large-scale language models trained on Korean corpora and chain-of-thought reasoning have recently gained attention, research applying these approaches to inappropriate utterance detection remains limited. In this study, we propose a soft inductive bias approach that explicitly defines reasoning perspectives to guide the inference process, thereby promoting rational decision-making and preventing errors that may arise during reasoning. We fine-tune a Korean large language model using the proposed method and conduct both quantitative performance comparisons and qualitative evaluations across different training strategies. Experimental results show that the Kanana-1.5 model achieves an average accuracy of 87.0046, improving by approximately 3.89 percent over standard supervised learning. These findings indicate that the proposed method goes beyond simple knowledge imitation by large language models and enables more precise and consistent judgments through constrained reasoning perspectives, demonstrating its effectiveness for inappropriate utterance detection.

cs.CL↗

arXiv2025

Explainable Adversarial-Robust Vision-Language-Action Model for Robotic Manipulation

Smart farming has emerged as a key technology for advancing modern agriculture through automation and intelligent control. However, systems relying on RGB cameras for perception and robotic manipulators for control, common in smart farming, are vulnerable to photometric perturbations such as hue, illumination, and noise changes, which can cause malfunction under adversarial attacks. To address this issue, we propose an explainable adversarial-robust Vision-Language-Action model based on the OpenVLA-OFT framework. The model integrates an Evidence-3 module that detects photometric perturbations and generates natural language explanations of their causes and effects. Experiments show that the proposed model reduces Current Action L1 loss by 21.7% and Next Actions L1 loss by 18.4% compared to the baseline, demonstrating improved action prediction accuracy and explainability under adversarial conditions.

cs.CV↗

arXiv2025

Materials and Design Strategies of Fully 3D Printed Biodegradable Wireless Devices for Biomedical Applications

Three-dimensional (3D) printing of bioelectronics offers a versatile platform for fabricating personalized and structurally integrated electronic systems within biological scaffolds. Biodegradable electronics, which naturally dissolve after their functional lifetime, minimize the long-term burden on both patients and healthcare providers by eliminating the need for surgical retrieval. In this study, we developed a library of 3D-printable, biodegradable electronic inks encompassing conductors, semiconductors, dielectrics, thereby enabling the direct printing of fully functional, multi-material, customizable electronic systems in a single integrated process. Especially, conjugated molecules were introduced to improve charge mobility, energy level alignment in semiconducting inks. This ink platform supports the fabrication of passive/active components and physical/chemical sensors making it suitable for complex biomedical applications. Versatility of this system was demonstrated through two representative applications: (i) wireless pressure sensor embedded within biodegradable scaffolds, (ii) wireless electrical stimulators that retain programmable electrical functionality in vivo and degrade post-implantation. This work establishes a foundation of modules for autonomous, biodegradable bioelectronic systems fabricated entirely via 3D printing, with implications for personalized diagnostics, therapeutic interfaces, and transient medical devices.

physics.med-ph↗

arXiv2024

Nonlinear optical detection of the orbital angular momentum of light

Optical beams carrying orbital angular momentum (OAM) have gained significant interest due to their unique properties, enhancing various communication systems and enabling applications such as the characterization of material or molecular chirality. Generating and detecting the OAM of light is thus crucial for numerous applications but poses challenges. This paper proposes a method utilizing stimulated Raman scattering to detect the magnitude of OAM. By exploring the strong Raman coupling between the pump and Stokes beams in higher-order Laguerre-Gauss modes, we demonstrate the discrimination of different optical vortex beams through nonlinear optical measurements. Numerical and experimental results support the feasibility of this approach, potentially advancing optical communication and sensing technologies.

physics.optics↗

arXiv2023

Lifetime-configurable soft robots via photodegradable silicone elastomer composites

Developing soft robots that can control their own life-cycle and degrade on-demand while maintaining hyper-elasticity is a significant research challenge. On-demand degradable soft robots, which conserve their original functionality during operation and rapidly degrade under specific external stimulation, present the opportunity to self-direct the disappearance of temporary robots. This study proposes soft robots and materials that exhibit excellent mechanical stretchability and can degrade under ultraviolet (UV) light by mixing a fluoride-generating diphenyliodonium hexafluorophosphate (DPI-HFP) with a silicone resin. Spectroscopic analysis revealed the mechanism of Si-O-Si backbone cleavage using fluoride ion (F-), which was generated from UV exposed DPI-HFP. Furthermore, photo-differential scanning calorimetry (DSC) based thermal analysis indicated increased decomposition kinetics at increased temperatures. Additionally, we demonstrated a robotics application of this composite by fabricating a gaiting robot. The integration of soft electronics, including strain sensors, temperature sensors, and photodetectors, expanded the robotic functionalities. This study provides a simple yet novel strategy for designing lifecycle mimicking soft robotics that can be applied to reduce soft robotics waste, explore hazardous areas where retrieval of robots is impossible, and ensure hardware security with on-demand destructive material platforms.

cs.RO↗

arXiv2009

Two-gap and paramagnetic pair-breaking effects on upper critical field of SmFeAsO$_{0.85}$ and SmFeAsO$_{0.8}$F$_{0.2}$ single crystals

We investigated the temperature dependence of the upper critical field [$H_{c2}(T)$] of fluorine-free SmFeAsO$_{0.85}$ and fluorine-doped SmFeAsO$_{0.8}$F$_{0.2}$ single crystals by measuring the resistive transition in low static magnetic fields and in pulsed fields up to 60 T. Both crystals show that $H_{c2}(T)$'s along the c axis [$H_{c2}^c(T)$] and in an $ab$-planar direction [$H_{c2}^{ab}(T)$] exhibit a linear and a sublinear increase, respectively, with decreasing temperature below the superconducting transition. $H_{c2}(T)$'s in both directions deviate from the conventional one-gap Werthamer-Helfand-Hohenberg theoretical prediction at low temperatures. A two-gap nature and the paramagnetic pair-breaking effect are shown to be responsible for the temperature-dependent behavior of $H_{c2}^c$ and $H_{c2}^{ab}$, respectively.

cond-mat.supr-con↗

arXiv2008

High-pressure growth of fluorine-free SmFeAsO$_{1-x}$ superconducting single crystals

Superconducting single crystals of SmFeAsO$_{1-x}$ without fluorine doping were grown at a pressure of 3.3 GPa and a temperature of 1350-1450 $^\circ$C by using the self-flux method. Plate-like single crystals of a few-150 $μ$m in their lateral size were obtained. Single crystals showed the superconducting transition at about 53.5 K with a narrow transition width of 0.5 K. The synchrotron-irradiated x-ray diffractometry patterns and high-angle-annular-dark-field scanning transmission electron microscopy images point to the high quality of the crystals with a well-defined layered tetragonal structure. The chemical compositions of the crystals were estimated by using the electron-probe x-ray microanalysis.

cond-mat.supr-con↗